Recovery RNAseq DOX Data

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Last updated: 2025-04-22

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Knit directory: Recovery_5FU/

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C:/Users/emmap/RDirectory/Recovery_RNAseq/Recovery_5FU/data/ensembl_backup_dox.RDS	data/ensembl_backup_dox.RDS
C:/Users/emmap/RDirectory/Recovery_RNAseq/Recovery_5FU/data/ind_num_dox.RDS	data/ind_num_dox.RDS
C:/Users/emmap/RDirectory/Recovery_RNAseq/Recovery_5FU/data/annot_dox.RDS	data/annot_dox.RDS

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Ignored files:
    Ignored:    .Rhistory
    Ignored:    .Rproj.user/
    Ignored:    analysis/figure/
    Ignored:    data/CDKN1A_geneplot_Dox.RDS
    Ignored:    data/Cormotif_prob_gene_list.RDS
    Ignored:    data/Cormotif_prob_gene_list_doxonly.RDS
    Ignored:    data/DMSO_TNN13_plot.RDS
    Ignored:    data/DOX_TNN13_plot.RDS
    Ignored:    data/DOXgeneplots.RDS
    Ignored:    data/MDM2_geneplot_Dox.RDS
    Ignored:    data/SIRT1_geneplot_Dox.RDS
    Ignored:    data/annot_dox.RDS
    Ignored:    data/cormotifARclust_pp.RDS
    Ignored:    data/counts_DE_df_dox.RDS
    Ignored:    data/ensembl_backup_dox.RDS
    Ignored:    data/filt_gene_list_dox.RDS
    Ignored:    data/gene_clustlike_motif.RDS
    Ignored:    data/gene_postprob_motif.RDS
    Ignored:    data/genematrix_dox.RDS
    Ignored:    data/heartgenes.csv
    Ignored:    data/heartgenes_dox.csv
    Ignored:    data/ind_num_dox.RDS
    Ignored:    data/initial_cormotif.RDS
    Ignored:    data/initial_cormotif_dox.RDS
    Ignored:    data/plot_leg_d.RDS
    Ignored:    data/plot_leg_d_horizontal.RDS
    Ignored:    data/plot_leg_d_vertical.RDS
    Ignored:    data/tableED_GOBP.RDS
    Ignored:    data/tableESR_GOBP_postprob.RDS
    Ignored:    data/tableLD_GOBP.RDS
    Ignored:    data/tableLR_GOBP_postprob.RDS
    Ignored:    data/tableNR_GOBP.RDS
    Ignored:    data/tableNR_GOBP_postprob.RDS
    Ignored:    data/top.table_V.D144r_dox.RDS
    Ignored:    data/top.table_V.D24_dox.RDS
    Ignored:    data/top.table_V.D24r_dox.RDS

Untracked files:
    Untracked:  000037.png
    Untracked:  BCL2A1
    Untracked:  BCL2A1.png
    Untracked:  NBL1.png
    Untracked:  NR1I2.png
    Untracked:  SRMS.png
    Untracked:  logFC_Abs_Motif1_EMP_250422.png
    Untracked:  logFC_Abs_Motif3_EMP_250422.png
    Untracked:  logFC_Abs_Motif4_EMP_250422.png
    Untracked:  logFC_Motif1_EMP_250422.png
    Untracked:  logFC_Motif3_EMP_250422.png
    Untracked:  logFC_Motif4_EMP_250422.png
    Untracked:  top5DE_geneplot_log2cpm_DOX24_EMP_250422.png

Unstaged changes:
    Modified:   analysis/Recovery_DE.Rmd

Note that any generated files, e.g. HTML, png, CSS, etc., are not included in this status report because it is ok for generated content to have uncommitted changes.

---

These are the previous versions of the repository in which changes were made to the R Markdown (analysis/Recovery_DOX.Rmd) and HTML (docs/Recovery_DOX.html) files. If you’ve configured a remote Git repository (see ?wflow_git_remote), click on the hyperlinks in the table below to view the files as they were in that past version.

File	Version	Author	Date	Message
Rmd	4ffd5ad	emmapfort	2025-04-22	Update 04/22/25 logFC motifs
html	ff644ec	emmapfort	2025-04-18	Build site.
Rmd	62c3340	emmapfort	2025-04-18	Updated analysis 25/04/18
Rmd	2f815d2	emmapfort	2025-04-18	Updated analysis 25/04/18
Rmd	424626d	emmapfort	2025-04-15	Add In DOX only set
html	be23fa9	emmapfort	2025-04-15	Build site.
Rmd	ff22325	emmapfort	2025-04-15	workflowr::wflow_publish(files = c("analysis/Recovery_DOX.Rmd"))
Rmd	82840fa	emmapfort	2025-04-15	Updating website
html	84d5599	emmapfort	2025-04-14	Build site.
Rmd	3db2eb6	emmapfort	2025-04-14	DOX only page

---

I want to separate out my dataset for this to only include the DOX and DMSO vehicle samples

fC_Matrix_Full_cpm_filter <- readRDS("data/fC_Matrix_Full_cpm_filter.RDS")

fC_Matrix_Full_cpm_filter_dox <- as.data.frame(fC_Matrix_Full_cpm_filter) %>% dplyr::select(-(contains("FLUO")))
#this dataset is the original log2cpm transformed and rowMeans filtered dataset which I need for heatmaps

counts_DE_df <- readRDS("data/counts_DE_df.RDS")
#this dataframe is pre-filtered and only contains genes (rows) that were present after log2cpm transformation and filtering by rowMeans > 0

DOX_counts_DE_df <- counts_DE_df %>% dplyr::select(-(contains("FLUO")))
dim(DOX_counts_DE_df)

[1] 14170    42

#this should have 42 variables if we remove the 21 variables from 5FU

col_tx_large <- rep(c("#499FBD" , "#63666D"), 21)
col_tx_large_2 <- c(rep("#499FBD" , 3), rep("#63666D", 3), 21)


ind_col <- c("#003F5C", "#45AE91",  "#58508D", "#BC4099", "#8B3E9B", "#FF6361", "#FF2362")

tx_col <- c("#499FBD","#63666D")

time_col <- c("#fbb4b9", "#f768a1", "#ae017e")

##Add columns with more information to each gene I pull out##
ind_names <- c(rep("Ind1", 6), rep("Ind2", 6), rep("Ind3", 6), rep("Ind4", 6), rep("Ind5", 6), rep("Ind6", 6), rep("Ind6REP", 6))
time_names <- c(rep("24", 2), rep("24rec", 2), rep("144rec", 2))
time_names2 <- c("24", "24rec", "144rec")
time_names <- c(rep(time_names, 7))
time_names2 <- c(rep(time_names2, 7))
tx_names <- c("DOX", "DMSO")
tx_names <- c(rep(tx_names, 21))
tx_names2 <- c(rep("DOX", 3), rep("DMSO", 3))
tx_names2 <- c(rep(tx_names2, 21))
txtime_names <- c("DOX_24", "DMSO_24", "DOX_24rec", "DMSO_24rec", "DOX_144rec", "DMSO_144rec")
txtime_names <- c(rep(txtime_names, 7))
txtime_names2 <- c("DOX_24", "DOX_24rec", "DOX_144rec", "DMSO_24", "DMSO_24rec", "DMSO_144rec")
txtime_names2 <- c(rep(txtime_names2, 7))


genematrix_dox <- fC_Matrix_Full_cpm_filter_dox %>% rownames_to_column(var = "entrezgene_id")

#saveRDS(genematrix_dox, "data/genematrix_dox.RDS")

###CDKN1A - 1026###
CDKN1A_d <- genematrix_dox %>% filter(entrezgene_id=="1026")
CDKN1A_new_d <- as.data.frame(CDKN1A_d) %>% dplyr::select("entrezgene_id", "DOX_24_Ind1", "DOX_24rec_Ind1", "DOX_144rec_Ind1", "DMSO_24_Ind1", "DMSO_24rec_Ind1", "DMSO_144rec_Ind1","DOX_24_Ind2", "DOX_24rec_Ind2", "DOX_144rec_Ind2", "DMSO_24_Ind2", "DMSO_24rec_Ind2", "DMSO_144rec_Ind2", "DOX_24_Ind3", "DOX_24rec_Ind3", "DOX_144rec_Ind3",  "DMSO_24_Ind3", "DMSO_24rec_Ind3", "DMSO_144rec_Ind3", "DOX_24_Ind4", "DOX_24rec_Ind4", "DOX_144rec_Ind4", "DMSO_24_Ind4", "DMSO_24rec_Ind4", "DMSO_144rec_Ind4", "DOX_24_Ind5", "DOX_24rec_Ind5", "DOX_144rec_Ind5", "DMSO_24_Ind5", "DMSO_24rec_Ind5", "DMSO_144rec_Ind5", "DOX_24_Ind6", "DOX_24rec_Ind6", "DOX_144rec_Ind6", "DMSO_24_Ind6", "DMSO_24rec_Ind6", "DMSO_144rec_Ind6", "DOX_24_Ind6REP", "DOX_24rec_Ind6REP", "DOX_144rec_Ind6REP", "DMSO_24_Ind6REP", "DMSO_24rec_Ind6REP", "DMSO_144rec_Ind6REP")
CDKN1A_melt_d <- melt(CDKN1A_d, variable.name = "sample")

Using entrezgene_id as id variables

CDKN1A_melt_new_d <- melt(CDKN1A_new_d, variable.name = "sample")

Using entrezgene_id as id variables

CDKN1A_melt_df_d <- data.frame(tx = factor(tx_names, levels = unique(tx_names)),
                               ind = factor(ind_names, levels = unique(ind_names)),
                               txtime = factor(txtime_names, levels = unique(txtime_names)),
                               time = factor(time_names, levels = unique(time_names)))
CDKN1A_melt_df2_d <- data.frame(tx = factor(tx_names2, levels = unique(tx_names2)),
                               ind = factor(ind_names, levels = unique(ind_names)),
                               txtime = factor(txtime_names2, levels = unique(txtime_names2)),
                               time = factor(time_names2, levels = unique(time_names2)))
CDKN1A_melt_df_all_d <- cbind(CDKN1A_melt_d, CDKN1A_melt_df_d)
CDKN1A_melt_df_all2_d <- cbind(CDKN1A_melt_new_d, CDKN1A_melt_df2_d)


####CDKN1A####
CDKN1A_melt_df_all2_d %>% ggplot(aes(x = txtime, y = value))+
  geom_boxplot(aes(fill = tx))+
  geom_point(aes(color = ind)) +
  labs(title = "CDKN1A")+
  theme_bw(base_size = 16)+
  scale_fill_manual(values = c(tx_col))+
  scale_color_manual(values = c(ind_col))+
  xlab("Conditions")+
  ylab("log2cpm")+
  theme(plot.title = element_text(face = "italic"))

Past versions of "Pull out Genes of Interest-1.png"

Version	Author	Date
cee6b3d	emmapfort	2025-04-18
84d5599	emmapfort	2025-04-14

#saveRDS(CDKN1A_geneplot_Dox, "data/CDKN1A_geneplot_Dox.RDS")

###MDM2 - 4193###
MDM2_d <- genematrix_dox %>% filter(entrezgene_id=="4193")
MDM2_new_d <- as.data.frame(MDM2_d) %>% dplyr::select("entrezgene_id", "DOX_24_Ind1", "DOX_24rec_Ind1", "DOX_144rec_Ind1", "DMSO_24_Ind1", "DMSO_24rec_Ind1", "DMSO_144rec_Ind1","DOX_24_Ind2", "DOX_24rec_Ind2", "DOX_144rec_Ind2", "DMSO_24_Ind2", "DMSO_24rec_Ind2", "DMSO_144rec_Ind2", "DOX_24_Ind3", "DOX_24rec_Ind3", "DOX_144rec_Ind3",  "DMSO_24_Ind3", "DMSO_24rec_Ind3", "DMSO_144rec_Ind3", "DOX_24_Ind4", "DOX_24rec_Ind4", "DOX_144rec_Ind4", "DMSO_24_Ind4", "DMSO_24rec_Ind4", "DMSO_144rec_Ind4", "DOX_24_Ind5", "DOX_24rec_Ind5", "DOX_144rec_Ind5", "DMSO_24_Ind5", "DMSO_24rec_Ind5", "DMSO_144rec_Ind5", "DOX_24_Ind6", "DOX_24rec_Ind6", "DOX_144rec_Ind6", "DMSO_24_Ind6", "DMSO_24rec_Ind6", "DMSO_144rec_Ind6", "DOX_24_Ind6REP", "DOX_24rec_Ind6REP", "DOX_144rec_Ind6REP", "DMSO_24_Ind6REP", "DMSO_24rec_Ind6REP", "DMSO_144rec_Ind6REP")
MDM2_melt_d <- melt(MDM2_d, variable.name = "sample")

Using entrezgene_id as id variables

MDM2_melt_new_d <- melt(MDM2_new_d, variable.name = "sample")

Using entrezgene_id as id variables

MDM2_melt_df_d <- data.frame(tx = factor(tx_names, levels = unique(tx_names)),
                               ind = factor(ind_names, levels = unique(ind_names)),
                               txtime = factor(txtime_names, levels = unique(txtime_names)),
                               time = factor(time_names, levels = unique(time_names)))
MDM2_melt_df2_d <- data.frame(tx = factor(tx_names2, levels = unique(tx_names2)),
                               ind = factor(ind_names, levels = unique(ind_names)),
                               txtime = factor(txtime_names2, levels = unique(txtime_names2)),
                               time = factor(time_names2, levels = unique(time_names2)))
MDM2_melt_df_all_d <- cbind(MDM2_melt_d, MDM2_melt_df_d)
MDM2_melt_df_all2_d <- cbind(MDM2_melt_new_d, MDM2_melt_df2_d)

####MDM2####
MDM2_melt_df_all2_d %>% ggplot(aes(x = txtime, y = value))+
  geom_boxplot(aes(fill = tx))+
  geom_point(aes(color = ind)) +
  labs(title = "MDM2")+
  theme_bw(base_size = 16)+
  scale_fill_manual(values = c(tx_col))+
  scale_color_manual(values = c(ind_col))+
  xlab("Conditions")+
  ylab("log2cpm")+
  theme(plot.title = element_text(face = "italic"))

Past versions of "Pull out Genes of Interest-2.png"

Version	Author	Date
cee6b3d	emmapfort	2025-04-18
84d5599	emmapfort	2025-04-14

#saveRDS(MDM2_geneplot_Dox, "data/MDM2_geneplot_Dox.RDS")


###SIRT1 - 23411###
SIRT1_d <- genematrix_dox %>% filter(entrezgene_id=="23411")
SIRT1_new_d <- as.data.frame(SIRT1_d) %>% dplyr::select("entrezgene_id", "DOX_24_Ind1", "DOX_24rec_Ind1", "DOX_144rec_Ind1", "DMSO_24_Ind1", "DMSO_24rec_Ind1", "DMSO_144rec_Ind1","DOX_24_Ind2", "DOX_24rec_Ind2", "DOX_144rec_Ind2", "DMSO_24_Ind2", "DMSO_24rec_Ind2", "DMSO_144rec_Ind2", "DOX_24_Ind3", "DOX_24rec_Ind3", "DOX_144rec_Ind3",  "DMSO_24_Ind3", "DMSO_24rec_Ind3", "DMSO_144rec_Ind3", "DOX_24_Ind4", "DOX_24rec_Ind4", "DOX_144rec_Ind4", "DMSO_24_Ind4", "DMSO_24rec_Ind4", "DMSO_144rec_Ind4", "DOX_24_Ind5", "DOX_24rec_Ind5", "DOX_144rec_Ind5", "DMSO_24_Ind5", "DMSO_24rec_Ind5", "DMSO_144rec_Ind5", "DOX_24_Ind6", "DOX_24rec_Ind6", "DOX_144rec_Ind6", "DMSO_24_Ind6", "DMSO_24rec_Ind6", "DMSO_144rec_Ind6", "DOX_24_Ind6REP", "DOX_24rec_Ind6REP", "DOX_144rec_Ind6REP", "DMSO_24_Ind6REP", "DMSO_24rec_Ind6REP", "DMSO_144rec_Ind6REP")
SIRT1_melt_d <- melt(SIRT1_d, variable.name = "sample")

Using entrezgene_id as id variables

SIRT1_melt_new_d <- melt(SIRT1_new_d, variable.name = "sample")

Using entrezgene_id as id variables

SIRT1_melt_df_d <- data.frame(tx = factor(tx_names, levels = unique(tx_names)),
                               ind = factor(ind_names, levels = unique(ind_names)),
                               txtime = factor(txtime_names, levels = unique(txtime_names)),
                               time = factor(time_names, levels = unique(time_names)))
SIRT1_melt_df2_d <- data.frame(tx = factor(tx_names2, levels = unique(tx_names2)),
                               ind = factor(ind_names, levels = unique(ind_names)),
                               txtime = factor(txtime_names2, levels = unique(txtime_names2)),
                               time = factor(time_names2, levels = unique(time_names2)))
SIRT1_melt_df_all_d <- cbind(SIRT1_melt_d, SIRT1_melt_df_d)
SIRT1_melt_df_all2_d <- cbind(SIRT1_melt_new_d, SIRT1_melt_df2_d)

####SIRT1####
SIRT1_vertplot <- SIRT1_melt_df_all2_d %>% ggplot(aes(x = txtime, y = value))+
  geom_boxplot(aes(fill = tx))+
  geom_point(aes(color = ind)) +
  labs(title = "SIRT1")+
  theme_bw(base_size = 16)+
  scale_fill_manual(values = c(tx_col))+
  scale_color_manual(values = c(ind_col))+
  xlab("Conditions")+
  ylab("log2cpm")+
  theme(plot.title = element_text(face = "italic"))

# get_legend_func <- function(plot) {
#   legends <- cowplot::get_plot_component(plot, "guide-box", return_all = TRUE)
#   nonzero <- vapply(plot_legend_d, \(x) !inherits(x, "zeroGrob"), TRUE)
#   idx <- which(nonzero)
# #this will return the first nonzero legend since it's not in the standard spot

# if (length(idx) >0) {
#   return(legends[[idx[1]]])  
# } else {
#   return(legends[[1]])
# }
# }

# plot_leg_d_hor <- get_legend_func(plot = SIRT1_vertplot + guides(color = guide_legend(nrow=1))+
#     theme(legend.position = "bottom")
# )


plot_leg_d_ver <- cowplot::get_legend(SIRT1_vertplot)

Warning in get_plot_component(plot, "guide-box"): Multiple components found;
returning the first one. To return all, use `return_all = TRUE`.

# ggdraw(plot_leg_d_hor)
ggdraw(plot_leg_d_ver)

Past versions of "Pull out Genes of Interest-3.png"

Version	Author	Date
cee6b3d	emmapfort	2025-04-18
84d5599	emmapfort	2025-04-14

#saveRDS(plot_leg_d_hor, "data/plot_leg_d_horizontal.RDS")
#saveRDS(plot_leg_d_ver, "data/plot_leg_d_vertical.RDS")

#saveRDS(SIRT1_geneplot_Dox, "data/SIRT1_geneplot_Dox.RDS")
#I saved these with no legend

#plot all of these genes together in one set

CDKN1A_geneplot_Dox <- readRDS("data/CDKN1A_geneplot_Dox.RDS")
MDM2_geneplot_Dox <- readRDS("data/MDM2_geneplot_Dox.RDS")
SIRT1_geneplot_Dox <- readRDS("data/SIRT1_geneplot_Dox.RDS")
plot_legend_d_ver <- readRDS("data/plot_leg_d_vertical.RDS")
plot_legend_d_hor <- readRDS("data/plot_leg_d_horizontal.RDS")

DOXgeneplots <- plot_grid(CDKN1A_geneplot_Dox,
                          MDM2_geneplot_Dox, 
                          SIRT1_geneplot_Dox, nrow = 1, ncol = 3)
DOXgeneplots

Past versions of "Pull out Genes of Interest-4.png"

Version	Author	Date
cee6b3d	emmapfort	2025-04-18
84d5599	emmapfort	2025-04-14

#saveRDS(DOXgeneplots, "data/DOXgeneplots.RDS")

genes_dox <- as.data.frame(fC_Matrix_Full_cpm_filter_dox)
genes_dox_df <- rownames_to_column(fC_Matrix_Full_cpm_filter_dox, var = "entrezgene_id")
###now let's pull some classic cardiac genes expressed in iPSC-CMs###
genecardiccheck_dox <- c("MYH7", "TNNT2","MYH6","ACTN2","BMP3","TNNI3","RYR2","CACNA1C","KCNQ1", "HCN1", "ADRB1", "ADRB2")

#ensembl_dox <- useMart("ensembl", dataset="hsapiens_gene_ensembl")
#saveRDS(ensembl_dox, "data/ensembl_backup_dox.RDS")
ensembl_dox <- readRDS("C:/Users/emmap/RDirectory/Recovery_RNAseq/Recovery_5FU/data/ensembl_backup_dox.RDS")
my_chr_dox <- c(1:22, 'M', 'X', 'Y')  ## creates a filter for each database

my_attributes_dox <- c('entrezgene_id', 'ensembl_gene_id', 'hgnc_symbol')

heartgenes_dox <- getBM(attributes=my_attributes_dox,filters ='hgnc_symbol',
                values = genecardiccheck_dox, mart = ensembl_dox)
write.csv(heartgenes_dox, "data/heartgenes_dox.csv")
heartgenes_dox <-read.csv("data/heartgenes_dox.csv")

fungraph_dox <- as.data.frame(fC_Matrix_Full_cpm_filter_dox[rownames(fC_Matrix_Full_cpm_filter_dox) %in% heartgenes_dox$entrezgene_id,])


fungraph_dox %>% 
  rownames_to_column("entrezgene_id") %>% 
  pivot_longer(-entrezgene_id, names_to = "samples",values_to = "counts") %>% 
  mutate(gene = case_match(entrezgene_id,"88"~"ACTN2","153"~"ADRB1",
  "154"~"ADRB2","651"~"BMP3","775"~"CACNA1C", "100874369"~"CACNA1C","348980"~"HCN1",
                           "3784"~"KCNQ1", "4624"~"MYH6","4625"~"MYH7","6262"~"RYR2",
                           "7137"~"TNNI3","7139"~"TNNT2",.default = entrezgene_id)) %>% 
  ggplot(., aes(x=reorder(gene,counts,decreasing=TRUE), y=counts))+
  geom_boxplot()+
  ggtitle(expression("Expression of typical cardiac tissue genes"))+
  xlab("")+
  ylim(c(0,20))+
  ylab(expression("log"[2]~"cpm"))+
  theme_bw()+
  theme(plot.title = element_text(size = rel(2), hjust = 0.5),
        axis.title = element_text(size = 15, color = "black"),
        axis.ticks = element_line(linewidth = 1.5),
        axis.line = element_line(linewidth = 1.5),
        axis.text = element_text(size =10, color = "black", angle = 0),
        strip.text.y = element_text(color = "white"))

Past versions of "Pull Out Some Cardiac Genes-1.png"

Version	Author	Date
cee6b3d	emmapfort	2025-04-18
be23fa9	emmapfort	2025-04-15

#Now I want to plot these with DOX vs Veh to see if there are any changes

#I'll choose a subset of these genes - TNN13, TNNT2, NPPB, MYH7, ACTN2

fungraph_dox_only <- fungraph_dox %>% dplyr::select("DOX_24_Ind1", "DOX_24rec_Ind1", "DOX_144rec_Ind1", "DOX_24_Ind2", "DOX_24rec_Ind2", "DOX_144rec_Ind2", "DOX_24_Ind3", "DOX_24rec_Ind3", "DOX_144rec_Ind3", "DOX_24_Ind4", "DOX_24rec_Ind4", "DOX_144rec_Ind4", "DOX_24_Ind5", "DOX_24rec_Ind5", "DOX_144rec_Ind5", "DOX_24_Ind6", "DOX_24rec_Ind6", "DOX_144rec_Ind6", "DOX_24_Ind6REP", "DOX_24rec_Ind6REP", "DOX_144rec_Ind6REP")

fungraph_dmso_only <- fungraph_dox %>% dplyr::select("DMSO_24_Ind1", "DMSO_24rec_Ind1", "DMSO_144rec_Ind1", "DMSO_24_Ind2", "DMSO_24rec_Ind2", "DMSO_144rec_Ind2", "DMSO_24_Ind3", "DMSO_24rec_Ind3", "DMSO_144rec_Ind3", "DMSO_24_Ind4", "DMSO_24rec_Ind4", "DMSO_144rec_Ind4", "DMSO_24_Ind5", "DMSO_24rec_Ind5", "DMSO_144rec_Ind5", "DMSO_24_Ind6", "DMSO_24rec_Ind6", "DMSO_144rec_Ind6", "DMSO_24_Ind6REP", "DMSO_24rec_Ind6REP", "DMSO_144rec_Ind6REP")

fungraph_dox_only %>% 
  rownames_to_column("entrezgene_id") %>% 
  pivot_longer(-entrezgene_id, names_to = "samples",values_to = "counts") %>% 
  mutate(gene = case_match(entrezgene_id,"88"~"ACTN2","153"~"ADRB1",
  "154"~"ADRB2","651"~"BMP3","775"~"CACNA1C", "100874369"~"CACNA1C","348980"~"HCN1",
                           "3784"~"KCNQ1", "4624"~"MYH6","4625"~"MYH7","6262"~"RYR2",
                           "7137"~"TNNI3","7139"~"TNNT2",.default = entrezgene_id)) %>% 
  ggplot(., aes(x=reorder(gene,counts,decreasing=TRUE), y=counts))+
  geom_boxplot()+
  ggtitle(expression("Expression Cardiac Genes DOX Only"))+
  xlab("")+
  ylim(c(0,20))+
  ylab(expression("log"[2]~"cpm"))+
  theme_bw()+
  theme(plot.title = element_text(size = rel(2), hjust = 0.5),
        axis.title = element_text(size = 15, color = "black"),
        axis.ticks = element_line(linewidth = 1.5),
        axis.line = element_line(linewidth = 1.5),
        axis.text = element_text(size =10, color = "black", angle = 0),
        strip.text.y = element_text(color = "white"))

Past versions of "Pull Out Some Cardiac Genes-2.png"

Version	Author	Date
cee6b3d	emmapfort	2025-04-18
be23fa9	emmapfort	2025-04-15

fungraph_dmso_only %>% 
  rownames_to_column("entrezgene_id") %>% 
  pivot_longer(-entrezgene_id, names_to = "samples",values_to = "counts") %>% 
  mutate(gene = case_match(entrezgene_id,"88"~"ACTN2","153"~"ADRB1",
  "154"~"ADRB2","651"~"BMP3","775"~"CACNA1C", "100874369"~"CACNA1C","348980"~"HCN1",
                           "3784"~"KCNQ1", "4624"~"MYH6","4625"~"MYH7","6262"~"RYR2",
                           "7137"~"TNNI3","7139"~"TNNT2",.default = entrezgene_id)) %>% 
  ggplot(., aes(x=reorder(gene,counts,decreasing=TRUE), y=counts))+
  geom_boxplot()+
  ggtitle(expression("Expression Cardiac Genes Vehicle Only"))+
  xlab("")+
  ylim(c(0,20))+
  ylab(expression("log"[2]~"cpm"))+
  theme_bw()+
  theme(plot.title = element_text(size = rel(2), hjust = 0.5),
        axis.title = element_text(size = 15, color = "black"),
        axis.ticks = element_line(linewidth = 1.5),
        axis.line = element_line(linewidth = 1.5),
        axis.text = element_text(size =10, color = "black", angle = 0),
        strip.text.y = element_text(color = "white"))

Past versions of "Pull Out Some Cardiac Genes-3.png"

Version	Author	Date
cee6b3d	emmapfort	2025-04-18
be23fa9	emmapfort	2025-04-15

#I want to just plot TNNI3 now

fungraph_dox_only_TNNI3 <- fungraph_dox_only %>% 
  rownames_to_column("entrezgene_id") %>% 
  pivot_longer(-entrezgene_id, names_to = "samples",values_to = "counts") %>% 
  filter(entrezgene_id == "7137") %>% 
  mutate(gene = case_match(entrezgene_id,"7137"~"TNNI3",.default = entrezgene_id)) %>% 
  ggplot(., aes(x=reorder(gene,counts,decreasing=TRUE), y=counts))+
  geom_boxplot()+
  ggtitle(expression("TNNI3 DOX"))+
  xlab("")+
  ylim(c(0,10))+
  ylab(expression("log"[2]~"cpm"))+
  theme_bw()+
  theme(plot.title = element_text(size = rel(2), hjust = 0.5),
        axis.title = element_text(size = 15, color = "black"),
        axis.ticks = element_line(linewidth = 1.5),
        axis.line = element_line(linewidth = 1.5),
        axis.text = element_text(size =10, color = "black", angle = 0),
        strip.text.y = element_text(color = "white"))

#saveRDS(fungraph_dox_only_TNNI3, "data/DOX_TNN13_plot.RDS")

fungraph_dmso_only_TNNI3 <- fungraph_dmso_only %>% 
  rownames_to_column("entrezgene_id") %>% 
  pivot_longer(-entrezgene_id, names_to = "samples",values_to = "counts") %>% 
  filter(entrezgene_id == "7137") %>% 
  mutate(gene = case_match(entrezgene_id,"7137"~"TNNI3",.default = entrezgene_id)) %>% 
  ggplot(., aes(x=reorder(gene,counts,decreasing=TRUE), y=counts))+
  geom_boxplot()+
  ggtitle(expression("TNNI3 VEH"))+
  xlab("")+
  ylim(c(0,10))+
  ylab(expression("log"[2]~"cpm"))+
  theme_bw()+
  theme(plot.title = element_text(size = rel(2), hjust = 0.5),
        axis.title = element_text(size = 15, color = "black"),
        axis.ticks = element_line(linewidth = 1.5),
        axis.line = element_line(linewidth = 1.5),
        axis.text = element_text(size =10, color = "black", angle = 0),
        strip.text.y = element_text(color = "white"))

#saveRDS(fungraph_dmso_only_TNNI3, "data/DMSO_TNN13_plot.RDS")

fungraph_dox_only_TNNI3

Past versions of "Pull Out Some Cardiac Genes-4.png"

Version	Author	Date
cee6b3d	emmapfort	2025-04-18
be23fa9	emmapfort	2025-04-15

fungraph_dmso_only_TNNI3

Past versions of "Pull Out Some Cardiac Genes-5.png"

Version	Author	Date
cee6b3d	emmapfort	2025-04-18
be23fa9	emmapfort	2025-04-15

plot_grid(fungraph_dox_only_TNNI3,
                          fungraph_dmso_only_TNNI3, 
                          nrow = 1, ncol = 2)

Past versions of "Pull Out Some Cardiac Genes-6.png"

Version	Author	Date
cee6b3d	emmapfort	2025-04-18
be23fa9	emmapfort	2025-04-15

####SPEARMAN FILTERED####
fC_Matrix_Full_cpm_filter_spearmancor_dox <-
  cor(
    fC_Matrix_Full_cpm_filter_dox,
    y = NULL,
    use = "everything",
    method = "spearman"
  )


Individual <- as.factor(c(rep("Ind1", 6), rep("Ind2", 6), rep("Ind3", 6), rep("Ind4", 6), rep("Ind5", 6), rep("Ind6", 6), rep("Ind6REP", 6)))

#Factor 2 - Treatment
tx_factor <- c("DOX", "DMSO")
Tx <- as.factor(c(rep(tx_factor, 21)))
#view(Treatment)

#Factor 3 - Timepoint
time_factor <- c(rep("24", 2), rep("24rec", 2), rep("144rec", 2))
Time <- as.factor(c(rep(time_factor, 7)))

####annotation for colors####
annot_col_hm = list(Tx = c(DOX = "blue", DMSO = "black"),
                             Ind = c(Ind1 = "#66E2A5", Ind2 = "#FC8D62", Ind3 = "#1F78B4", Ind4 = "#EFEDA3", Ind5 = "#A6D854", Ind6 = "#FFD92A", Ind6REP = "#8B3E9B"),
                             Time = c("24" = "#096F38", "24rec" = "#0050B5", "144rec" = "#B725AD"))

####annotation for values####
annot_list_hm <- data.frame(Individual = as.factor(c(rep("Ind1", 6), rep("Ind2", 6), rep("Ind3", 6), rep("Ind4", 6), rep("Ind5", 6), rep("Ind6", 6), rep("Ind6REP", 6))),
                                               Tx = as.factor(c(rep(tx_factor, 21))), 
                                               Time = as.factor(c(rep(time_factor, 7))))

  
##add in the annotations from above into the dataframe
row.names(annot_list_hm) <- colnames(fC_Matrix_Full_cpm_filter_spearmancor_dox)

####ANNOTATED HEATMAPS####

pheatmap(fC_Matrix_Full_cpm_filter_spearmancor_dox, border_color = "black", legend = TRUE, angle_col = 90, display_numbers = FALSE, number_color = "black", fontsize = 10, fontsize_number = 5, annotation_col = annot_list_hm, annotation_colors = annot_col_hm)

Past versions of "Spearman Heatmap-1.png"

Version	Author	Date
cee6b3d	emmapfort	2025-04-18
84d5599	emmapfort	2025-04-14

#look at the correlation between samples with boxplots using my Spearman dataset
#set1 - all samples
All_Spearman <- as.data.frame(fC_Matrix_Full_cpm_filter_spearmancor_dox) %>% 
  rownames_to_column(var = "Sample")
  

#set2 - exact matches with Ind 6 + Ind 6 REP DOX24
Ind6_Spearman <- as.data.frame(fC_Matrix_Full_cpm_filter_spearmancor_dox) %>% 
  dplyr::select(contains("Ind6")) %>% 
  rownames_to_column(var = "Sample")
  

#set 3 - all samples from rep ind

Now that I’ve put together my data, let’s begin DE!

group_1d <- rep(c("DOX_24",
                  "DMSO_24",
                  "DOX_24rec", 
                  "DMSO_24rec",
                  "DOX_144rec",
                  "DMSO_144rec"), 6)

group_2d <- rep(c("DOX_24",
                  "DMSO_24",
                  "DOX_24rec",
                  "DMSO_24rec",
                  "DOX_144rec",
                  "DMSO_144rec"), 7)

dge_d <- DGEList.data.frame(counts = DOX_counts_DE_df, group = group_2d, genes = row.names(DOX_counts_DE_df))


#calculate the normalization factors with method TMM
dged_calc <- calcNormFactors(dge_d, method = "TMM")


#Pull out factors
snames_d <- data.frame("samples" = colnames(dged_calc)) %>% separate_wider_delim(., cols = samples, names = c("Treatment", "Time", "Individual"), delim = "_", cols_remove = FALSE)

snames_time_d <- snames_d$Time
snames_tx_d <- snames_d$Treatment
snames_ind_d <- snames_d$Individual

#Create my model matrix
mm_r_d <- model.matrix(~0 + group_2d)

p_d <- voom(dged_calc$counts, mm_r_d, plot = TRUE)

Past versions of "Differential Expression Analysis-1.png"

Version	Author	Date
cee6b3d	emmapfort	2025-04-18
84d5599	emmapfort	2025-04-14

corfit_d <- duplicateCorrelation(p_d, mm_r_d, block = snames_ind_d)

v_d <- voom(dged_calc$counts, mm_r_d, block = snames_ind_d, correlation = corfit_d$consensus)

fit_d <- lmFit(v_d, mm_r_d, block = snames_ind_d, correlation = corfit_d$consensus)

#make sure to check which order the columns are in - otherwise they won't match right (it was moved into alphabetical and number order)
colnames(mm_r_d) <- c("DMSO_144rec","DMSO_24","DMSO_24rec","DOX_144rec","DOX_24","DOX_24rec")

cm_r_d <- makeContrasts(
        V.D24 = DOX_24 - DMSO_24,
        V.D24r = DOX_24rec - DMSO_24rec,
        V.D144r = DOX_144rec - DMSO_144rec,
        levels = mm_r_d
)

vfit_r_d <- lmFit(p_d, mm_r_d)
vfit_r_d <- contrasts.fit(vfit_r_d, contrasts = cm_r_d)

efit2_d <- eBayes(vfit_r_d)

results_d = decideTests(efit2_d)
summary(results_d)
       V.D24 V.D24r V.D144r
Down    9709   6869      31
NotSig  3276   6379   13680
Up      1185    922     459
# #       V.D24 V.D24r V.D144r
# Down    9709   6869      31
# NotSig  3276   6379   13680
# Up      1185    922     459

####plot your voom####
voom_plot_d <- voom(dged_calc, mm_r_d, plot = TRUE)

Past versions of "Differential Expression Analysis-2.png"

Version	Author	Date
cee6b3d	emmapfort	2025-04-18
84d5599	emmapfort	2025-04-14

top.table_V.D24_dox <- topTable(fit = efit2_d, coef = "V.D24", number = nrow(dged_calc), adjust.method = "BH", p.value = 1, sort.by = "none")
head(top.table_V.D24_dox)

              logFC  AveExpr         t      P.Value    adj.P.Val         B
100287102 -1.804419 5.673476 -1.741845 8.886085e-02 1.088296e-01 -4.985757
102466751 -1.386392 6.598993 -2.215141 3.223163e-02 4.236756e-02 -4.208131
100302278  2.117211 4.110796  5.136780 6.832114e-06 1.543790e-05  3.484472
645520    -1.060785 3.557889 -2.870907 6.387858e-03 9.406209e-03 -3.056843
79501     -1.851133 3.191793 -7.289085 5.649161e-09 1.915955e-08 10.231400
102725121 -2.392951 5.717312 -2.447792 1.863753e-02 2.550153e-02 -3.658644

#saveRDS(top.table_V.D24_dox, "data/top.table_V.D24_dox.RDS")

top.table_V.D24r_dox <- topTable(fit = efit2_d, coef = "V.D24r", number = nrow(dged_calc), adjust.method = "BH", p.value = 1, sort.by = "none")
head(top.table_V.D24r_dox)

               logFC  AveExpr          t    P.Value  adj.P.Val         B
100287102  0.2141767 5.673476  0.2255907 0.82261472 0.86440123 -6.218826
102466751 -0.8094950 6.598993 -1.3328291 0.18977853 0.26317888 -5.413117
100302278 -0.8734257 4.110796 -1.7817528 0.08202618 0.12937566 -4.863398
645520    -0.1192432 3.557889 -0.2881042 0.77468499 0.82587957 -6.419091
79501     -0.6825584 3.191793 -2.3475219 0.02368945 0.04379952 -4.150543
102725121  0.3419483 5.717312  0.3858246 0.70157538 0.76548265 -6.184783

#saveRDS(top.table_V.D24r_dox, "data/top.table_V.D24r_dox.RDS")

top.table_V.D144r_dox <- topTable(fit = efit2_d, coef = "V.D144r", number = nrow(dged_calc), adjust.method = "BH", p.value = 1, sort.by = "none")
head(top.table_V.D144r_dox)

                logFC  AveExpr          t    P.Value adj.P.Val         B
100287102 -0.42467259 5.673476 -0.4139649 0.68100778 0.9656919 -6.176321
102466751 -0.04911403 6.598993 -0.0842465 0.93326102 0.9658168 -6.400185
100302278  0.32459251 4.110796  1.0815817 0.28561401 0.8618346 -6.375234
645520    -0.46815849 3.557889 -1.2874535 0.20499081 0.7713611 -5.861459
79501      0.56678196 3.191793  1.9032026 0.06388777 0.4666442 -5.076972
102725121  0.18759316 5.717312  0.1938705 0.84721256 0.9656919 -6.246426

#saveRDS(top.table_V.D144r_dox, "data/top.table_V.D144r_dox.RDS")


#plot the top 5 most DE genes for each condition
#i sorted the toptable by the top 5 most DE genes for each + found the corresponding gene name
#####24hr Tx####
topDEG_dox24 <- top.table_V.D24_dox %>% 
  dplyr::slice_min(., n=5, order_by=P.Value) %>% 
  rownames_to_column(var = "GeneID")

Gene_Name <- c("FAM163A","SLC26A8","THBS-AS1","FOXD3-AS1","GRIK3")

topDEG_dox24 %>% mutate(GeneID = factor(GeneID, levels = c("148753", "116369", "101929523", "100996301", "2899"))) %>% 
  cbind(Gene_Name)

     GeneID     logFC  AveExpr         t      P.Value    adj.P.Val        B
1    148753  6.274101 5.578715  22.98007 2.128816e-25 3.016533e-21 47.14980
2    116369  5.789178 6.348094  20.56787 1.542184e-23 1.092637e-19 43.01677
3 101929523 -6.034510 6.305356 -19.08546 2.647316e-22 1.004705e-18 39.91738
4 100996301  5.149384 5.289969  18.98930 3.202808e-22 1.004705e-18 40.23872
5      2899  5.508418 5.862853  18.93819 3.545183e-22 1.004705e-18 40.05644
  Gene_Name
1   FAM163A
2   SLC26A8
3  THBS-AS1
4 FOXD3-AS1
5     GRIK3

#top 5 DE genes based on p-value and adj p value 
ggplot(topDEG_dox24, aes(x=Gene_Name, y=logFC))+
  geom_boxplot(aes(colour = adj.P.Val))+
  ggtitle(expression("Top 5 DE Genes DOX 24"))+
  xlab("")+
  ylim(c(-10, 10))+
  ylab(expression("logFC"))+
  theme_bw()+
  theme(plot.title = element_text(size = rel(1.5)),
        axis.title = element_text(size = 15, color = "black"),
        axis.ticks = element_line(linewidth = 1.5),
        axis.line = element_line(linewidth = 1.5),
        axis.text = element_text(size =10, color = "black", angle = 0),
        strip.text.y = element_text(color = "white"))

Past versions of "Make Toptables Of Each Condition-1.png"

Version	Author	Date
ff644ec	emmapfort	2025-04-18

####24hr Recovery####
topDEG_dox24R <- top.table_V.D24r_dox %>% 
  dplyr::slice_min(., n=5, order_by=P.Value) %>% 
  rownames_to_column(var = "GeneID")

Gene_Name1 <- c("KCNK10", "CSTA", "LCE1B", "OTP", "KRTAP19-1")

topDEG_dox24R %>% mutate(GeneID = factor(GeneID, levels = c("54207", "1475", "353132", "23440", "337882"))) %>% 
  cbind(Gene_Name1)

  GeneID    logFC  AveExpr        t      P.Value    adj.P.Val        B
1  54207 4.949406 6.530192 15.82299 2.695651e-19 2.698663e-15 33.02274
2   1475 5.603936 5.360183 15.67190 3.808981e-19 2.698663e-15 32.95920
3 353132 4.839166 4.461296 14.34492 8.816170e-18 4.164171e-14 30.06752
4  23440 5.863845 6.216741 13.53171 6.670038e-17 2.362861e-13 27.67891
5 337882 6.367767 5.675415 13.17894 1.644191e-16 4.659637e-13 27.24446
  Gene_Name1
1     KCNK10
2       CSTA
3      LCE1B
4        OTP
5  KRTAP19-1

ggplot(topDEG_dox24R, aes(x=Gene_Name1, y=logFC))+
  geom_boxplot(aes(colour = adj.P.Val))+
  ggtitle(expression("Top 5 DE Genes DOX 24 Recovery"))+
  xlab("")+
  ylim(c(-10,10))+
  ylab(expression("logFC"))+
  theme_bw()+
  theme(plot.title = element_text(size = rel(1.5)),
        axis.title = element_text(size = 15, color = "black"),
        axis.ticks = element_line(linewidth = 1.5),
        axis.line = element_line(linewidth = 1.5),
        axis.text = element_text(size =10, color = "black", angle = 0),
        strip.text.y = element_text(color = "white"))

Past versions of "Make Toptables Of Each Condition-2.png"

Version	Author	Date
ff644ec	emmapfort	2025-04-18

####144R####
topDEG_dox144R <- top.table_V.D144r_dox %>% 
  dplyr::slice_min(., n=5, order_by=P.Value) %>% 
  rownames_to_column(var = "GeneID")

Gene_Name2 <- c("LINC03025", "SLC4A10", "VIT", "PSMA8", "MYO3B")

topDEG_dox144R %>% mutate(GeneID = factor(GeneID, levels = c("440896", "57282", "5212", "143471", "140469"))) %>% 
  cbind(Gene_Name2)

  GeneID    logFC  AveExpr        t      P.Value    adj.P.Val        B
1 440896 4.681589 4.937852 13.65775 4.849711e-17 6.872040e-13 28.36219
2  57282 4.710121 5.295198 12.59160 7.637380e-16 5.411084e-12 25.77519
3   5212 3.923330 4.773412 12.10946 2.782463e-15 1.314250e-11 24.40702
4 143471 3.521809 4.241896 11.71091 8.284121e-15 2.643174e-11 23.33360
5 140469 4.647516 6.057544 11.66805 9.326656e-15 2.643174e-11 23.23254
  Gene_Name2
1  LINC03025
2    SLC4A10
3        VIT
4      PSMA8
5      MYO3B

ggplot(topDEG_dox144R, aes(x=Gene_Name2, y=logFC))+
  geom_boxplot(aes(colour = adj.P.Val))+
  ggtitle(expression("Top 5 DE Genes DOX 144 Recovery"))+
  xlab("")+
  ylim(c(-10,10))+
  ylab(expression("logFC"))+
  theme_bw()+
  theme(plot.title = element_text(size = rel(1.5)),
        axis.title = element_text(size = 15, color = "black"),
        axis.ticks = element_line(linewidth = 1.5),
        axis.line = element_line(linewidth = 1.5),
        axis.text = element_text(size =10, color = "black", angle = 0),
        strip.text.y = element_text(color = "white"))

Past versions of "Make Toptables Of Each Condition-3.png"

Version	Author	Date
ff644ec	emmapfort	2025-04-18

generate_volcano_plot <- function(toptable, title) {
  
  #make significance labels
  toptable$Significance <- "Not Significant"
  toptable$Significance[toptable$logFC > 0 & toptable$adj.P.Val < 0.05] <- "Upregulated"
  toptable$Significance[toptable$logFC < 0 & toptable$adj.P.Val < 0.05] <- "Downregulated"
  
  #add number of genes for each significance label
  upgenes <- toptable %>% filter(Significance == "Upregulated") %>% nrow()
  downgenes <- toptable %>% filter(Significance == "Downregulated") %>% nrow()
  nsgenes <- toptable %>% filter(Significance == "Not Significant") %>% nrow()

  #make legend labels for no of genes
  legend_lab <- c(
    str_c('Upregulated: ', upgenes),
    str_c('Not Significant: ', nsgenes),
    str_c('Downregulated: ', downgenes)
  )

  #generate volcano plot w/ legend
  ggplot(toptable, aes(x = logFC, y = -log10(P.Value), color = Significance)) +
    geom_point(alpha = 0.4, size = 2) + 
    scale_color_manual(values = c("Upregulated" = "blue", "Downregulated" = "red", "Not Significant" = "gray"), labels = legend_lab) +
    xlim(-5, 5) +
    labs(title = title, x = expression(x = "log"[2]*"FC"), y = expression(y = "-log"[10]*"P-value")) +
    theme(legend.position = "none", 
          plot.title = element_text(size = rel(1.5), hjust = 0.5),
          axis.title = element_text(size = rel(1.25))) +
    theme_bw()
}

#now that I've made a function, I can make volcano plots for each of my comparisons (6 total)

volcano_plots <- list(
  "V.D24" = generate_volcano_plot(top.table_V.D24_dox, "Volcano Plot DOX 24hr (adj P-val<0.05)"),
  "V.D24r" = generate_volcano_plot(top.table_V.D24r_dox, "Volcano Plot DOX 24hr Recovery (adj P-val<0.05)"),
  "V.D144r" = generate_volcano_plot(top.table_V.D144r_dox, "Volcano Plot DOX 144hr Recovery (adj P-val<0.05)")
)

# Display each volcano plot
for (plot_name in names(volcano_plots)) {
  print(volcano_plots[[plot_name]])
}

Warning: Removed 90 rows containing missing values or values outside the scale range
(`geom_point()`).

Past versions of "Volcano Plots from Pairwise Gene Analysis-1.png"

Version	Author	Date
cee6b3d	emmapfort	2025-04-18
84d5599	emmapfort	2025-04-14

Warning: Removed 11 rows containing missing values or values outside the scale range
(`geom_point()`).

Past versions of "Volcano Plots from Pairwise Gene Analysis-2.png"

Version	Author	Date
cee6b3d	emmapfort	2025-04-18
84d5599	emmapfort	2025-04-14

Past versions of "Volcano Plots from Pairwise Gene Analysis-3.png"

Version	Author	Date
cee6b3d	emmapfort	2025-04-18
84d5599	emmapfort	2025-04-14

#I want to add the number of DEG onto this for each
#make each volcano plot into an object so I can see how many rows it has

# Alternative function from Renee to combine them all into one image
# volcanosig <- function(df, psig.lvl,topg) {
#     df <- df %>% 
#     mutate(threshold = ifelse(adj.P.Val > psig.lvl, "A", ifelse(adj.P.Val <= psig.lvl & logFC<=0,"B","C")))
#     
#   ggplot(df, aes(x=logFC, y=-log10(adj.P.Val))) + 
#     geom_point(aes(color=threshold))+
#     xlab(expression("Log"[2]*" FC"))+
#     ylim(0,30)+
#     ylab(expression("-log"[10]*"P Value"))+
#     scale_color_manual(values = c("black", "red","blue"))+
#     theme_cowplot()+
#     theme(legend.position = "none",
#           plot.title = element_text(size = rel(0.8), hjust = 0.5),
#           axis.title = element_text(size = rel(0.8))) 
# }
# 
# vol1 <- volcanosig(top.table_V.D24_dox, 0.01,0)+ ggtitle("Doxorubicin \n 24 hour")
# vol2 <- volcanosig(top.table_V.D24r_dox, 0.01,0)+ ggtitle("Doxorubicin \n 24 hour Recovery")
# vol3 <- volcanosig(top.table_V.D144r_dox, 0.01,0)+ ggtitle("Doxorubicin\n 144 hour Recovery")+ylab("")
# 
# 
# Volcanoplots <- plot_grid(vol1,vol2,vol3, nrow = 1, ncol = 3)
# Volcanoplots

#now like the hypoxia paper, I'd like to put together comparisons between samples and conditions to check if they are more similar than others

PCA_data_d <- fC_Matrix_Full_cpm_filter_dox %>% 
  prcomp(.) %>% 
  t()

PCA_data_test_d <- (prcomp(t(fC_Matrix_Full_cpm_filter_dox), scale. = TRUE))


#ind_num_dox <- c("1", "1", "1", "1", "1", "1", "2", "2", "2", "2", "2", "2", "3", "3", "3", "3", "3", "3", "4", "4", "4", "4", "4", "4","5", "5", "5", "5", "5", "5", "6", "6", "6", "6", "6", "6", "6R", "6R", "6R", "6R", "6R", "6R")

#saveRDS(ind_num_dox, "data/ind_num_dox.RDS")

ind_num_dox <- readRDS("C:/Users/emmap/RDirectory/Recovery_RNAseq/Recovery_5FU/data/ind_num_dox.RDS")

####now make an annotation for my PCA####
annot_d <- data.frame("samples" = colnames(fC_Matrix_Full_cpm_filter_dox)) %>% separate_wider_delim(., cols = samples, names = c("Tx", "Time", "Ind"), delim = "_", cols_remove = FALSE) %>% unite(., col = "Tx_Time", Tx, Time, sep = "_", remove = FALSE) %>% cbind(., ind_num_dox)

#saveRDS(annot_d, "C:/Users/emmap/RDirectory/Recovery_RNAseq/Recovery_5FU/data/annot_dox.RDS")


#combine the prcomp matrix and annotation
annot_PCA_matrix_d <- PCA_data_test_d$x %>% cbind(., annot_d)


#now I can make a graph where I have filled values for individual! I have seven colors for seven individuals
# I have three fill values for three timepoints

#using annotation matrix above as well as annotated PCA matrix #(annot_PCA_matrix)

#extra info for colors in the graph (fill parameter)
fill_col_ind <- c("#66C2A5", "#FC8D62", "#1F78B4", "#E78AC3", "#A6D854", "#FFD92A", "#8B3E9B")

fill_col_ind_dark <- c("#003F5C", "#45AE91",  "#58508D", "#BC4099", "#8B3E9B", "#FF6361", "#FF2362")

fill_col_tx_dox <- c("#63666D", "#499FBD")

fill_col_txtime_d <- c("#45AE91",  "#58508D", "#BC4099", "#FF2362", "#A6D854", "#FC8D62")

#I want the color parameter to be treatment, the shape as time, and individual as number

####PC1/PC2####
annot_PCA_matrix_d %>% ggplot(., aes(x=PC1, y=PC2, size=10)) +
  geom_point(aes(color = Tx, shape = Time)) +
  scale_color_manual(values = c(fill_col_tx_dox))+
  scale_shape_manual(values = c(15, 19, 17))+
  geom_text_repel(aes(label = ind_num_dox))+
  theme_bw(base_size = 10)+
  ggtitle(expression("PCA of filtered log"[2]*"cpm"))+
  guides(size="none")

Warning: ggrepel: 27 unlabeled data points (too many overlaps). Consider
increasing max.overlaps

Past versions of "DOX only PCA plots no RUVs-1.png"

Version	Author	Date
cee6b3d	emmapfort	2025-04-18
84d5599	emmapfort	2025-04-14

####PC1/PC2 autoplot####
prcomp_res_d <- prcomp(t(fC_Matrix_Full_cpm_filter_dox), scale. = FALSE, center = TRUE)
annot_prcomp_res_d <- prcomp_res_d$x %>% cbind(., annot_d)

ggplot2::autoplot(prcomp_res_d, data = annot_d, colour = "Tx_Time", size =4)+
  theme_bw()+
  scale_color_manual(values = c(fill_col_txtime_d))+
  ggrepel::geom_text_repel(label= ind_num_dox)+
  ggtitle("PCA of DOX filtered log2cpm")

Warning: ggrepel: 8 unlabeled data points (too many overlaps). Consider
increasing max.overlaps

Past versions of "DOX only PCA plots no RUVs-2.png"

Version	Author	Date
cee6b3d	emmapfort	2025-04-18
84d5599	emmapfort	2025-04-14

####PC2/PC3####
annot_PCA_matrix_d %>% ggplot(., aes(x=PC2, y=PC3, size=10)) +
  geom_point(aes(color = Tx, shape = Time)) +
  scale_color_manual(values = c(fill_col_tx_dox))+
  scale_shape_manual(values = c(15, 19, 17))+
  geom_text_repel(aes(label = ind_num_dox))+
  theme_bw(base_size = 10)+
  ggtitle(expression("PCA of filtered log"[2]*"cpm"))+
  guides(size="none")

Warning: ggrepel: 7 unlabeled data points (too many overlaps). Consider
increasing max.overlaps

Past versions of "DOX only PCA plots no RUVs-3.png"

Version	Author	Date
cee6b3d	emmapfort	2025-04-18
84d5599	emmapfort	2025-04-14

####PC3/PC4####
annot_PCA_matrix_d %>% ggplot(., aes(x=PC3, y=PC4, size=10)) +
  geom_point(aes(color = Tx, shape = Time)) +
  scale_color_manual(values = c(fill_col_tx_dox))+
  scale_shape_manual(values = c(15, 19, 17))+
  geom_text_repel(aes(label = ind_num_dox))+
  theme_bw(base_size = 10)+
  ggtitle(expression("PCA of filtered log"[2]*"cpm"))+
  guides(size="none")

Past versions of "DOX only PCA plots no RUVs-4.png"

Version	Author	Date
cee6b3d	emmapfort	2025-04-18
84d5599	emmapfort	2025-04-14

fC_Matrix_Full <- readRDS("data/fC_Matrix_Full.RDS")

fC_Matrix_Full_dox <- as.data.frame(fC_Matrix_Full) %>% dplyr::select(-(contains("FLUO")))

Counts_Full_df_dox <- data.frame(fC_Matrix_Full_dox)

#filter this dataframe by the filtered gene list I have
filt_gene_list_dox <- row.names(fC_Matrix_Full_cpm_filter_dox)
#saveRDS(filt_gene_list_dox, "data/filt_gene_list_dox.RDS")

counts_DE_df_dox <- Counts_Full_df_dox[! (rownames(Counts_Full_df_dox) %in% filt_gene_list_dox), ]

#saveRDS(counts_DE_df_dox, "data/counts_DE_df_dox.RDS")

RUV_filt_counts_dox <- fC_Matrix_Full_dox %>% 
  as.data.frame() %>% 
  dplyr::filter(., row.names(.)%in% filt_gene_list_dox)

#add in the annotation files
ind_num_dox <- readRDS("C:/Users/emmap/RDirectory/Recovery_RNAseq/Recovery_5FU/data/ind_num_dox.RDS")
annot_d <- readRDS("C:/Users/emmap/RDirectory/Recovery_RNAseq/Recovery_5FU/data/annot_dox.RDS")


#  counts need to be integer values and in a numeric matrix
# note: the log transformation needs to be accounted for in the isLog argument in RUVs function.
counts_d <- as.matrix(RUV_filt_counts_dox)
dim(counts_d)

[1] 14225    42

#14225 genes
# Create a DataFrame for the phenoData
phenoData_d <- DataFrame(annot_d)

# Now create the RangedSummarizedExperiment necessary for RUVs input
# looks like it did need both the phenodata and the counts.
set_dox <- SummarizedExperiment(assays =  counts_d, metadata = phenoData_d)

# Generate a background matrix
# The column "Cond" holds the comparisons that you actually want to make. DOX_24, DMSO_24,5FU_24, DOX_3,etc.
scIdx_d <-RUVSeq::makeGroups(phenoData_d$Tx_Time)
scIdx_d

     [,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,]    6   12   18   24   30   36   42
[2,]    2    8   14   20   26   32   38
[3,]    4   10   16   22   28   34   40
[4,]    5   11   17   23   29   35   41
[5,]    1    7   13   19   25   31   37
[6,]    3    9   15   21   27   33   39

#now I've made all of the data I need for this - they are located in each section for k values

#DO NOT USE THESE COUNTS FOR LINEAR MODELING

#colors for all of the plots
fill_col_ind <- c("#66C2A5", "#FC8D62", "#1F78B4", "#E78AC3", "#A6D854", "#FFD92A", "#8B3E9B")

fill_col_ind_dark <- c("#003F5C", "#45AE91",  "#58508D", "#BC4099", "#8B3E9B", "#FF6361", "#FF2362")

fill_col_tx_dox <- c("#63666D", "#499FBD")

fill_col_txtime_dox <- c("#45AE91",  "#58508D", "#BC4099", "#FF2362", "#A6D854", "#FC8D62")

# before ruv
prcomp_res_d <- prcomp(t(counts_d), scale. = FALSE, center = TRUE)
ggplot2::autoplot(prcomp_res_d, data = annot_d, colour = "Tx_Time", size =4)+
  theme_bw()+
  scale_color_manual(values = c(fill_col_txtime_dox))+
  ggrepel::geom_text_repel(label= ind_num_dox)+
  ggtitle("No RUV")

Past versions of "RUVs Correction Start DOX Only Set-1.png"

Version	Author	Date
cee6b3d	emmapfort	2025-04-18
84d5599	emmapfort	2025-04-14

####new PCA plots no correction####
#PCA plots for each value of k attached in each section
prcomp_res_d <- prcomp(t(counts_d), scale. = FALSE, center = TRUE)
annot_prcomp_res_d <- prcomp_res_d$x %>% cbind(., annot_d)

group_2d <- rep(c("DOX_24",
                  "DMSO_24",
                  "DOX_24rec",
                  "DMSO_24rec",
                  "DOX_144rec",
                  "DMSO_144rec"), 7)


dge1_d <- DGEList.data.frame(counts = fC_Matrix_Full_dox, group = group_2d, genes = row.names(fC_Matrix_Full_dox))

#calculate the normalization factors with method TMM
dge1_calc_d <- calcNormFactors(dge1_d, method = "TMM")

#Pull out factors
snames1_d <- data.frame("samples" = colnames(dge1_calc_d)) %>% separate_wider_delim(., cols = samples, names = c("Treatment", "Time", "Individual"), delim = "_", cols_remove = FALSE)

snames1_ind_d <- snames1_d$Individual

#Apply RUVs function from RUVSeq
#"k" will be iteratively adjusted over time depending on your PCA.
set_d <- RUVSeq::RUVs(x = counts_d, k =1, scIdx = scIdx_d, isLog = FALSE)

#get the ruv weights to put into the linear model. n weights = k.
#k=1
RUV_df_d <- set_d$W %>% as.data.frame()
RUV_df_d$Names <- rownames(RUV_df_d)


#Check that the names match
#k=1
RUV_df_rm_d <- RUV_df_d[RUV_df_d$Names %in% annot_d$samples, ] 
RUV_1_d <-  RUV_df_rm_d$W_1

# after ruv k=1

#PCA checks
#k=1
prcomp_res_1_d <- prcomp(t(set_d$normalizedCounts), scale. = FALSE, center = TRUE)
annot_prcomp_res_1_d <- prcomp_res_1_d$x %>% cbind(., annot_d)

ggplot2::autoplot(prcomp_res_1_d, data = annot_d, colour = "Tx_Time", size =4)+
  theme_bw()+
  scale_color_manual(values = c(fill_col_txtime_dox))+
  ggrepel::geom_text_repel(label= ind_num_dox)+
  ggtitle("RUVs Correction k=1")

Warning: ggrepel: 5 unlabeled data points (too many overlaps). Consider
increasing max.overlaps

Past versions of "RUVs k1 DOX only set-1.png"

Version	Author	Date
cee6b3d	emmapfort	2025-04-18
84d5599	emmapfort	2025-04-14

#k=1
annot_d$samples == RUV_df_rm_d$Names

 [1] TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
[16] TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
[31] TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE

annot_d$RUV_1_d <- RUV_df_rm_d$W_1

#Create my model matrix
#k=1
mm_r1_d <- model.matrix(~0 + group_2d + RUV_1_d, data = annot_d)

p1_d <- voom(dge1_calc_d$counts, mm_r1_d, plot = TRUE)

Past versions of "RUVs k1 DOX only set-2.png"

Version	Author	Date
cee6b3d	emmapfort	2025-04-18
84d5599	emmapfort	2025-04-14

corfit1_d <- duplicateCorrelation(p1_d, mm_r1_d, block = snames1_ind_d)

v1_d <- voom(dge1_calc_d$counts, mm_r1_d, block = snames1_ind_d, correlation = corfit1_d$consensus)

fit1_d <- lmFit(v1_d, mm_r1_d, block = snames1_ind_d, correlation = corfit1_d$consensus)

#k=1
mm_r1_names_d <- str_replace(string = colnames(mm_r1_d), pattern = "group_2d", replacement = "")
design_d <- model.matrix(~ group_2d + RUV_1_d , annot_d)
colnames(mm_r1_d) <- mm_r1_names_d

#k=1
cm_r1_d <- makeContrasts(
        V.D24 = DOX_24 - DMSO_24,
        V.D24r = DOX_24rec - DMSO_24rec,
        V.D144r = DOX_144rec - DMSO_144rec,
        RUV_1_24 = RUV_1_d - DMSO_24,
        RUV_1_24r= RUV_1_d - DMSO_24rec,
        RUV_1_144r = RUV_1_d - DMSO_144rec,
        levels = mm_r1_d
)

#k=1
vfit_r1_d <- lmFit(p1_d, mm_r1_d)
vfit_r1_d <- contrasts.fit(vfit_r1_d, contrasts = cm_r1_d)

#k=1
efit1_d <- eBayes(vfit_r1_d)

#k=1
results1_d = decideTests(efit1_d)
summary(results1_d)

       V.D24 V.D24r V.D144r RUV_1_24 RUV_1_24r RUV_1_144r
Down    5222   2650     486    13532     13539      13491
NotSig 14886  16841   26921     1645      1641       1721
Up      8287   8904     988    13218     13215      13183

#         V.D24 V.D24r V.D144r RUV_1_24 RUV_1_24r RUV_1_144r
# Down    5222   2650     486    13532     13539      13491
# NotSig 14886  16841   26921     1645      1641       1721
# Up      8287   8904     988    13218     13215      13183

#k=1
toptable_Dupcor_DOX_d <- topTable(efit1_d, coef = "V.D24", number = nrow(dge1_calc_d$counts), p.value = 1)
toptable_Dupcor_DOXrec_d <- topTable(efit1_d, coef = "V.D24r", number = nrow(dge1_calc_d$counts), p.value = 1)
toptable_Dupcor_DOX144_d <- topTable(efit1_d, coef = "V.D144r", number = nrow(dge1_calc_d$counts), p.value = 1)
#k=1 plots
toptable_Dupcor_DOX_d$logFC %>% hist(, main= "RUVs k=1 DOX 24hr Toptable")

Past versions of "RUVs k1 DOX only set-3.png"

Version	Author	Date
cee6b3d	emmapfort	2025-04-18
84d5599	emmapfort	2025-04-14

toptable_Dupcor_DOXrec_d$logFC %>% hist(, main = "RUVs k=1 DOX 24Rec Toptable")

Past versions of "RUVs k1 DOX only set-4.png"

Version	Author	Date
cee6b3d	emmapfort	2025-04-18
84d5599	emmapfort	2025-04-14

toptable_Dupcor_DOX144_d$logFC %>% hist(, main = "RUVs k=1 DOX 144Rec Toptable")

Past versions of "RUVs k1 DOX only set-5.png"

Version	Author	Date
cee6b3d	emmapfort	2025-04-18
84d5599	emmapfort	2025-04-14

#function is on the previous
annot_data_d <- annot_d %>% dplyr::select("Tx_Time", "Time", "Tx", "Ind", "samples")

Cormotif_d <- counts_DE_df_dox %>% cpm(., log = TRUE)
Cormotif_df_d <- as.data.frame(Cormotif_d)

groupid_d <- rep(c(1, 2, 3, 4, 5, 6), 7)

compid_d <- data.frame(c1 = c(1, 3, 5), c2 = c(2, 4, 6))

#set.seed(12345)
# initial_cormotif_dox <- cormotiffit(exprs = Cormotif_d,
#                                  groupid = groupid_d,
#                                  compid = compid_d,
#                                  K=1:8  , max.iter = 500, runtype = "logCPM")

#only need to run this once! 
#save this to an object so I can retrieve it as needed

#saveRDS(initial_cormotif_dox, "data/initial_cormotif_dox.RDS")

initial_cormotif_dox <- readRDS("data/initial_cormotif_dox.RDS")

plotIC(initial_cormotif_dox)

Past versions of "Plot AIC and BIC-1.png"

Version	Author	Date
cee6b3d	emmapfort	2025-04-18
84d5599	emmapfort	2025-04-14

plotMotif(initial_cormotif_dox)

Past versions of "Plot Motifs DOX Only-1.png"

Version	Author	Date
cee6b3d	emmapfort	2025-04-18
84d5599	emmapfort	2025-04-14

myColors <-  rev(c("#FFFFFF", "#E6E6E6" ,"#CCCCCC", "#B3B3B3", "#999999", "#808080", "#666666","#4C4C4C", "#333333", "#191919","#000000"))

plot.new()
legend('bottomleft',fill=myColors, legend =rev(c("0", "0.1", "0.2", "0.3", "0.4",  "0.5", "0.6", "0.7", "0.8","0.9", "1")), box.col="white",title = "Probability\nlegend", horiz=FALSE,title.cex=.8)

Past versions of "Plot Motifs DOX Only-2.png"

Version	Author	Date
cee6b3d	emmapfort	2025-04-18
84d5599	emmapfort	2025-04-14

topgenelist_d <- generank(initial_cormotif_dox$bestmotif$p.post)
rownames(topgenelist_d) <- rownames(Cormotif_df_d)


motif_prob_d <- initial_cormotif_dox$bestmotif$clustlike
rownames(motif_prob_d) <- rownames(topgenelist_d)
#saveRDS(motif_prob_d, "data/Cormotif_prob_gene_list_doxonly.RDS")


#Define the gene probability groups - I have 4
clust1_d <- motif_prob_d %>% 
  as.data.frame() %>% 
  filter(V1>0.5) %>% 
  rownames

#using a filter of >0.57 I get 11130 genes compared to 11156 above

length(clust1_d)

[1] 11482

#11482 > 0.5
#11130 > 0.57
#is this clust1 a non-response?

clust1_d_df <- as.data.frame(clust1_d)

#example gene - UID 4681 - NBL1
NBL1_motif1 <- Cormotif_df_d %>% 
  rownames_to_column(var = "entrezgene_id") %>% 
  dplyr::filter(entrezgene_id == "4681")

NBL1_motif1_long <- melt(NBL1_motif1,
                         id.vars = c("entrezgene_id"),
                         variable.name = "Sample",
                         value.name = "log2cpm")

#now add in my factors like time, tx, tx_time, and ind by breaking up the Sample column
NBL1_motif1_long_df <- data.frame(tx = factor(tx_names2, levels = unique(tx_names2)),
                                  ind = factor(ind_names, levels = unique(ind_names)),
                                  txtime = factor(txtime_names2, levels = unique(txtime_names2)),
                                  time = factor(time_names2, levels = unique(time_names2)))

NBL1_motif1_long_factors <- cbind(NBL1_motif1_long_df, NBL1_motif1_long)

NBL1_motif1_long_factors %>% ggplot(aes(x = txtime, y = log2cpm))+
  geom_boxplot(aes(fill = tx))+
  geom_point(aes(color = ind)) +
  labs(title = "NBL1")+
  theme_bw(base_size = 16)+
  scale_fill_manual(values = c(tx_col))+
  scale_color_manual(values = c(ind_col))+
  xlab("Conditions")+
  ylab("log2cpm")+
  ylim(0,10)+
  theme(plot.title = element_text(face = "italic"))

Past versions of "Cormotif Cluster Probabilities-1.png"

Version	Author	Date
ff644ec	emmapfort	2025-04-18
cee6b3d	emmapfort	2025-04-18
84d5599	emmapfort	2025-04-14

#saveRDS(CDKN1A_geneplot_Dox, "data/CDKN1A_geneplot_Dox.RDS")

clust2_d <- motif_prob_d %>% 
  as.data.frame() %>% 
  filter(V2>0.5) %>% 
  rownames

#using a filter of >0.132 I get the closest - 326 original vs 327 genes here

length(clust2_d)

[1] 0

#0 > 0.5
#326 > 0.132
#is clust2 a dox early response?

clust2_d_df <- as.data.frame(clust2_d)

#example gene - 597 - BCL2A1
BCL2A1_motif1 <- Cormotif_df_d %>% 
  rownames_to_column(var = "entrezgene_id") %>% 
  dplyr::filter(entrezgene_id == "597")

BCL2A1_motif1_long <- melt(BCL2A1_motif1,
                         id.vars = c("entrezgene_id"),
                         variable.name = "Sample",
                         value.name = "log2cpm")

#now add in my factors like time, tx, tx_time, and ind by breaking up the Sample column
BCL2A1_motif1_long_df <- data.frame(tx = factor(tx_names2, levels = unique(tx_names2)),
                                  ind = factor(ind_names, levels = unique(ind_names)),
                                  txtime = factor(txtime_names2, levels = unique(txtime_names2)),
                                  time = factor(time_names2, levels = unique(time_names2)))

BCL2A1_motif1_long_factors <- cbind(BCL2A1_motif1_long_df, BCL2A1_motif1_long)

BCL2A1_motif1_long_factors %>% ggplot(aes(x = txtime, y = log2cpm))+
  geom_boxplot(aes(fill = tx))+
  geom_point(aes(color = ind)) +
  labs(title = "BCL2A1")+
  theme_bw(base_size = 16)+
  scale_fill_manual(values = c(tx_col))+
  scale_color_manual(values = c(ind_col))+
  xlab("Conditions")+
  ylab("log2cpm")+
  ylim(0,10)+
  theme(plot.title = element_text(face = "italic"))

Past versions of "Cormotif Cluster Probabilities-2.png"

Version	Author	Date
ff644ec	emmapfort	2025-04-18

clust3_d <- motif_prob_d %>% 
  as.data.frame() %>% 
  filter(V3>0.5) %>% 
  rownames

#using a filter of >0.3 I get 740 genes vs original 739 genes

length(clust3_d)

[1] 538

#538 > 0.5
#740 > 0.3
#is clust 3 a late response?

clust3_d_df <- as.data.frame(clust3_d)

#example gene - 8856 - NR1I2
NR1I2_motif1 <- Cormotif_df_d %>% 
  rownames_to_column(var = "entrezgene_id") %>% 
  dplyr::filter(entrezgene_id == "8856")

NR1I2_motif1_long <- melt(NR1I2_motif1,
                         id.vars = c("entrezgene_id"),
                         variable.name = "Sample",
                         value.name = "log2cpm")

#now add in my factors like time, tx, tx_time, and ind by breaking up the Sample column
NR1I2_motif1_long_df <- data.frame(tx = factor(tx_names2, levels = unique(tx_names2)),
                                  ind = factor(ind_names, levels = unique(ind_names)),
                                  txtime = factor(txtime_names2, levels = unique(txtime_names2)),
                                  time = factor(time_names2, levels = unique(time_names2)))

NR1I2_motif1_long_factors <- cbind(NR1I2_motif1_long_df, NR1I2_motif1_long)

NR1I2_motif1_long_factors %>% ggplot(aes(x = txtime, y = log2cpm))+
  geom_boxplot(aes(fill = tx))+
  geom_point(aes(color = ind)) +
  labs(title = "NR1I2")+
  theme_bw(base_size = 16)+
  scale_fill_manual(values = c(tx_col))+
  scale_color_manual(values = c(ind_col))+
  xlab("Conditions")+
  ylab("log2cpm")+
  ylim(0,10)+
  theme(plot.title = element_text(face = "italic"))

Past versions of "Cormotif Cluster Probabilities-3.png"

Version	Author	Date
ff644ec	emmapfort	2025-04-18

#cluster 4
clust4_d <- motif_prob_d %>% 
  as.data.frame() %>% 
  filter(V4>0.5) %>% 
  rownames

#using >0.4 as my cutoff, I get 1938 genes as compared to original 1948 genes

length(clust4_d)

[1] 1576

#1576 > 0.5
#1938 > 0.4
#is clust4 a DOX late response?

clust4_d_df <- as.data.frame(clust4_d)

#example gene - 6725 - SRMS 
SRMS_motif1 <- Cormotif_df_d %>% 
  rownames_to_column(var = "entrezgene_id") %>% 
  dplyr::filter(entrezgene_id == "6725")

SRMS_motif1_long <- melt(SRMS_motif1,
                         id.vars = c("entrezgene_id"),
                         variable.name = "Sample",
                         value.name = "log2cpm")

#now add in my factors like time, tx, tx_time, and ind by breaking up the Sample column
SRMS_motif1_long_df <- data.frame(tx = factor(tx_names2, levels = unique(tx_names2)),
                                  ind = factor(ind_names, levels = unique(ind_names)),
                                  txtime = factor(txtime_names2, levels = unique(txtime_names2)),
                                  time = factor(time_names2, levels = unique(time_names2)))

SRMS_motif1_long_factors <- cbind(SRMS_motif1_long_df, SRMS_motif1_long)

SRMS_motif1_long_factors %>% ggplot(aes(x = txtime, y = log2cpm))+
  geom_boxplot(aes(fill = tx))+
  geom_point(aes(color = ind)) +
  labs(title = "SRMS")+
  theme_bw(base_size = 16)+
  scale_fill_manual(values = c(tx_col))+
  scale_color_manual(values = c(ind_col))+
  xlab("Conditions")+
  ylab("log2cpm")+
  ylim(0,10)+
  theme(plot.title = element_text(face = "italic"))

Past versions of "Cormotif Cluster Probabilities-4.png"

Version	Author	Date
ff644ec	emmapfort	2025-04-18

#now let's make a pie chart with the above number of genes for each motif
clusterdata_d_adj <- data.frame(
  Category = c("No Response","Acute Response", "Late Response", "Early Sustained Response"), 
  Value = c(11130, 327, 740, 1938)
)

piecolors <- c("No Response" = "#007896", 
               "Acute Response" = "#079255",
               "Late Response" = "#58508D", 
               "Early Sustained Response" = "#BC5090")

#make a piechart of these distributions
clusterdata_d_adj %>% ggplot(aes(x = "", y = Value, fill = Category))+
  geom_bar(width = 1, stat = "identity")+
  coord_polar("y", start = 0)+
  geom_text(aes(label = Value),
            position = position_stack(vjust = 0.5),
            size = 4, color = "black")+
  labs(title = "Distribution of Gene Clusters Identified By Cormotif", x = NULL, y = NULL)+
  theme_void()+
  scale_fill_manual(values = piecolors)

Past versions of "Cormotif Cluster Probabilities-5.png"

Version	Author	Date
ff644ec	emmapfort	2025-04-18

#now let's look at each of these motifs by study with the posterior probability
#changing the cutoffs based on the look of each motif - if it's very dark = > 0.5
#if white < 0.5 
#if grey try a less stringent cutoff > 0.1
#ideally each of these are similar to the number of genes in the above plot

#gene_postprob_motif <- initial_cormotif_dox$bestmotif$p.post
#rownames(gene_postprob_motif) <- rownames(Cormotif_df_d)

#saveRDS(gene_postprob_motif, "data/gene_postprob_motif.RDS")


gene_postprob_motif <- readRDS("data/gene_postprob_motif.RDS")

gene_postprob_motif_df <- as.data.frame(gene_postprob_motif)


#motif 1 no response p.prob
prob_motif_1 <- rownames(gene_postprob_motif_df[(gene_postprob_motif_df[,1] < 0.62 
                                              & gene_postprob_motif_df[,2] < 0.62 
                                              & gene_postprob_motif_df[,3] < 0.62),])
length(prob_motif_1)

[1] 11157

#10903 genes post prob

#gene example:  943 - TNFRSF8
TNFRF8_gene <- 

#10903 genes post prob - close to value of 11156 on cormotif pattern graph

#gene example:  11009 - IL24
IL24_gene_motif1 <- 


#motif 2 acute response
prob_motif_2 <- rownames(gene_postprob_motif_df[(gene_postprob_motif_df[,1] > 0.99 
                                              & gene_postprob_motif_df[,2] < 0.5 
                                              & gene_postprob_motif_df[,3] < 0.5),])
length(prob_motif_2)

[1] 277

#2586 genes post prob

#motif 3 late response
prob_motif_3 <- rownames(gene_postprob_motif_df[(gene_postprob_motif_df[,1] > 0.1 
                                              & gene_postprob_motif_df[,2] > 0.5 
                                              & gene_postprob_motif_df[,3] > 0.5),])
length(prob_motif_3)

[1] 451

#451 genes post prob

#motif 4 early sustained response
prob_motif_4 <- rownames(gene_postprob_motif_df[(gene_postprob_motif_df[,1] > 0.5 
                                              & gene_postprob_motif_df[,2] > 0.1 
                                              & gene_postprob_motif_df[,3] < 0.5),])
length(prob_motif_4)

[1] 2600

#2600 genes post prob

#this totals 16540

#Extract the gene IDs from each motif

##motif 1
motif1_genes <- clust1_d_df

##motif 2 
motif2_genes <- clust2_d_df

##motif 3
motif3_genes <- clust3_d_df

##motif 4
motif4_genes <- clust4_d_df

#Combine the toptables I have from pairwise analysis into a single dataframe
d24_toptable <- top.table_V.D24_dox %>% 
  rownames_to_column(var = "entrezgene_ID") %>% 
  mutate(Drug = "DOX", Time = "24")

d24r_toptable <- top.table_V.D24r_dox %>% 
  rownames_to_column(var = "entrezgene_ID") %>% 
  mutate(Drug = "DOX", Time = "24R")

d144r_toptable <- top.table_V.D144r_dox %>% 
  rownames_to_column(var = "entrezgene_ID") %>% 
  mutate(Drug = "DOX", Time = "144R")

combined_toptables_dox <- bind_rows(
  d24_toptable,
  d24r_toptable,
  d144r_toptable)

#Filter the data based on each motif
filt_toptable <- combined_toptables_dox %>% 
  dplyr::filter(entrezgene_ID  %in% clust1_d) %>% 
  mutate(absFC = abs(logFC)) %>% 
  mutate(time = factor(Time, levels = c("24", "24R", "144R"), labels = c("24hr", "24hr Recovery", "144hr Recovery"))) %>% 
  ggplot(., aes(x = time, y = logFC))+
  geom_boxplot(aes(fill = time))+
  scale_fill_manual(values = time_col)+
  guides(fill = guide_legend(title = "Time"))+
  facet_wrap(~Drug)+
  theme_bw()+
  xlab(" ")+
  ylab("logFC")+
  theme_bw()+
  ggtitle("LogFC for all genes in Motif 1")+
  theme(plot.title = element_text(size = rel(1.5), hjust = 0.5),
        axis.title = element_text(size = 15, colour = "black"),
        strip.background = element_rect(fill = "#CAD899"),
        axis.text.x = element_text(size = 8, colour = "white", angle = 15),
        strip.text.x = element_text(size = 12, colour = "black", face = "bold"))

#motif 2
filt_toptable_2 <- combined_toptables_dox %>% 
  dplyr::filter(entrezgene_ID  %in% clust2_d) %>% 
  mutate(absFC = abs(logFC)) %>% 
  mutate(time = factor(Time, levels = c("24", "24R", "144R"), labels = c("24hr", "24hr Recovery", "144hr Recovery"))) %>% 
  ggplot(., aes(x = time, y = logFC))+
  geom_boxplot(aes(fill = time))+
  scale_fill_manual(values = time_col)+
  guides(fill = guide_legend(title = "Time"))+
  facet_wrap(~Drug)+
  theme_bw()+
  xlab(" ")+
  ylab("logFC")+
  theme_bw()+
  ggtitle("LogFC for all genes in Motif 2")+
  theme(plot.title = element_text(size = rel(1.5), hjust = 0.5),
        axis.title = element_text(size = 15, colour = "black"),
        strip.background = element_rect(fill = "#CAD899"),
        axis.text.x = element_text(size = 8, colour = "white", angle = 15),
        strip.text.x = element_text(size = 12, colour = "black", face = "bold"))


#motif 3
filt_toptable_3 <- combined_toptables_dox %>% 
  dplyr::filter(entrezgene_ID  %in% clust3_d) %>% 
  mutate(absFC = abs(logFC)) %>% 
  mutate(time = factor(Time, levels = c("24", "24R", "144R"), labels = c("24hr", "24hr Recovery", "144hr Recovery"))) %>% 
  ggplot(., aes(x = time, y = logFC))+
  geom_boxplot(aes(fill = time))+
  scale_fill_manual(values = time_col)+
  guides(fill = guide_legend(title = "Time"))+
  facet_wrap(~Drug)+
  theme_bw()+
  xlab(" ")+
  ylab("logFC")+
  theme_bw()+
  ggtitle("LogFC for all genes in Motif 3")+
  theme(plot.title = element_text(size = rel(1.5), hjust = 0.5),
        axis.title = element_text(size = 15, colour = "black"),
        strip.background = element_rect(fill = "#CAD899"),
        axis.text.x = element_text(size = 8, colour = "white", angle = 15),
        strip.text.x = element_text(size = 12, colour = "black", face = "bold"))


#motif 4
filt_toptable_4 <- combined_toptables_dox %>% 
  dplyr::filter(entrezgene_ID  %in% clust4_d) %>% 
  mutate(absFC = abs(logFC)) %>% 
  mutate(time = factor(Time, levels = c("24", "24R", "144R"), labels = c("24hr", "24hr Recovery", "144hr Recovery"))) %>% 
  ggplot(., aes(x = time, y = logFC))+
  geom_boxplot(aes(fill = time))+
  scale_fill_manual(values = time_col)+
  guides(fill = guide_legend(title = "Time"))+
  facet_wrap(~Drug)+
  theme_bw()+
  xlab(" ")+
  ylab("logFC")+
  theme_bw()+
  ggtitle("LogFC for all genes in Motif 4")+
  theme(plot.title = element_text(size = rel(1.5), hjust = 0.5),
        axis.title = element_text(size = 15, colour = "black"),
        strip.background = element_rect(fill = "#CAD899"),
        axis.text.x = element_text(size = 8, colour = "white", angle = 15),
        strip.text.x = element_text(size = 12, colour = "black", face = "bold"))

#plots
filt_toptable

#filt_toptable_2
filt_toptable_3

filt_toptable_4

#now plot the abs logFC for each of these too
filt_toptable_abs <- combined_toptables_dox %>% 
  dplyr::filter(entrezgene_ID  %in% clust1_d) %>% 
  mutate(absFC = abs(logFC)) %>% 
  mutate(time = factor(Time, levels = c("24", "24R", "144R"), labels = c("24hr", "24hr Recovery", "144hr Recovery"))) %>% 
  ggplot(., aes(x = time, y = absFC))+
  geom_boxplot(aes(fill = time))+
  scale_fill_manual(values = time_col)+
  guides(fill = guide_legend(title = "Time"))+
  facet_wrap(~Drug)+
  theme_bw()+
  xlab(" ")+
  ylab("|logFC|")+
  theme_bw()+
  ggtitle("Abs LogFC for all genes in Motif 1")+
  theme(plot.title = element_text(size = rel(1.5), hjust = 0.5),
        axis.title = element_text(size = 15, colour = "black"),
        strip.background = element_rect(fill = "#CAD899"),
        axis.text.x = element_text(size = 8, colour = "white", angle = 15),
        strip.text.x = element_text(size = 12, colour = "black", face = "bold"))

#motif 2
filt_toptable_2_abs <- combined_toptables_dox %>% 
  dplyr::filter(entrezgene_ID  %in% clust2_d) %>% 
  mutate(absFC = abs(logFC)) %>% 
  mutate(time = factor(Time, levels = c("24", "24R", "144R"), labels = c("24hr", "24hr Recovery", "144hr Recovery"))) %>% 
  ggplot(., aes(x = time, y = absFC))+
  geom_boxplot(aes(fill = time))+
  scale_fill_manual(values = time_col)+
  guides(fill = guide_legend(title = "Time"))+
  facet_wrap(~Drug)+
  theme_bw()+
  xlab(" ")+
  ylab("|logFC|")+
  theme_bw()+
  ggtitle("Abs LogFC for all genes in Motif 2")+
  theme(plot.title = element_text(size = rel(1.5), hjust = 0.5),
        axis.title = element_text(size = 15, colour = "black"),
        strip.background = element_rect(fill = "#CAD899"),
        axis.text.x = element_text(size = 8, colour = "white", angle = 15),
        strip.text.x = element_text(size = 12, colour = "black", face = "bold"))


#motif 3
filt_toptable_3_abs <- combined_toptables_dox %>% 
  dplyr::filter(entrezgene_ID  %in% clust3_d) %>% 
  mutate(absFC = abs(logFC)) %>% 
  mutate(time = factor(Time, levels = c("24", "24R", "144R"), labels = c("24hr", "24hr Recovery", "144hr Recovery"))) %>% 
  ggplot(., aes(x = time, y = absFC))+
  geom_boxplot(aes(fill = time))+
  scale_fill_manual(values = time_col)+
  guides(fill = guide_legend(title = "Time"))+
  facet_wrap(~Drug)+
  theme_bw()+
  xlab(" ")+
  ylab("|logFC|")+
  theme_bw()+
  ggtitle("Abs LogFC for all genes in Motif 3")+
  theme(plot.title = element_text(size = rel(1.5), hjust = 0.5),
        axis.title = element_text(size = 15, colour = "black"),
        strip.background = element_rect(fill = "#CAD899"),
        axis.text.x = element_text(size = 8, colour = "white", angle = 15),
        strip.text.x = element_text(size = 12, colour = "black", face = "bold"))


#motif 4
filt_toptable_4_abs <- combined_toptables_dox %>% 
  dplyr::filter(entrezgene_ID  %in% clust4_d) %>% 
  mutate(absFC = abs(logFC)) %>% 
  mutate(time = factor(Time, levels = c("24", "24R", "144R"), labels = c("24hr", "24hr Recovery", "144hr Recovery"))) %>% 
  ggplot(., aes(x = time, y = absFC))+
  geom_boxplot(aes(fill = time))+
  scale_fill_manual(values = time_col)+
  guides(fill = guide_legend(title = "Time"))+
  facet_wrap(~Drug)+
  theme_bw()+
  xlab(" ")+
  ylab("|logFC|")+
  theme_bw()+
  ggtitle("Abs LogFC for all genes in Motif 4")+
  theme(plot.title = element_text(size = rel(1.5), hjust = 0.5),
        axis.title = element_text(size = 15, colour = "black"),
        strip.background = element_rect(fill = "#CAD899"),
        axis.text.x = element_text(size = 8, colour = "white", angle = 15),
        strip.text.x = element_text(size = 12, colour = "black", face = "bold"))


#plots
filt_toptable_abs

#filt_toptable_2_abs
filt_toptable_3_abs

filt_toptable_4_abs

clusterdata_postprob <- data.frame(
  Category = c("No Response", "Acute Response", "Late Response", "Early Sustained Response"), 
  Value = c(10903, 2586, 451, 2600)
)

piecolors_2 <- c("No Response" = "#007896",
               "Acute Response" = "#58508D",
               "Late Response" = "#ABCC59", 
               "Early Sustained Response" = "#BC5090")

#make a piechart of these distributions
clusterdata_postprob %>% ggplot(aes(x = "", y = Value, fill = Category))+
  geom_bar(width = 1, stat = "identity")+
  coord_polar("y", start = 0)+
  geom_text(aes(label = Value),
            position = position_stack(vjust = 0.5),
            size = 4, color = "black")+
  labs(title = "Distribution of Gene Clusters Identified By Cormotif", x = NULL, y = NULL)+
  theme_void()+
  scale_fill_manual(values = piecolors_2)

Past versions of "Assess Gene Distribution Post Prob Cormotif-1.png"

Version	Author	Date
cee6b3d	emmapfort	2025-04-18
84d5599	emmapfort	2025-04-14

Now we will use Gene Ontology analysis to discover biological relevance to the genes that are assigned to this cluster This set is for the No Response motif (motif 1) with clustlike

motif_NR_d <- clust1_d

NRmotif_genes_d <- gost(query = motif_NR_d,
                      organism = "hsapiens",
                      ordered_query = FALSE,
                      measure_underrepresentation = FALSE,
                      evcodes = FALSE,
                      user_threshold = 0.05,
                      correction_method = c("fdr"),
                      sources = c("GO:BP", "KEGG"))

cormotifNFclust_d <- gostplot(NRmotif_genes_d, capped = FALSE, interactive = TRUE)
cormotifNFclust_d

tableNR_d <- NRmotif_genes_d$result %>% 
  dplyr::select(c(source, term_id, term_name, intersection_size, term_size, p_value))

tableNR_d %>% 
  mutate_at(.vars = 6, .funs = scales::label_scientific(digits=4)) %>% 
  kableExtra::kable(.,) %>% 
  kableExtra::kable_paper("striped", full_width = FALSE) %>% 
  kableExtra::kable_styling(full_width = FALSE, position = "left", bootstrap_options = c("striped", "hover")) %>% 
  kableExtra::scroll_box(width = "100%", height = "400px")

source	term_id	term_name	intersection_size	term_size	p_value
GO:BP	GO:0050907	detection of chemical stimulus involved in sensory perception	394	443	2.099e-211
GO:BP	GO:0035195	miRNA-mediated post-transcriptional gene silencing	477	612	4.095e-206
GO:BP	GO:0007606	sensory perception of chemical stimulus	418	497	2.501e-204
GO:BP	GO:0050911	detection of chemical stimulus involved in sensory perception of smell	362	397	2.924e-203
GO:BP	GO:0035194	regulatory ncRNA-mediated post-transcriptional gene silencing	478	624	4.629e-201
GO:BP	GO:0016441	post-transcriptional gene silencing	479	630	4.448e-199
GO:BP	GO:0009593	detection of chemical stimulus	404	480	7.960e-198
GO:BP	GO:0050906	detection of stimulus involved in sensory perception	419	515	5.041e-194
GO:BP	GO:0007608	sensory perception of smell	369	423	1.005e-191
GO:BP	GO:0031047	regulatory ncRNA-mediated gene silencing	485	686	1.000e-178
GO:BP	GO:0051606	detection of stimulus	460	643	1.638e-172
GO:BP	GO:0007186	G protein-coupled receptor signaling pathway	702	1275	1.993e-169
GO:BP	GO:0007600	sensory perception	561	955	1.695e-150
GO:BP	GO:0050877	nervous system process	654	1489	1.255e-95
GO:BP	GO:0010608	post-transcriptional regulation of gene expression	516	1087	6.436e-89
GO:BP	GO:0003008	system process	814	2266	2.014e-68
GO:BP	GO:0010629	negative regulation of gene expression	637	1640	1.677e-66
GO:BP	GO:0042221	response to chemical	1122	3867	5.099e-40
GO:BP	GO:0065007	biological regulation	2992	12671	6.636e-36
GO:BP	GO:0042742	defense response to bacterium	170	326	6.062e-34
GO:BP	GO:0006959	humoral immune response	142	254	1.701e-32
GO:BP	GO:0050789	regulation of biological process	2896	12278	1.784e-32
GO:BP	GO:0006952	defense response	588	1809	2.171e-32
GO:BP	GO:0032501	multicellular organismal process	1842	7234	8.240e-32
GO:BP	GO:0050794	regulation of cellular process	2800	11876	1.068e-29
GO:BP	GO:0009617	response to bacterium	284	721	5.585e-29
GO:BP	GO:0010558	negative regulation of macromolecule biosynthetic process	808	2772	1.486e-27
GO:BP	GO:0098542	defense response to other organism	418	1228	8.345e-27
GO:BP	GO:0009890	negative regulation of biosynthetic process	816	2838	8.551e-26
GO:BP	GO:0031424	keratinization	62	82	5.996e-24
GO:BP	GO:0019730	antimicrobial humoral response	83	131	9.733e-24
GO:BP	GO:0043207	response to external biotic stimulus	491	1558	3.572e-23
GO:BP	GO:0051707	response to other organism	489	1555	7.492e-23
GO:BP	GO:0009607	response to biotic stimulus	498	1593	1.062e-22
GO:BP	GO:0140546	defense response to symbiont	376	1125	2.767e-22
GO:BP	GO:0009605	response to external stimulus	672	2367	4.718e-19
GO:BP	GO:0007165	signal transduction	1490	5979	9.766e-19
GO:BP	GO:0001906	cell killing	107	219	2.841e-18
GO:BP	GO:0141060	disruption of anatomical structure in another organism	62	98	1.639e-17
GO:BP	GO:0006954	inflammatory response	286	847	2.720e-17
GO:BP	GO:0061844	antimicrobial humoral immune response mediated by antimicrobial peptide	55	83	7.921e-17
GO:BP	GO:0044419	biological process involved in interspecies interaction between organisms	506	1724	8.800e-17
GO:BP	GO:0006955	immune response	574	2008	1.288e-16
GO:BP	GO:0031640	killing of cells of another organism	58	91	1.309e-16
GO:BP	GO:0141061	disruption of cell in another organism	58	91	1.309e-16
GO:BP	GO:0010605	negative regulation of macromolecule metabolic process	852	3197	1.946e-16
GO:BP	GO:0045087	innate immune response	317	977	1.946e-16
GO:BP	GO:0007154	cell communication	1578	6496	2.330e-15
GO:BP	GO:0023052	signaling	1571	6471	3.737e-15
GO:BP	GO:0045109	intermediate filament organization	48	73	1.917e-14
GO:BP	GO:0050830	defense response to Gram-positive bacterium	66	120	2.533e-14
GO:BP	GO:0009892	negative regulation of metabolic process	887	3418	6.520e-14
GO:BP	GO:0002252	immune effector process	236	703	7.908e-14
GO:BP	GO:0050896	response to stimulus	2093	8993	2.383e-13
GO:BP	GO:0050909	sensory perception of taste	44	67	3.535e-13
GO:BP	GO:0030216	keratinocyte differentiation	83	176	5.400e-13
GO:BP	GO:0097530	granulocyte migration	76	156	8.440e-13
GO:BP	GO:0050829	defense response to Gram-negative bacterium	53	91	8.440e-13
GO:BP	GO:0002697	regulation of immune effector process	144	381	1.380e-12
GO:BP	GO:1990266	neutrophil migration	66	129	2.468e-12
GO:BP	GO:0030593	neutrophil chemotaxis	57	106	9.133e-12
GO:BP	GO:0007586	digestion	67	136	1.612e-11
GO:BP	GO:0050913	sensory perception of bitter taste	31	42	3.164e-11
GO:BP	GO:0071621	granulocyte chemotaxis	64	129	3.650e-11
GO:BP	GO:0050912	detection of chemical stimulus involved in sensory perception of taste	31	43	8.803e-11
GO:BP	GO:0009913	epidermal cell differentiation	101	250	1.169e-10
GO:BP	GO:0002237	response to molecule of bacterial origin	131	355	1.496e-10
GO:BP	GO:0001580	detection of chemical stimulus involved in sensory perception of bitter taste	28	37	1.530e-10
GO:BP	GO:0002323	natural killer cell activation involved in immune response	27	35	1.731e-10
GO:BP	GO:0030595	leukocyte chemotaxis	96	237	3.354e-10
GO:BP	GO:0002376	immune system process	720	2796	3.674e-10
GO:BP	GO:0050900	leukocyte migration	140	396	9.295e-10
GO:BP	GO:0019731	antibacterial humoral response	40	68	9.295e-10
GO:BP	GO:0032496	response to lipopolysaccharide	123	337	1.549e-09
GO:BP	GO:0045104	intermediate filament cytoskeleton organization	49	94	1.915e-09
GO:BP	GO:0097529	myeloid leukocyte migration	94	237	2.134e-09
GO:BP	GO:0071219	cellular response to molecule of bacterial origin	90	224	2.467e-09
GO:BP	GO:0051716	cellular response to stimulus	1702	7320	2.514e-09
GO:BP	GO:0046651	lymphocyte proliferation	114	308	2.958e-09
GO:BP	GO:0045103	intermediate filament-based process	49	95	2.964e-09
GO:BP	GO:0070098	chemokine-mediated signaling pathway	47	90	4.220e-09
GO:BP	GO:0007283	spermatogenesis	201	637	5.143e-09
GO:BP	GO:0019221	cytokine-mediated signaling pathway	166	503	5.685e-09
GO:BP	GO:0070661	leukocyte proliferation	125	351	6.046e-09
GO:BP	GO:0032943	mononuclear cell proliferation	115	315	6.046e-09
GO:BP	GO:0071222	cellular response to lipopolysaccharide	86	214	6.046e-09
GO:BP	GO:0002526	acute inflammatory response	53	109	7.814e-09
GO:BP	GO:0048232	male gamete generation	204	654	1.064e-08
GO:BP	GO:0007218	neuropeptide signaling pathway	53	110	1.179e-08
GO:BP	GO:0002682	regulation of immune system process	416	1526	1.256e-08
GO:BP	GO:0008544	epidermis development	135	394	2.033e-08
GO:BP	GO:0007338	single fertilization	71	169	2.540e-08
GO:BP	GO:0042100	B cell proliferation	51	106	2.685e-08
GO:BP	GO:0060326	cell chemotaxis	114	319	2.989e-08
GO:BP	GO:0052695	cellular glucuronidation	18	21	3.186e-08
GO:BP	GO:0033141	positive regulation of peptidyl-serine phosphorylation of STAT protein	18	21	3.186e-08
GO:BP	GO:0002699	positive regulation of immune effector process	95	253	4.432e-08
GO:BP	GO:0070663	regulation of leukocyte proliferation	98	265	6.144e-08
GO:BP	GO:0002684	positive regulation of immune system process	302	1066	7.008e-08
GO:BP	GO:0045321	leukocyte activation	274	951	7.263e-08
GO:BP	GO:0002548	monocyte chemotaxis	37	68	8.828e-08
GO:BP	GO:0001775	cell activation	309	1098	9.336e-08
GO:BP	GO:0002703	regulation of leukocyte mediated immunity	91	243	1.128e-07
GO:BP	GO:0022414	reproductive process	417	1556	1.138e-07
GO:BP	GO:0009566	fertilization	82	212	1.224e-07
GO:BP	GO:0002922	positive regulation of humoral immune response	18	22	1.277e-07
GO:BP	GO:0002366	leukocyte activation involved in immune response	108	305	1.387e-07
GO:BP	GO:0002263	cell activation involved in immune response	109	309	1.481e-07
GO:BP	GO:0048609	multicellular organismal reproductive process	279	980	1.719e-07
GO:BP	GO:1990868	response to chemokine	47	99	1.942e-07
GO:BP	GO:1990869	cellular response to chemokine	47	99	1.942e-07
GO:BP	GO:0072677	eosinophil migration	22	31	2.001e-07
GO:BP	GO:0050776	regulation of immune response	258	897	2.436e-07
GO:BP	GO:0050832	defense response to fungus	33	59	2.445e-07
GO:BP	GO:0071216	cellular response to biotic stimulus	92	251	2.903e-07
GO:BP	GO:0048245	eosinophil chemotaxis	20	27	3.121e-07
GO:BP	GO:0071715	icosanoid transport	35	65	3.122e-07
GO:BP	GO:0050727	regulation of inflammatory response	127	381	3.701e-07
GO:BP	GO:0032649	regulation of type II interferon production	52	117	4.698e-07
GO:BP	GO:0050670	regulation of lymphocyte proliferation	87	236	5.335e-07
GO:BP	GO:0022600	digestive system process	48	105	5.726e-07
GO:BP	GO:0032944	regulation of mononuclear cell proliferation	88	240	5.813e-07
GO:BP	GO:0060294	cilium movement involved in cell motility	67	167	5.832e-07
GO:BP	GO:0030317	flagellated sperm motility	61	147	5.861e-07
GO:BP	GO:0097722	sperm motility	61	147	5.861e-07
GO:BP	GO:0032609	type II interferon production	52	118	6.345e-07
GO:BP	GO:0031341	regulation of cell killing	48	106	7.977e-07
GO:BP	GO:0002706	regulation of lymphocyte mediated immunity	71	182	8.191e-07
GO:BP	GO:0002443	leukocyte mediated immunity	146	461	1.138e-06
GO:BP	GO:0033139	regulation of peptidyl-serine phosphorylation of STAT protein	18	24	1.242e-06
GO:BP	GO:0006953	acute-phase response	28	49	1.763e-06
GO:BP	GO:0048247	lymphocyte chemotaxis	33	63	1.893e-06
GO:BP	GO:0001539	cilium or flagellum-dependent cell motility	67	172	2.139e-06
GO:BP	GO:0060285	cilium-dependent cell motility	67	172	2.139e-06
GO:BP	GO:0001909	leukocyte mediated cytotoxicity	56	135	2.223e-06
GO:BP	GO:0002274	myeloid leukocyte activation	86	240	2.612e-06
GO:BP	GO:0007188	adenylate cyclase-modulating G protein-coupled receptor signaling pathway	88	248	3.047e-06
GO:BP	GO:0032689	negative regulation of type II interferon production	25	42	3.066e-06
GO:BP	GO:0042501	serine phosphorylation of STAT protein	18	25	3.341e-06
GO:BP	GO:0022412	cellular process involved in reproduction in multicellular organism	130	408	4.288e-06
GO:BP	GO:0007276	gamete generation	233	822	4.345e-06
GO:BP	GO:0050778	positive regulation of immune response	211	732	4.554e-06
GO:BP	GO:0019953	sexual reproduction	300	1103	4.591e-06
GO:BP	GO:0048240	sperm capacitation	21	33	6.936e-06
GO:BP	GO:0001819	positive regulation of cytokine production	149	486	7.167e-06
GO:BP	GO:0006063	uronic acid metabolic process	18	26	8.268e-06
GO:BP	GO:0019585	glucuronate metabolic process	18	26	8.268e-06
GO:BP	GO:0140975	disruption of cellular anatomical structure in another organism	10	10	8.941e-06
GO:BP	GO:0002775	antimicrobial peptide production	10	10	8.941e-06
GO:BP	GO:0007259	cell surface receptor signaling pathway via JAK-STAT	64	168	1.011e-05
GO:BP	GO:0043588	skin development	106	322	1.071e-05
GO:BP	GO:0001817	regulation of cytokine production	217	765	1.076e-05
GO:BP	GO:0009620	response to fungus	34	70	1.121e-05
GO:BP	GO:0050953	sensory perception of light stimulus	79	222	1.129e-05
GO:BP	GO:0030101	natural killer cell activation	42	95	1.209e-05
GO:BP	GO:0097696	cell surface receptor signaling pathway via STAT	66	176	1.246e-05
GO:BP	GO:0007601	visual perception	78	219	1.267e-05
GO:BP	GO:0051873	killing by host of symbiont cells	19	29	1.312e-05
GO:BP	GO:0042129	regulation of T cell proliferation	67	180	1.371e-05
GO:BP	GO:0001816	cytokine production	218	772	1.391e-05
GO:BP	GO:0006690	icosanoid metabolic process	50	122	1.557e-05
GO:BP	GO:0002920	regulation of humoral immune response	25	45	1.684e-05
GO:BP	GO:0007631	feeding behavior	45	106	1.805e-05
GO:BP	GO:0007286	spermatid development	76	214	1.968e-05
GO:BP	GO:0042531	positive regulation of tyrosine phosphorylation of STAT protein	31	63	2.471e-05
GO:BP	GO:0019755	one-carbon compound transport	17	25	2.471e-05
GO:BP	GO:0002251	organ or tissue specific immune response	24	43	2.511e-05
GO:BP	GO:0042330	taxis	141	465	2.686e-05
GO:BP	GO:0072676	lymphocyte migration	50	124	2.686e-05
GO:BP	GO:0007342	fusion of sperm to egg plasma membrane involved in single fertilization	19	30	2.686e-05
GO:BP	GO:0001910	regulation of leukocyte mediated cytotoxicity	40	92	3.619e-05
GO:BP	GO:0010468	regulation of gene expression	1268	5515	3.899e-05
GO:BP	GO:0002285	lymphocyte activation involved in immune response	75	214	4.009e-05
GO:BP	GO:0048515	spermatid differentiation	77	222	4.556e-05
GO:BP	GO:0036230	granulocyte activation	26	50	5.085e-05
GO:BP	GO:0050865	regulation of cell activation	177	616	5.147e-05
GO:BP	GO:0015718	monocarboxylic acid transport	65	179	5.147e-05
GO:BP	GO:0002385	mucosal immune response	22	39	5.559e-05
GO:BP	GO:0006935	chemotaxis	139	463	5.666e-05
GO:BP	GO:0007204	positive regulation of cytosolic calcium ion concentration	62	169	5.956e-05
GO:BP	GO:0042119	neutrophil activation	23	42	6.327e-05
GO:BP	GO:0015670	carbon dioxide transport	12	15	7.547e-05
GO:BP	GO:0070665	positive regulation of leukocyte proliferation	60	163	7.610e-05
GO:BP	GO:0015732	prostaglandin transport	18	29	7.651e-05
GO:BP	GO:0002286	T cell activation involved in immune response	49	125	8.455e-05
GO:BP	GO:0002694	regulation of leukocyte activation	162	561	1.007e-04
GO:BP	GO:0009584	detection of visible light	19	32	1.007e-04
GO:BP	GO:0042102	positive regulation of T cell proliferation	42	102	1.008e-04
GO:BP	GO:0002705	positive regulation of leukocyte mediated immunity	55	147	1.102e-04
GO:BP	GO:0050729	positive regulation of inflammatory response	55	147	1.102e-04
GO:BP	GO:0046649	lymphocyte activation	216	787	1.227e-04
GO:BP	GO:0002698	negative regulation of immune effector process	47	120	1.352e-04
GO:BP	GO:0032612	interleukin-1 production	44	110	1.426e-04
GO:BP	GO:0032652	regulation of interleukin-1 production	44	110	1.426e-04
GO:BP	GO:0042509	regulation of tyrosine phosphorylation of STAT protein	33	74	1.494e-04
GO:BP	GO:0002784	regulation of antimicrobial peptide production	8	8	1.574e-04
GO:BP	GO:0002760	positive regulation of antimicrobial humoral response	8	8	1.574e-04
GO:BP	GO:0002778	antibacterial peptide production	8	8	1.574e-04
GO:BP	GO:0009583	detection of light stimulus	31	68	1.638e-04
GO:BP	GO:0051249	regulation of lymphocyte activation	145	497	1.739e-04
GO:BP	GO:0002673	regulation of acute inflammatory response	24	47	1.755e-04
GO:BP	GO:0032653	regulation of interleukin-10 production	28	59	1.790e-04
GO:BP	GO:0032613	interleukin-10 production	28	59	1.790e-04
GO:BP	GO:0015908	fatty acid transport	46	118	1.873e-04
GO:BP	GO:0003006	developmental process involved in reproduction	270	1022	1.873e-04
GO:BP	GO:0098586	cellular response to virus	34	78	1.884e-04
GO:BP	GO:0071346	cellular response to type II interferon	48	125	1.893e-04
GO:BP	GO:0003341	cilium movement	72	212	2.016e-04
GO:BP	GO:0050671	positive regulation of lymphocyte proliferation	53	143	2.099e-04
GO:BP	GO:0071674	mononuclear cell migration	78	235	2.183e-04
GO:BP	GO:0034341	response to type II interferon	54	147	2.310e-04
GO:BP	GO:0030855	epithelial cell differentiation	203	741	2.510e-04
GO:BP	GO:0042110	T cell activation	159	558	2.519e-04
GO:BP	GO:0060295	regulation of cilium movement involved in cell motility	18	31	2.536e-04
GO:BP	GO:1902019	regulation of cilium-dependent cell motility	18	31	2.536e-04
GO:BP	GO:0007159	leukocyte cell-cell adhesion	121	404	2.574e-04
GO:BP	GO:0032309	icosanoid secretion	24	48	2.602e-04
GO:BP	GO:0007602	phototransduction	24	48	2.602e-04
GO:BP	GO:0042363	fat-soluble vitamin catabolic process	10	12	2.649e-04
GO:BP	GO:0007260	tyrosine phosphorylation of STAT protein	33	76	2.691e-04
GO:BP	GO:0051250	negative regulation of lymphocyte activation	57	159	2.915e-04
GO:BP	GO:0045026	plasma membrane fusion	19	34	2.933e-04
GO:BP	GO:0002822	regulation of adaptive immune response based on somatic recombination of immune receptors built from immunoglobulin superfamily domains	65	189	3.360e-04
GO:BP	GO:0002819	regulation of adaptive immune response	69	204	3.426e-04
GO:BP	GO:0031347	regulation of defense response	212	783	3.438e-04
GO:BP	GO:0032946	positive regulation of mononuclear cell proliferation	53	146	3.899e-04
GO:BP	GO:0006805	xenobiotic metabolic process	47	125	4.184e-04
GO:BP	GO:0006691	leukotriene metabolic process	18	32	4.408e-04
GO:BP	GO:0032945	negative regulation of mononuclear cell proliferation	36	88	5.148e-04
GO:BP	GO:1903037	regulation of leukocyte cell-cell adhesion	110	366	5.277e-04
GO:BP	GO:0007281	germ cell development	111	370	5.277e-04
GO:BP	GO:0002709	regulation of T cell mediated immunity	38	95	5.492e-04
GO:BP	GO:0032722	positive regulation of chemokine production	31	72	5.902e-04
GO:BP	GO:0002685	regulation of leukocyte migration	75	230	5.911e-04
GO:BP	GO:0050863	regulation of T cell activation	112	375	5.911e-04
GO:BP	GO:0007200	phospholipase C-activating G protein-coupled receptor signaling pathway	44	116	5.911e-04
GO:BP	GO:1901317	regulation of flagellated sperm motility	14	22	5.951e-04
GO:BP	GO:0010556	regulation of macromolecule biosynthetic process	1276	5633	6.069e-04
GO:BP	GO:0002695	negative regulation of leukocyte activation	63	185	6.100e-04
GO:BP	GO:0002225	positive regulation of antimicrobial peptide production	7	7	6.253e-04
GO:BP	GO:0052697	xenobiotic glucuronidation	7	7	6.253e-04
GO:BP	GO:0002704	negative regulation of leukocyte mediated immunity	29	66	6.637e-04
GO:BP	GO:0032101	regulation of response to external stimulus	277	1071	6.802e-04
GO:BP	GO:0032602	chemokine production	38	96	6.874e-04
GO:BP	GO:0032642	regulation of chemokine production	38	96	6.874e-04
GO:BP	GO:0070664	negative regulation of leukocyte proliferation	38	96	6.874e-04
GO:BP	GO:0032757	positive regulation of interleukin-8 production	28	63	6.970e-04
GO:BP	GO:0009581	detection of external stimulus	51	142	7.251e-04
GO:BP	GO:0002449	lymphocyte mediated immunity	108	361	7.251e-04
GO:BP	GO:0002687	positive regulation of leukocyte migration	54	153	7.362e-04
GO:BP	GO:0042113	B cell activation	88	282	7.362e-04
GO:BP	GO:0032677	regulation of interleukin-8 production	34	83	7.764e-04
GO:BP	GO:0032637	interleukin-8 production	34	83	7.764e-04
GO:BP	GO:0042098	T cell proliferation	70	213	7.789e-04
GO:BP	GO:0002444	myeloid leukocyte mediated immunity	43	114	7.950e-04
GO:BP	GO:0002544	chronic inflammatory response	13	20	8.066e-04
GO:BP	GO:0050868	negative regulation of T cell activation	46	125	8.673e-04
GO:BP	GO:0070374	positive regulation of ERK1 and ERK2 cascade	69	210	8.811e-04
GO:BP	GO:0002759	regulation of antimicrobial humoral response	9	11	9.070e-04
GO:BP	GO:1903038	negative regulation of leukocyte cell-cell adhesion	49	136	9.078e-04
GO:BP	GO:0050672	negative regulation of lymphocyte proliferation	35	87	9.094e-04
GO:BP	GO:0002227	innate immune response in mucosa	16	28	9.123e-04
GO:BP	GO:0032103	positive regulation of response to external stimulus	170	619	9.807e-04
GO:BP	GO:0015669	gas transport	14	23	1.100e-03
GO:BP	GO:0030277	maintenance of gastrointestinal epithelium	14	23	1.100e-03
GO:BP	GO:0032735	positive regulation of interleukin-12 production	21	43	1.271e-03
GO:BP	GO:0071345	cellular response to cytokine stimulus	222	843	1.273e-03
GO:BP	GO:1904892	regulation of receptor signaling pathway via STAT	40	106	1.418e-03
GO:BP	GO:0046425	regulation of receptor signaling pathway via JAK-STAT	38	99	1.418e-03
GO:BP	GO:0060046	regulation of acrosome reaction	11	16	1.565e-03
GO:BP	GO:0001818	negative regulation of cytokine production	88	288	1.624e-03
GO:BP	GO:0002825	regulation of T-helper 1 type immune response	17	32	1.754e-03
GO:BP	GO:0002715	regulation of natural killer cell mediated immunity	23	50	1.781e-03
GO:BP	GO:0002228	natural killer cell mediated immunity	31	76	1.797e-03
GO:BP	GO:0002700	regulation of production of molecular mediator of immune response	62	188	1.837e-03
GO:BP	GO:0007189	adenylate cyclase-activating G protein-coupled receptor signaling pathway	54	158	1.843e-03
GO:BP	GO:0002701	negative regulation of production of molecular mediator of immune response	21	44	1.881e-03
GO:BP	GO:0001523	retinoid metabolic process	33	83	1.899e-03
GO:BP	GO:0031343	positive regulation of cell killing	30	73	1.961e-03
GO:BP	GO:0009889	regulation of biosynthetic process	1302	5795	1.992e-03
GO:BP	GO:0009111	vitamin catabolic process	10	14	2.062e-03
GO:BP	GO:0070942	neutrophil mediated cytotoxicity	10	14	2.062e-03
GO:BP	GO:0042445	hormone metabolic process	76	243	2.132e-03
GO:BP	GO:0048519	negative regulation of biological process	1316	5865	2.239e-03
GO:BP	GO:0042832	defense response to protozoan	15	27	2.350e-03
GO:BP	GO:0000270	peptidoglycan metabolic process	6	6	2.505e-03
GO:BP	GO:0009253	peptidoglycan catabolic process	6	6	2.505e-03
GO:BP	GO:0051552	flavone metabolic process	6	6	2.505e-03
GO:BP	GO:0051673	disruption of plasma membrane integrity in another organism	6	6	2.505e-03
GO:BP	GO:0002786	regulation of antibacterial peptide production	6	6	2.505e-03
GO:BP	GO:0009582	detection of abiotic stimulus	50	145	2.505e-03
GO:BP	GO:0070943	neutrophil-mediated killing of symbiont cell	9	12	2.622e-03
GO:BP	GO:0032680	regulation of tumor necrosis factor production	55	164	2.649e-03
GO:BP	GO:0032640	tumor necrosis factor production	55	164	2.649e-03
GO:BP	GO:0031349	positive regulation of defense response	135	484	2.649e-03
GO:BP	GO:0016101	diterpenoid metabolic process	34	88	2.739e-03
GO:BP	GO:0030431	sleep	13	22	2.927e-03
GO:BP	GO:0120254	olefinic compound metabolic process	54	161	3.006e-03
GO:BP	GO:0002456	T cell mediated immunity	44	124	3.006e-03
GO:BP	GO:0050866	negative regulation of cell activation	66	207	3.129e-03
GO:BP	GO:0002707	negative regulation of lymphocyte mediated immunity	24	55	3.173e-03
GO:BP	GO:0002768	immune response-regulating cell surface receptor signaling pathway	98	334	3.194e-03
GO:BP	GO:0008228	opsonization	11	17	3.205e-03
GO:BP	GO:0071706	tumor necrosis factor superfamily cytokine production	56	169	3.205e-03
GO:BP	GO:1903555	regulation of tumor necrosis factor superfamily cytokine production	56	169	3.205e-03
GO:BP	GO:0006968	cellular defense response	23	52	3.364e-03
GO:BP	GO:0032615	interleukin-12 production	26	62	3.618e-03
GO:BP	GO:0032655	regulation of interleukin-12 production	26	62	3.618e-03
GO:BP	GO:0051607	defense response to virus	92	311	3.618e-03
GO:BP	GO:0002708	positive regulation of lymphocyte mediated immunity	44	125	3.618e-03
GO:BP	GO:0002710	negative regulation of T cell mediated immunity	15	28	3.752e-03
GO:BP	GO:0002275	myeloid cell activation involved in immune response	37	100	3.763e-03
GO:BP	GO:0032611	interleukin-1 beta production	35	93	3.806e-03
GO:BP	GO:0032651	regulation of interleukin-1 beta production	35	93	3.806e-03
GO:BP	GO:0030183	B cell differentiation	53	159	3.943e-03
GO:BP	GO:0071466	cellular response to xenobiotic stimulus	62	194	4.400e-03
GO:BP	GO:0034097	response to cytokine	239	937	4.901e-03
GO:BP	GO:0060259	regulation of feeding behavior	14	26	5.747e-03
GO:BP	GO:0032760	positive regulation of tumor necrosis factor production	37	102	5.854e-03
GO:BP	GO:0046456	icosanoid biosynthetic process	24	57	5.854e-03
GO:BP	GO:0032733	positive regulation of interleukin-10 production	19	41	5.913e-03
GO:BP	GO:0009072	aromatic amino acid metabolic process	19	41	5.913e-03
GO:BP	GO:0010817	regulation of hormone levels	148	548	5.969e-03
GO:BP	GO:0042755	eating behavior	18	38	6.100e-03
GO:BP	GO:0050482	arachidonate secretion	16	32	6.178e-03
GO:BP	GO:1903963	arachidonate transport	16	32	6.178e-03
GO:BP	GO:1903557	positive regulation of tumor necrosis factor superfamily cytokine production	38	106	6.239e-03
GO:BP	GO:0071347	cellular response to interleukin-1	38	106	6.239e-03
GO:BP	GO:0002440	production of molecular mediator of immune response	68	220	6.306e-03
GO:BP	GO:1901652	response to peptide	241	950	6.306e-03
GO:BP	GO:0032732	positive regulation of interleukin-1 production	28	71	6.656e-03
GO:BP	GO:0002820	negative regulation of adaptive immune response	25	61	6.970e-03
GO:BP	GO:0050795	regulation of behavior	29	75	7.694e-03
GO:BP	GO:0070944	neutrophil-mediated killing of bacterium	8	11	8.362e-03
GO:BP	GO:1903027	regulation of opsonization	8	11	8.362e-03
GO:BP	GO:0044058	regulation of digestive system process	18	39	8.822e-03
GO:BP	GO:0034374	low-density lipoprotein particle remodeling	10	16	9.089e-03
GO:BP	GO:0002675	positive regulation of acute inflammatory response	14	27	9.089e-03
GO:BP	GO:0015671	oxygen transport	10	16	9.089e-03
GO:BP	GO:0002719	negative regulation of cytokine production involved in immune response	16	33	9.254e-03
GO:BP	GO:0050891	multicellular organismal-level water homeostasis	16	33	9.254e-03
GO:BP	GO:0001562	response to protozoan	15	30	9.254e-03
GO:BP	GO:0050766	positive regulation of phagocytosis	27	69	9.556e-03
GO:BP	GO:0002688	regulation of leukocyte chemotaxis	42	123	9.628e-03
GO:BP	GO:0022407	regulation of cell-cell adhesion	130	478	9.660e-03
GO:BP	GO:0052696	flavonoid glucuronidation	5	5	1.015e-02
GO:BP	GO:0002803	positive regulation of antibacterial peptide production	5	5	1.015e-02
GO:BP	GO:1903028	positive regulation of opsonization	7	9	1.047e-02
GO:BP	GO:0001912	positive regulation of leukocyte mediated cytotoxicity	26	66	1.060e-02
GO:BP	GO:0042267	natural killer cell mediated cytotoxicity	28	73	1.081e-02
GO:BP	GO:0002827	positive regulation of T-helper 1 type immune response	11	19	1.105e-02
GO:BP	GO:0019370	leukotriene biosynthetic process	11	19	1.105e-02
GO:BP	GO:0007187	G protein-coupled receptor signaling pathway, coupled to cyclic nucleotide second messenger	23	56	1.105e-02
GO:BP	GO:0035743	CD4-positive, alpha-beta T cell cytokine production	11	19	1.105e-02
GO:BP	GO:0002823	negative regulation of adaptive immune response based on somatic recombination of immune receptors built from immunoglobulin superfamily domains	23	56	1.105e-02
GO:BP	GO:0007198	adenylate cyclase-inhibiting serotonin receptor signaling pathway	6	7	1.179e-02
GO:BP	GO:0043299	leukocyte degranulation	31	84	1.180e-02
GO:BP	GO:0002683	negative regulation of immune system process	135	502	1.204e-02
GO:BP	GO:0035036	sperm-egg recognition	22	53	1.204e-02
GO:BP	GO:0050867	positive regulation of cell activation	104	372	1.216e-02
GO:BP	GO:0070555	response to interleukin-1	44	132	1.220e-02
GO:BP	GO:0002446	neutrophil mediated immunity	17	37	1.269e-02
GO:BP	GO:0010273	detoxification of copper ion	9	14	1.269e-02
GO:BP	GO:0002430	complement receptor mediated signaling pathway	9	14	1.269e-02
GO:BP	GO:1990169	stress response to copper ion	9	14	1.269e-02
GO:BP	GO:0072678	T cell migration	28	74	1.338e-02
GO:BP	GO:1902221	erythrose 4-phosphate/phosphoenolpyruvate family amino acid metabolic process	14	28	1.358e-02
GO:BP	GO:0055078	sodium ion homeostasis	20	47	1.432e-02
GO:BP	GO:0009988	cell-cell recognition	28	75	1.695e-02
GO:BP	GO:0008037	cell recognition	50	157	1.695e-02
GO:BP	GO:0044706	multi-multicellular organism process	64	212	1.695e-02
GO:BP	GO:0043330	response to exogenous dsRNA	21	51	1.764e-02
GO:BP	GO:0032621	interleukin-18 production	8	12	1.828e-02
GO:BP	GO:0016056	G protein-coupled opsin signaling pathway	8	12	1.828e-02
GO:BP	GO:0032661	regulation of interleukin-18 production	8	12	1.828e-02
GO:BP	GO:0009812	flavonoid metabolic process	8	12	1.828e-02
GO:BP	GO:0022408	negative regulation of cell-cell adhesion	58	189	1.862e-02
GO:BP	GO:0042130	negative regulation of T cell proliferation	27	72	1.900e-02
GO:BP	GO:0006775	fat-soluble vitamin metabolic process	20	48	1.924e-02
GO:BP	GO:0018149	peptide cross-linking	14	29	2.049e-02
GO:BP	GO:0006910	phagocytosis, recognition	14	29	2.049e-02
GO:BP	GO:0098581	detection of external biotic stimulus	13	26	2.058e-02
GO:BP	GO:0032729	positive regulation of type II interferon production	28	76	2.093e-02
GO:BP	GO:0048523	negative regulation of cellular process	1251	5646	2.251e-02
GO:BP	GO:0030098	lymphocyte differentiation	118	438	2.292e-02
GO:BP	GO:0046006	regulation of activated T cell proliferation	18	42	2.298e-02
GO:BP	GO:0044703	multi-organism reproductive process	61	203	2.426e-02
GO:BP	GO:0141005	transposable element silencing by heterochromatin formation	9	15	2.437e-02
GO:BP	GO:0007340	acrosome reaction	17	39	2.484e-02
GO:BP	GO:0002690	positive regulation of leukocyte chemotaxis	33	95	2.484e-02
GO:BP	GO:0032635	interleukin-6 production	48	152	2.487e-02
GO:BP	GO:0032675	regulation of interleukin-6 production	48	152	2.487e-02
GO:BP	GO:0002361	CD4-positive, CD25-positive, alpha-beta regulatory T cell differentiation	7	10	2.492e-02
GO:BP	GO:0008343	adult feeding behavior	7	10	2.492e-02
GO:BP	GO:0002696	positive regulation of leukocyte activation	98	355	2.492e-02
GO:BP	GO:0002676	regulation of chronic inflammatory response	7	10	2.492e-02
GO:BP	GO:0002765	immune response-inhibiting signal transduction	7	10	2.492e-02
GO:BP	GO:0002821	positive regulation of adaptive immune response	42	129	2.492e-02
GO:BP	GO:0071947	protein deubiquitination involved in ubiquitin-dependent protein catabolic process	7	10	2.492e-02
GO:BP	GO:0035747	natural killer cell chemotaxis	7	10	2.492e-02
GO:BP	GO:0006869	lipid transport	116	431	2.510e-02
GO:BP	GO:0002437	inflammatory response to antigenic stimulus	28	77	2.522e-02
GO:BP	GO:0006721	terpenoid metabolic process	34	99	2.549e-02
GO:BP	GO:0002764	immune response-regulating signaling pathway	133	504	2.619e-02
GO:BP	GO:0042269	regulation of natural killer cell mediated cytotoxicity	19	46	2.740e-02
GO:BP	GO:0034369	plasma lipoprotein particle remodeling	15	33	2.741e-02
GO:BP	GO:0042573	retinoic acid metabolic process	15	33	2.741e-02
GO:BP	GO:0034368	protein-lipid complex remodeling	15	33	2.741e-02
GO:BP	GO:0010669	epithelial structure maintenance	15	33	2.741e-02
GO:BP	GO:0007603	phototransduction, visible light	10	18	2.741e-02
GO:BP	GO:0002523	leukocyte migration involved in inflammatory response	11	21	2.925e-02
GO:BP	GO:0042745	circadian sleep/wake cycle	11	21	2.925e-02
GO:BP	GO:0043950	positive regulation of cAMP-mediated signaling	11	21	2.925e-02
GO:BP	GO:0002577	regulation of antigen processing and presentation	11	21	2.925e-02
GO:BP	GO:0032731	positive regulation of interleukin-1 beta production	23	60	2.925e-02
GO:BP	GO:0003352	regulation of cilium movement	18	43	2.957e-02
GO:BP	GO:0002438	acute inflammatory response to antigenic stimulus	13	27	2.957e-02
GO:BP	GO:0046634	regulation of alpha-beta T cell activation	38	115	2.962e-02
GO:BP	GO:0009074	aromatic amino acid family catabolic process	12	24	2.967e-02
GO:BP	GO:0002367	cytokine production involved in immune response	39	119	3.047e-02
GO:BP	GO:0002718	regulation of cytokine production involved in immune response	39	119	3.047e-02
GO:BP	GO:0002824	positive regulation of adaptive immune response based on somatic recombination of immune receptors built from immunoglobulin superfamily domains	40	123	3.138e-02
GO:BP	GO:0042088	T-helper 1 type immune response	20	50	3.165e-02
GO:BP	GO:2000501	regulation of natural killer cell chemotaxis	6	8	3.222e-02
GO:BP	GO:1903039	positive regulation of leukocyte cell-cell adhesion	77	271	3.222e-02
GO:BP	GO:0019369	arachidonate metabolic process	22	57	3.222e-02
GO:BP	GO:0070268	cornification	6	8	3.222e-02
GO:BP	GO:0032714	negative regulation of interleukin-5 production	6	8	3.222e-02
GO:BP	GO:0032741	positive regulation of interleukin-18 production	6	8	3.222e-02
GO:BP	GO:0014061	regulation of norepinephrine secretion	8	13	3.369e-02
GO:BP	GO:0046541	saliva secretion	8	13	3.369e-02
GO:BP	GO:0035745	T-helper 2 cell cytokine production	8	13	3.369e-02
GO:BP	GO:2000551	regulation of T-helper 2 cell cytokine production	8	13	3.369e-02
GO:BP	GO:0060456	positive regulation of digestive system process	8	13	3.369e-02
GO:BP	GO:0032720	negative regulation of tumor necrosis factor production	23	61	3.613e-02
GO:BP	GO:0032692	negative regulation of interleukin-1 production	15	34	3.738e-02
GO:BP	GO:0002702	positive regulation of production of molecular mediator of immune response	43	136	3.774e-02
GO:BP	GO:0042320	regulation of circadian sleep/wake cycle, REM sleep	4	4	3.774e-02
GO:BP	GO:0036101	leukotriene B4 catabolic process	4	4	3.774e-02
GO:BP	GO:0042376	phylloquinone catabolic process	4	4	3.774e-02
GO:BP	GO:0042377	vitamin K catabolic process	4	4	3.774e-02
GO:BP	GO:0042374	phylloquinone metabolic process	4	4	3.774e-02
GO:BP	GO:2000851	positive regulation of glucocorticoid secretion	4	4	3.774e-02
GO:BP	GO:0042747	circadian sleep/wake cycle, REM sleep	4	4	3.774e-02
GO:BP	GO:0002325	natural killer cell differentiation involved in immune response	4	4	3.774e-02
GO:BP	GO:0045938	positive regulation of circadian sleep/wake cycle, sleep	4	4	3.774e-02
GO:BP	GO:0002429	immune response-activating cell surface receptor signaling pathway	85	306	3.774e-02
GO:BP	GO:0060480	lung goblet cell differentiation	4	4	3.774e-02
GO:BP	GO:0032826	regulation of natural killer cell differentiation involved in immune response	4	4	3.774e-02
GO:BP	GO:0044278	disruption of cell wall in another organism	4	4	3.774e-02
GO:BP	GO:0051464	positive regulation of cortisol secretion	4	4	3.774e-02
GO:BP	GO:0002507	tolerance induction	14	31	3.812e-02
GO:BP	GO:0051969	regulation of transmission of nerve impulse	9	16	3.812e-02
GO:BP	GO:0034382	chylomicron remnant clearance	5	6	3.812e-02
GO:BP	GO:2000503	positive regulation of natural killer cell chemotaxis	5	6	3.812e-02
GO:BP	GO:0036100	leukotriene catabolic process	5	6	3.812e-02
GO:BP	GO:0010901	regulation of very-low-density lipoprotein particle remodeling	5	6	3.812e-02
GO:BP	GO:0035821	modulation of process of another organism	9	16	3.812e-02
GO:BP	GO:0097272	ammonium homeostasis	5	6	3.812e-02
GO:BP	GO:0022409	positive regulation of cell-cell adhesion	88	319	3.812e-02
GO:BP	GO:0072378	blood coagulation, fibrin clot formation	9	16	3.812e-02
GO:BP	GO:0046942	carboxylic acid transport	94	344	3.812e-02
GO:BP	GO:0042744	hydrogen peroxide catabolic process	14	31	3.812e-02
GO:BP	GO:0050731	positive regulation of peptidyl-tyrosine phosphorylation	50	164	3.908e-02
GO:BP	GO:0015849	organic acid transport	94	345	4.079e-02
GO:BP	GO:0032693	negative regulation of interleukin-10 production	10	19	4.083e-02
GO:BP	GO:0072376	protein activation cascade	10	19	4.083e-02
GO:BP	GO:0097501	stress response to metal ion	10	19	4.083e-02
GO:BP	GO:0022410	circadian sleep/wake cycle process	10	19	4.083e-02
GO:BP	GO:0098543	detection of other organism	10	19	4.083e-02
GO:BP	GO:0042749	regulation of circadian sleep/wake cycle	10	19	4.083e-02
GO:BP	GO:0048520	positive regulation of behavior	12	25	4.100e-02
GO:BP	GO:0042430	indole-containing compound metabolic process	12	25	4.100e-02
GO:BP	GO:0002833	positive regulation of response to biotic stimulus	102	379	4.100e-02
GO:BP	GO:1900015	regulation of cytokine production involved in inflammatory response	23	62	4.233e-02
GO:BP	GO:0002534	cytokine production involved in inflammatory response	23	62	4.233e-02
GO:BP	GO:0050878	regulation of body fluid levels	100	371	4.233e-02
GO:BP	GO:2000344	positive regulation of acrosome reaction	7	11	4.646e-02
GO:BP	GO:0034105	positive regulation of tissue remodeling	7	11	4.646e-02
GO:BP	GO:0032375	negative regulation of cholesterol transport	7	11	4.646e-02
GO:BP	GO:0032372	negative regulation of sterol transport	7	11	4.646e-02
GO:BP	GO:0030888	regulation of B cell proliferation	24	66	4.646e-02
GO:BP	GO:0002725	negative regulation of T cell cytokine production	7	11	4.646e-02
GO:BP	GO:0021562	vestibulocochlear nerve development	7	11	4.646e-02
GO:BP	GO:0042116	macrophage activation	35	107	4.681e-02
GO:BP	GO:0046636	negative regulation of alpha-beta T cell activation	18	45	4.681e-02
KEGG	KEGG:04740	Olfactory transduction	369	428	7.883e-179
KEGG	KEGG:04060	Cytokine-cytokine receptor interaction	154	291	2.327e-27
KEGG	KEGG:04080	Neuroactive ligand-receptor interaction	178	365	2.562e-26
KEGG	KEGG:05206	MicroRNAs in cancer	149	310	4.215e-21
KEGG	KEGG:05150	Staphylococcus aureus infection	60	86	1.731e-18
KEGG	KEGG:04061	Viral protein interaction with cytokine and cytokine receptor	63	98	1.101e-16
KEGG	KEGG:04742	Taste transduction	49	85	2.376e-10
KEGG	KEGG:00830	Retinol metabolism	41	68	1.610e-09
KEGG	KEGG:05320	Autoimmune thyroid disease	32	49	1.071e-08
KEGG	KEGG:05310	Asthma	21	27	8.154e-08
KEGG	KEGG:00980	Metabolism of xenobiotics by cytochrome P450	40	74	1.840e-07
KEGG	KEGG:04640	Hematopoietic cell lineage	46	92	3.330e-07
KEGG	KEGG:05204	Chemical carcinogenesis - DNA adducts	36	67	1.103e-06
KEGG	KEGG:04672	Intestinal immune network for IgA production	26	44	6.383e-06
KEGG	KEGG:00982	Drug metabolism - cytochrome P450	34	68	2.141e-05
KEGG	KEGG:04630	JAK-STAT signaling pathway	64	162	3.107e-05
KEGG	KEGG:05323	Rheumatoid arthritis	40	88	4.815e-05
KEGG	KEGG:00053	Ascorbate and aldarate metabolism	19	30	4.815e-05
KEGG	KEGG:05322	Systemic lupus erythematosus	54	132	4.823e-05
KEGG	KEGG:00140	Steroid hormone biosynthesis	31	62	4.823e-05
KEGG	KEGG:05332	Graft-versus-host disease	21	37	1.440e-04
KEGG	KEGG:04976	Bile secretion	39	89	1.440e-04
KEGG	KEGG:05321	Inflammatory bowel disease	30	62	1.440e-04
KEGG	KEGG:00590	Arachidonic acid metabolism	29	61	2.912e-04
KEGG	KEGG:05144	Malaria	24	49	7.806e-04
KEGG	KEGG:00591	Linoleic acid metabolism	17	30	8.847e-04
KEGG	KEGG:00040	Pentose and glucuronate interconversions	19	36	1.186e-03
KEGG	KEGG:00592	alpha-Linolenic acid metabolism	15	26	1.624e-03
KEGG	KEGG:05330	Allograft rejection	18	34	1.624e-03
KEGG	KEGG:04610	Complement and coagulation cascades	35	86	1.941e-03
KEGG	KEGG:04650	Natural killer cell mediated cytotoxicity	45	124	5.422e-03
KEGG	KEGG:04940	Type I diabetes mellitus	19	40	5.422e-03
KEGG	KEGG:00860	Porphyrin metabolism	20	43	5.422e-03
KEGG	KEGG:04975	Fat digestion and absorption	20	43	5.422e-03
KEGG	KEGG:05340	Primary immunodeficiency	18	37	5.422e-03
KEGG	KEGG:05164	Influenza A	57	167	5.688e-03
KEGG	KEGG:05152	Tuberculosis	59	175	6.375e-03
KEGG	KEGG:05143	African trypanosomiasis	17	36	1.011e-02
KEGG	KEGG:00350	Tyrosine metabolism	17	36	1.011e-02
KEGG	KEGG:04620	Toll-like receptor signaling pathway	38	106	1.465e-02
KEGG	KEGG:00983	Drug metabolism - other enzymes	30	79	1.527e-02
KEGG	KEGG:04514	Cell adhesion molecules	50	153	2.874e-02
KEGG	KEGG:05133	Pertussis	28	76	3.368e-02
KEGG	KEGG:04613	Neutrophil extracellular trap formation	59	188	3.520e-02
KEGG	KEGG:04972	Pancreatic secretion	35	102	4.363e-02
KEGG	KEGG:04657	IL-17 signaling pathway	32	92	4.766e-02

#write.csv(tableNR, "output/table_NRmotif.csv")

#GO:BP
tableNR_GOBP_d <- tableNR_d %>% 
  dplyr::filter(source=="GO:BP") %>% 
  dplyr::select(p_value, term_name, intersection_size) %>% 
  dplyr::slice_min(., n=10, order_by=p_value) %>% 
  mutate(log_val = -log10(p_value))

#saveRDS(tableNR_GOBP, "data/tableNR_GOBP.RDS")

tableNR_GOBP_d %>% ggplot(., aes(x = log_val, y = reorder(term_name, p_value), col= intersection_size)) +
  geom_point(aes(size = intersection_size)) +
  ggtitle("No Response Enriched GO:BP Terms")+
  xlab(expression("-log"[10]~"p-value"))+
  guides(col="none", size= guide_legend(title = "# of intersected \n terms"))+
  ylab("GO:BP term")+
  scale_y_discrete(labels = scales::label_wrap(30))+
  theme_bw()+
  theme(plot.title = element_text(size = rel(1.5), hjust = 0.5),
        axis.title = element_text(size = 15, colour = "black"),
        axis.ticks = element_line(linewidth = 1.5),
        axis.line = element_line(linewidth = 1.5),
        axis.text = element_text(size = 10, colour = "black", angle = 0),
        strip.text = element_text(size = 15, colour = "black", face = "bold"))

Past versions of "GO analysis NR Dox only-2.png"

Version	Author	Date
ff644ec	emmapfort	2025-04-18
cee6b3d	emmapfort	2025-04-18
84d5599	emmapfort	2025-04-14

#KEGG
tableNR_KEGG_d <- tableNR_d %>% 
  dplyr::filter(source=="KEGG") %>% 
  dplyr::select(p_value, term_name, intersection_size) %>% 
  dplyr::slice_min(., n=10, order_by=p_value) %>% 
  mutate(log_val = -log10(p_value))

tableNR_KEGG_d %>% ggplot(., aes(x = log_val, y = reorder(term_name, p_value), col= intersection_size)) +
  geom_point(aes(size = intersection_size)) +
  ggtitle("No Response Enriched KEGG Terms")+
  xlab(expression("-log"[10]~"p-value"))+
  guides(col="none", size= guide_legend(title = "# of intersected \n terms"))+
  ylab("KEGG term")+
  scale_y_discrete(labels = scales::label_wrap(30))+
  theme_bw()+
  theme(plot.title = element_text(size = rel(1.5), hjust = 0.5),
        axis.title = element_text(size = 15, colour = "black"),
        axis.ticks = element_line(linewidth = 1.5),
        axis.line = element_line(linewidth = 1.5),
        axis.text = element_text(size = 10, colour = "black", angle = 0),
        strip.text = element_text(size = 15, colour = "black", face = "bold"))

Past versions of "GO analysis NR Dox only-3.png"

Version	Author	Date
ff644ec	emmapfort	2025-04-18
cee6b3d	emmapfort	2025-04-18
84d5599	emmapfort	2025-04-14

Now let’s do the same thing but with the posterior probability rather than the clustlike

motif_NR_pp <- prob_motif_1

NRmotif_genes_pp <- gost(query = motif_NR_pp,
                      organism = "hsapiens",
                      ordered_query = FALSE,
                      measure_underrepresentation = FALSE,
                      evcodes = FALSE,
                      user_threshold = 0.05,
                      correction_method = c("fdr"),
                      sources = c("GO:BP", "KEGG"))

cormotifNFclust_pp <- gostplot(NRmotif_genes_pp, capped = FALSE, interactive = TRUE)
cormotifNFclust_pp

tableNR_pp <- NRmotif_genes_pp$result %>% 
  dplyr::select(c(source, term_id, term_name, intersection_size, term_size, p_value))

tableNR_pp %>% 
  mutate_at(.vars = 6, .funs = scales::label_scientific(digits=4)) %>% 
  kableExtra::kable(.,) %>% 
  kableExtra::kable_paper("striped", full_width = FALSE) %>% 
  kableExtra::kable_styling(full_width = FALSE, position = "left", bootstrap_options = c("striped", "hover")) %>% 
  kableExtra::scroll_box(width = "100%", height = "400px")

source	term_id	term_name	intersection_size	term_size	p_value
GO:BP	GO:0050907	detection of chemical stimulus involved in sensory perception	390	443	1.287e-211
GO:BP	GO:0050911	detection of chemical stimulus involved in sensory perception of smell	361	397	3.880e-207
GO:BP	GO:0035195	miRNA-mediated post-transcriptional gene silencing	470	612	1.992e-205
GO:BP	GO:0007606	sensory perception of chemical stimulus	413	497	2.606e-204
GO:BP	GO:0035194	regulatory ncRNA-mediated post-transcriptional gene silencing	471	624	2.134e-200
GO:BP	GO:0016441	post-transcriptional gene silencing	472	630	1.663e-198
GO:BP	GO:0009593	detection of chemical stimulus	399	480	1.882e-197
GO:BP	GO:0007608	sensory perception of smell	368	423	4.525e-196
GO:BP	GO:0050906	detection of stimulus involved in sensory perception	412	515	8.753e-192
GO:BP	GO:0031047	regulatory ncRNA-mediated gene silencing	478	686	7.125e-179
GO:BP	GO:0007186	G protein-coupled receptor signaling pathway	691	1275	6.531e-171
GO:BP	GO:0051606	detection of stimulus	450	643	3.612e-169
GO:BP	GO:0007600	sensory perception	550	955	1.330e-149
GO:BP	GO:0050877	nervous system process	640	1489	7.974e-96
GO:BP	GO:0010608	post-transcriptional regulation of gene expression	507	1087	6.512e-90
GO:BP	GO:0003008	system process	792	2266	7.511e-68
GO:BP	GO:0010629	negative regulation of gene expression	623	1640	4.964e-67
GO:BP	GO:0042221	response to chemical	1081	3867	6.538e-38
GO:BP	GO:0065007	biological regulation	2890	12671	3.299e-35
GO:BP	GO:0050789	regulation of biological process	2803	12278	6.612e-33
GO:BP	GO:0042742	defense response to bacterium	163	326	1.270e-31
GO:BP	GO:0006952	defense response	567	1809	7.997e-31
GO:BP	GO:0032501	multicellular organismal process	1775	7234	4.261e-30
GO:BP	GO:0050794	regulation of cellular process	2710	11876	4.261e-30
GO:BP	GO:0006959	humoral immune response	135	254	1.532e-29
GO:BP	GO:0010558	negative regulation of macromolecule biosynthetic process	784	2772	2.288e-27
GO:BP	GO:0009617	response to bacterium	270	721	5.192e-26
GO:BP	GO:0009890	negative regulation of biosynthetic process	792	2838	1.031e-25
GO:BP	GO:0098542	defense response to other organism	401	1228	7.042e-25
GO:BP	GO:0031424	keratinization	62	82	7.370e-25
GO:BP	GO:0019730	antimicrobial humoral response	81	131	3.323e-23
GO:BP	GO:0043207	response to external biotic stimulus	472	1558	1.127e-21
GO:BP	GO:0051707	response to other organism	470	1555	2.367e-21
GO:BP	GO:0140546	defense response to symbiont	363	1125	2.502e-21
GO:BP	GO:0009607	response to biotic stimulus	479	1593	2.604e-21
GO:BP	GO:0007165	signal transduction	1438	5979	5.050e-18
GO:BP	GO:0009605	response to external stimulus	645	2367	1.527e-17
GO:BP	GO:0141060	disruption of anatomical structure in another organism	60	98	1.074e-16
GO:BP	GO:0001906	cell killing	102	219	1.111e-16
GO:BP	GO:0010605	negative regulation of macromolecule metabolic process	826	3197	2.318e-16
GO:BP	GO:0006954	inflammatory response	275	847	3.167e-16
GO:BP	GO:0044419	biological process involved in interspecies interaction between organisms	489	1724	3.212e-16
GO:BP	GO:0061844	antimicrobial humoral immune response mediated by antimicrobial peptide	53	83	7.347e-16
GO:BP	GO:0031640	killing of cells of another organism	56	91	9.719e-16
GO:BP	GO:0141061	disruption of cell in another organism	56	91	9.719e-16
GO:BP	GO:0045087	innate immune response	305	977	1.891e-15
GO:BP	GO:0045109	intermediate filament organization	48	73	4.381e-15
GO:BP	GO:0006955	immune response	549	2008	5.955e-15
GO:BP	GO:0030216	keratinocyte differentiation	84	176	1.835e-14
GO:BP	GO:0007154	cell communication	1520	6496	1.967e-14
GO:BP	GO:0023052	signaling	1513	6471	3.321e-14
GO:BP	GO:0009892	negative regulation of metabolic process	859	3418	7.863e-14
GO:BP	GO:0097530	granulocyte migration	74	156	1.684e-12
GO:BP	GO:1990266	neutrophil migration	65	129	1.812e-12
GO:BP	GO:0050896	response to stimulus	2016	8993	1.856e-12
GO:BP	GO:0050829	defense response to Gram-negative bacterium	51	91	5.170e-12
GO:BP	GO:0050830	defense response to Gram-positive bacterium	61	120	6.701e-12
GO:BP	GO:0030593	neutrophil chemotaxis	56	106	8.589e-12
GO:BP	GO:0009913	epidermal cell differentiation	101	250	1.235e-11
GO:BP	GO:0002252	immune effector process	221	703	2.576e-11
GO:BP	GO:0071621	granulocyte chemotaxis	63	129	2.607e-11
GO:BP	GO:0007586	digestion	65	136	3.831e-11
GO:BP	GO:0030595	leukocyte chemotaxis	95	237	1.092e-10
GO:BP	GO:0050900	leukocyte migration	139	396	1.402e-10
GO:BP	GO:0050909	sensory perception of taste	40	67	1.572e-10
GO:BP	GO:0002237	response to molecule of bacterial origin	127	355	2.877e-10
GO:BP	GO:0002697	regulation of immune effector process	134	381	2.911e-10
GO:BP	GO:0045104	intermediate filament cytoskeleton organization	49	94	5.229e-10
GO:BP	GO:0002376	immune system process	696	2796	6.460e-10
GO:BP	GO:0097529	myeloid leukocyte migration	93	237	7.182e-10
GO:BP	GO:0002323	natural killer cell activation involved in immune response	26	35	8.175e-10
GO:BP	GO:0045103	intermediate filament-based process	49	95	8.229e-10
GO:BP	GO:0007218	neuropeptide signaling pathway	54	110	8.825e-10
GO:BP	GO:0019731	antibacterial humoral response	39	68	1.527e-09
GO:BP	GO:0071219	cellular response to molecule of bacterial origin	88	224	2.298e-09
GO:BP	GO:0032496	response to lipopolysaccharide	119	337	3.248e-09
GO:BP	GO:0008544	epidermis development	134	394	3.770e-09
GO:BP	GO:0070661	leukocyte proliferation	122	351	5.808e-09
GO:BP	GO:0071222	cellular response to lipopolysaccharide	84	214	6.541e-09
GO:BP	GO:0050913	sensory perception of bitter taste	28	42	7.382e-09
GO:BP	GO:0046651	lymphocyte proliferation	110	308	7.797e-09
GO:BP	GO:0051716	cellular response to stimulus	1639	7320	1.120e-08
GO:BP	GO:0007283	spermatogenesis	194	637	1.246e-08
GO:BP	GO:0007338	single fertilization	70	169	1.462e-08
GO:BP	GO:0032943	mononuclear cell proliferation	111	315	1.544e-08
GO:BP	GO:0050912	detection of chemical stimulus involved in sensory perception of taste	28	43	1.592e-08
GO:BP	GO:0052695	cellular glucuronidation	18	21	1.831e-08
GO:BP	GO:0033141	positive regulation of peptidyl-serine phosphorylation of STAT protein	18	21	1.831e-08
GO:BP	GO:0070098	chemokine-mediated signaling pathway	45	90	1.838e-08
GO:BP	GO:0048232	male gamete generation	197	654	2.315e-08
GO:BP	GO:0042100	B cell proliferation	50	106	2.576e-08
GO:BP	GO:0071715	icosanoid transport	36	65	2.911e-08
GO:BP	GO:0060326	cell chemotaxis	111	319	3.324e-08
GO:BP	GO:0001580	detection of chemical stimulus involved in sensory perception of bitter taste	25	37	4.338e-08
GO:BP	GO:0009566	fertilization	81	212	5.545e-08
GO:BP	GO:0002682	regulation of immune system process	399	1526	7.018e-08
GO:BP	GO:0045321	leukocyte activation	265	951	1.229e-07
GO:BP	GO:0002548	monocyte chemotaxis	36	68	1.442e-07
GO:BP	GO:0001775	cell activation	299	1098	1.442e-07
GO:BP	GO:0019221	cytokine-mediated signaling pathway	156	503	1.723e-07
GO:BP	GO:0048245	eosinophil chemotaxis	20	27	1.818e-07
GO:BP	GO:0070663	regulation of leukocyte proliferation	94	265	2.192e-07
GO:BP	GO:0071216	cellular response to biotic stimulus	90	251	2.555e-07
GO:BP	GO:0002526	acute inflammatory response	49	109	2.614e-07
GO:BP	GO:0022414	reproductive process	401	1556	3.920e-07
GO:BP	GO:0048609	multicellular organismal reproductive process	269	980	4.080e-07
GO:BP	GO:0022600	digestive system process	47	105	6.278e-07
GO:BP	GO:1990869	cellular response to chemokine	45	99	7.116e-07
GO:BP	GO:1990868	response to chemokine	45	99	7.116e-07
GO:BP	GO:0002366	leukocyte activation involved in immune response	103	305	7.469e-07
GO:BP	GO:0002263	cell activation involved in immune response	104	309	7.689e-07
GO:BP	GO:0033139	regulation of peptidyl-serine phosphorylation of STAT protein	18	24	7.793e-07
GO:BP	GO:0002699	positive regulation of immune effector process	89	253	8.236e-07
GO:BP	GO:0072677	eosinophil migration	21	31	8.501e-07
GO:BP	GO:0006953	acute-phase response	28	49	8.612e-07
GO:BP	GO:0002274	myeloid leukocyte activation	85	240	1.193e-06
GO:BP	GO:0050832	defense response to fungus	31	59	2.090e-06
GO:BP	GO:0042501	serine phosphorylation of STAT protein	18	25	2.145e-06
GO:BP	GO:0060294	cilium movement involved in cell motility	64	167	2.377e-06
GO:BP	GO:0050670	regulation of lymphocyte proliferation	83	236	2.430e-06
GO:BP	GO:0032944	regulation of mononuclear cell proliferation	84	240	2.562e-06
GO:BP	GO:0031341	regulation of cell killing	46	106	2.568e-06
GO:BP	GO:0002684	positive regulation of immune system process	284	1066	2.902e-06
GO:BP	GO:0030317	flagellated sperm motility	58	147	2.965e-06
GO:BP	GO:0097722	sperm motility	58	147	2.965e-06
GO:BP	GO:0048247	lymphocyte chemotaxis	32	63	3.354e-06
GO:BP	GO:0032649	regulation of type II interferon production	49	117	3.559e-06
GO:BP	GO:0043588	skin development	105	322	3.654e-06
GO:BP	GO:0032609	type II interferon production	49	118	4.838e-06
GO:BP	GO:0019585	glucuronate metabolic process	18	26	5.102e-06
GO:BP	GO:0006063	uronic acid metabolic process	18	26	5.102e-06
GO:BP	GO:0007188	adenylate cyclase-modulating G protein-coupled receptor signaling pathway	85	248	5.705e-06
GO:BP	GO:0050776	regulation of immune response	243	897	6.122e-06
GO:BP	GO:0002775	antimicrobial peptide production	10	10	6.776e-06
GO:BP	GO:0140975	disruption of cellular anatomical structure in another organism	10	10	6.776e-06
GO:BP	GO:0019953	sexual reproduction	290	1103	7.052e-06
GO:BP	GO:0007631	feeding behavior	45	106	7.082e-06
GO:BP	GO:0001539	cilium or flagellum-dependent cell motility	64	172	7.376e-06
GO:BP	GO:0060285	cilium-dependent cell motility	64	172	7.376e-06
GO:BP	GO:0002922	positive regulation of humoral immune response	16	22	8.801e-06
GO:BP	GO:0002703	regulation of leukocyte mediated immunity	83	243	8.934e-06
GO:BP	GO:0072676	lymphocyte migration	50	124	9.854e-06
GO:BP	GO:0030101	natural killer cell activation	41	95	1.434e-05
GO:BP	GO:0007259	cell surface receptor signaling pathway via JAK-STAT	62	168	1.566e-05
GO:BP	GO:0010468	regulation of gene expression	1231	5515	1.601e-05
GO:BP	GO:0007342	fusion of sperm to egg plasma membrane involved in single fertilization	19	30	1.685e-05
GO:BP	GO:0007276	gamete generation	223	822	1.685e-05
GO:BP	GO:0022412	cellular process involved in reproduction in multicellular organism	124	408	1.784e-05
GO:BP	GO:0097696	cell surface receptor signaling pathway via STAT	64	176	1.813e-05
GO:BP	GO:0050727	regulation of inflammatory response	117	381	2.093e-05
GO:BP	GO:0048240	sperm capacitation	20	33	2.241e-05
GO:BP	GO:0001909	leukocyte mediated cytotoxicity	52	135	2.922e-05
GO:BP	GO:0042330	taxis	137	465	3.037e-05
GO:BP	GO:0001819	positive regulation of cytokine production	142	486	3.187e-05
GO:BP	GO:0015908	fatty acid transport	47	118	3.220e-05
GO:BP	GO:0071674	mononuclear cell migration	79	235	3.327e-05
GO:BP	GO:0015718	monocarboxylic acid transport	64	179	3.440e-05
GO:BP	GO:0006690	icosanoid metabolic process	48	122	3.689e-05
GO:BP	GO:0032309	icosanoid secretion	25	48	4.224e-05
GO:BP	GO:0042129	regulation of T cell proliferation	64	180	4.227e-05
GO:BP	GO:0007286	spermatid development	73	214	4.564e-05
GO:BP	GO:0007200	phospholipase C-activating G protein-coupled receptor signaling pathway	46	116	4.695e-05
GO:BP	GO:0015732	prostaglandin transport	18	29	4.842e-05
GO:BP	GO:0051873	killing by host of symbiont cells	18	29	4.842e-05
GO:BP	GO:0001817	regulation of cytokine production	207	765	4.892e-05
GO:BP	GO:0007159	leukocyte cell-cell adhesion	121	404	5.096e-05
GO:BP	GO:0009620	response to fungus	32	70	5.455e-05
GO:BP	GO:0002251	organ or tissue specific immune response	23	43	5.998e-05
GO:BP	GO:0001816	cytokine production	208	772	6.150e-05
GO:BP	GO:0006935	chemotaxis	135	463	6.150e-05
GO:BP	GO:0002706	regulation of lymphocyte mediated immunity	64	182	6.150e-05
GO:BP	GO:0050865	regulation of cell activation	171	616	7.851e-05
GO:BP	GO:0050778	positive regulation of immune response	198	732	8.254e-05
GO:BP	GO:0034341	response to type II interferon	54	147	8.849e-05
GO:BP	GO:0002285	lymphocyte activation involved in immune response	72	214	8.885e-05
GO:BP	GO:0098586	cellular response to virus	34	78	9.303e-05
GO:BP	GO:0050953	sensory perception of light stimulus	74	222	9.367e-05
GO:BP	GO:0048515	spermatid differentiation	74	222	9.367e-05
GO:BP	GO:0036230	granulocyte activation	25	50	1.007e-04
GO:BP	GO:0007601	visual perception	73	219	1.084e-04
GO:BP	GO:0051250	negative regulation of lymphocyte activation	57	159	1.093e-04
GO:BP	GO:0001910	regulation of leukocyte mediated cytotoxicity	38	92	1.145e-04
GO:BP	GO:0002694	regulation of leukocyte activation	157	561	1.184e-04
GO:BP	GO:0002760	positive regulation of antimicrobial humoral response	8	8	1.237e-04
GO:BP	GO:0002778	antibacterial peptide production	8	8	1.237e-04
GO:BP	GO:0002784	regulation of antimicrobial peptide production	8	8	1.237e-04
GO:BP	GO:0002443	leukocyte mediated immunity	133	461	1.239e-04
GO:BP	GO:0042531	positive regulation of tyrosine phosphorylation of STAT protein	29	63	1.296e-04
GO:BP	GO:0002385	mucosal immune response	21	39	1.355e-04
GO:BP	GO:0042119	neutrophil activation	22	42	1.433e-04
GO:BP	GO:0032689	negative regulation of type II interferon production	22	42	1.433e-04
GO:BP	GO:0002920	regulation of humoral immune response	23	45	1.480e-04
GO:BP	GO:0051249	regulation of lymphocyte activation	141	497	1.646e-04
GO:BP	GO:0071346	cellular response to type II interferon	47	125	1.725e-04
GO:BP	GO:0002286	T cell activation involved in immune response	47	125	1.725e-04
GO:BP	GO:0006805	xenobiotic metabolic process	47	125	1.725e-04
GO:BP	GO:0007204	positive regulation of cytosolic calcium ion concentration	59	169	1.783e-04
GO:BP	GO:0045026	plasma membrane fusion	19	34	1.852e-04
GO:BP	GO:1903037	regulation of leukocyte cell-cell adhesion	109	366	1.921e-04
GO:BP	GO:0042363	fat-soluble vitamin catabolic process	10	12	2.025e-04
GO:BP	GO:0046649	lymphocyte activation	208	787	2.146e-04
GO:BP	GO:0070665	positive regulation of leukocyte proliferation	57	163	2.373e-04
GO:BP	GO:0009584	detection of visible light	18	32	2.865e-04
GO:BP	GO:0010556	regulation of macromolecule biosynthetic process	1238	5633	2.971e-04
GO:BP	GO:0032722	positive regulation of chemokine production	31	72	3.070e-04
GO:BP	GO:0070374	positive regulation of ERK1 and ERK2 cascade	69	210	3.102e-04
GO:BP	GO:0032642	regulation of chemokine production	38	96	3.356e-04
GO:BP	GO:0032602	chemokine production	38	96	3.356e-04
GO:BP	GO:0002685	regulation of leukocyte migration	74	230	3.391e-04
GO:BP	GO:0050863	regulation of T cell activation	110	375	3.516e-04
GO:BP	GO:0050868	negative regulation of T cell activation	46	125	3.931e-04
GO:BP	GO:1903038	negative regulation of leukocyte cell-cell adhesion	49	136	3.991e-04
GO:BP	GO:0002695	negative regulation of leukocyte activation	62	185	4.263e-04
GO:BP	GO:0003341	cilium movement	69	212	4.284e-04
GO:BP	GO:0042110	T cell activation	153	558	4.571e-04
GO:BP	GO:0015670	carbon dioxide transport	11	15	5.153e-04
GO:BP	GO:0030855	epithelial cell differentiation	195	741	5.213e-04
GO:BP	GO:0002225	positive regulation of antimicrobial peptide production	7	7	5.269e-04
GO:BP	GO:0052697	xenobiotic glucuronidation	7	7	5.269e-04
GO:BP	GO:0019755	one-carbon compound transport	15	25	5.456e-04
GO:BP	GO:0042509	regulation of tyrosine phosphorylation of STAT protein	31	74	5.586e-04
GO:BP	GO:0032945	negative regulation of mononuclear cell proliferation	35	88	6.260e-04
GO:BP	GO:0042102	positive regulation of T cell proliferation	39	102	6.260e-04
GO:BP	GO:1904892	regulation of receptor signaling pathway via STAT	40	106	7.014e-04
GO:BP	GO:0046425	regulation of receptor signaling pathway via JAK-STAT	38	99	7.157e-04
GO:BP	GO:0002759	regulation of antimicrobial humoral response	9	11	7.523e-04
GO:BP	GO:0007189	adenylate cyclase-activating G protein-coupled receptor signaling pathway	54	158	7.761e-04
GO:BP	GO:0050671	positive regulation of lymphocyte proliferation	50	143	7.761e-04
GO:BP	GO:0070664	negative regulation of leukocyte proliferation	37	96	8.104e-04
GO:BP	GO:0030277	maintenance of gastrointestinal epithelium	14	23	8.118e-04
GO:BP	GO:0003006	developmental process involved in reproduction	257	1022	8.286e-04
GO:BP	GO:0032613	interleukin-10 production	26	59	8.894e-04
GO:BP	GO:0032653	regulation of interleukin-10 production	26	59	8.894e-04
GO:BP	GO:0007260	tyrosine phosphorylation of STAT protein	31	76	9.966e-04
GO:BP	GO:0032637	interleukin-8 production	33	83	1.030e-03
GO:BP	GO:0032677	regulation of interleukin-8 production	33	83	1.030e-03
GO:BP	GO:0032757	positive regulation of interleukin-8 production	27	63	1.130e-03
GO:BP	GO:0002673	regulation of acute inflammatory response	22	47	1.171e-03
GO:BP	GO:0050672	negative regulation of lymphocyte proliferation	34	87	1.182e-03
GO:BP	GO:0050482	arachidonate secretion	17	32	1.192e-03
GO:BP	GO:0006691	leukotriene metabolic process	17	32	1.192e-03
GO:BP	GO:1903963	arachidonate transport	17	32	1.192e-03
GO:BP	GO:0002687	positive regulation of leukocyte migration	52	153	1.220e-03
GO:BP	GO:0032946	positive regulation of mononuclear cell proliferation	50	146	1.361e-03
GO:BP	GO:0009889	regulation of biosynthetic process	1261	5795	1.384e-03
GO:BP	GO:0002705	positive regulation of leukocyte mediated immunity	50	147	1.653e-03
GO:BP	GO:0042098	T cell proliferation	67	213	1.665e-03
GO:BP	GO:0009111	vitamin catabolic process	10	14	1.665e-03
GO:BP	GO:0007602	phototransduction	22	48	1.679e-03
GO:BP	GO:0009583	detection of light stimulus	28	68	1.847e-03
GO:BP	GO:0071466	cellular response to xenobiotic stimulus	62	194	1.847e-03
GO:BP	GO:0048519	negative regulation of biological process	1273	5865	1.948e-03
GO:BP	GO:0007281	germ cell development	105	370	2.077e-03
GO:BP	GO:0051552	flavone metabolic process	6	6	2.251e-03
GO:BP	GO:1901317	regulation of flagellated sperm motility	13	22	2.251e-03
GO:BP	GO:0002786	regulation of antibacterial peptide production	6	6	2.251e-03
GO:BP	GO:0051673	disruption of plasma membrane integrity in another organism	6	6	2.251e-03
GO:BP	GO:0032655	regulation of interleukin-12 production	26	62	2.262e-03
GO:BP	GO:0032615	interleukin-12 production	26	62	2.262e-03
GO:BP	GO:0032735	positive regulation of interleukin-12 production	20	43	2.735e-03
GO:BP	GO:0002227	innate immune response in mucosa	15	28	2.833e-03
GO:BP	GO:0031343	positive regulation of cell killing	29	73	2.833e-03
GO:BP	GO:1902221	erythrose 4-phosphate/phosphoenolpyruvate family amino acid metabolic process	15	28	2.833e-03
GO:BP	GO:0060295	regulation of cilium movement involved in cell motility	16	31	2.946e-03
GO:BP	GO:1902019	regulation of cilium-dependent cell motility	16	31	2.946e-03
GO:BP	GO:0042113	B cell activation	83	282	2.979e-03
GO:BP	GO:0035036	sperm-egg recognition	23	53	3.039e-03
GO:BP	GO:0032760	positive regulation of tumor necrosis factor production	37	102	3.171e-03
GO:BP	GO:0031347	regulation of defense response	199	783	3.171e-03
GO:BP	GO:0050729	positive regulation of inflammatory response	49	147	3.178e-03
GO:BP	GO:0032101	regulation of response to external stimulus	263	1071	3.242e-03
GO:BP	GO:0002715	regulation of natural killer cell mediated immunity	22	50	3.287e-03
GO:BP	GO:0002544	chronic inflammatory response	12	20	3.327e-03
GO:BP	GO:0071347	cellular response to interleukin-1	38	106	3.346e-03
GO:BP	GO:1903557	positive regulation of tumor necrosis factor superfamily cytokine production	38	106	3.346e-03
GO:BP	GO:0032652	regulation of interleukin-1 production	39	110	3.566e-03
GO:BP	GO:0032612	interleukin-1 production	39	110	3.566e-03
GO:BP	GO:0001818	negative regulation of cytokine production	84	288	3.652e-03
GO:BP	GO:0050866	negative regulation of cell activation	64	207	3.794e-03
GO:BP	GO:0015669	gas transport	13	23	3.873e-03
GO:BP	GO:0032680	regulation of tumor necrosis factor production	53	164	4.006e-03
GO:BP	GO:0032733	positive regulation of interleukin-10 production	19	41	4.006e-03
GO:BP	GO:0032640	tumor necrosis factor production	53	164	4.006e-03
GO:BP	GO:0009072	aromatic amino acid metabolic process	19	41	4.006e-03
GO:BP	GO:0060259	regulation of feeding behavior	14	26	4.204e-03
GO:BP	GO:0042755	eating behavior	18	38	4.204e-03
GO:BP	GO:0002825	regulation of T-helper 1 type immune response	16	32	4.434e-03
GO:BP	GO:0009988	cell-cell recognition	29	75	4.561e-03
GO:BP	GO:0071345	cellular response to cytokine stimulus	211	843	4.722e-03
GO:BP	GO:0071706	tumor necrosis factor superfamily cytokine production	54	169	4.722e-03
GO:BP	GO:1903555	regulation of tumor necrosis factor superfamily cytokine production	54	169	4.722e-03
GO:BP	GO:0002698	negative regulation of immune effector process	41	120	5.800e-03
GO:BP	GO:0032103	positive regulation of response to external stimulus	160	619	5.831e-03
GO:BP	GO:0002228	natural killer cell mediated immunity	29	76	5.859e-03
GO:BP	GO:0006968	cellular defense response	22	52	6.103e-03
GO:BP	GO:0044058	regulation of digestive system process	18	39	6.143e-03
GO:BP	GO:0030183	B cell differentiation	51	159	6.256e-03
GO:BP	GO:0070555	response to interleukin-1	44	132	6.378e-03
GO:BP	GO:0050891	multicellular organismal-level water homeostasis	16	33	6.736e-03
GO:BP	GO:0042832	defense response to protozoan	14	27	6.782e-03
GO:BP	GO:0015671	oxygen transport	10	16	7.332e-03
GO:BP	GO:0007187	G protein-coupled receptor signaling pathway, coupled to cyclic nucleotide second messenger	23	56	7.332e-03
GO:BP	GO:0034374	low-density lipoprotein particle remodeling	10	16	7.332e-03
GO:BP	GO:0022407	regulation of cell-cell adhesion	127	478	7.559e-03
GO:BP	GO:0002444	myeloid leukocyte mediated immunity	39	114	7.636e-03
GO:BP	GO:0008037	cell recognition	50	157	8.438e-03
GO:BP	GO:0072678	T cell migration	28	74	8.473e-03
GO:BP	GO:0120254	olefinic compound metabolic process	51	161	8.473e-03
GO:BP	GO:0042436	indole-containing compound catabolic process	7	9	9.139e-03
GO:BP	GO:0006569	tryptophan catabolic process	7	9	9.139e-03
GO:BP	GO:0002275	myeloid cell activation involved in immune response	35	100	9.235e-03
GO:BP	GO:0002803	positive regulation of antibacterial peptide production	5	5	9.235e-03
GO:BP	GO:0009581	detection of external stimulus	46	142	9.235e-03
GO:BP	GO:0052696	flavonoid glucuronidation	5	5	9.235e-03
GO:BP	GO:0019369	arachidonate metabolic process	23	57	9.561e-03
GO:BP	GO:0002688	regulation of leukocyte chemotaxis	41	123	9.712e-03
GO:BP	GO:0030431	sleep	12	22	9.851e-03
GO:BP	GO:0032651	regulation of interleukin-1 beta production	33	93	9.917e-03
GO:BP	GO:0055078	sodium ion homeostasis	20	47	9.917e-03
GO:BP	GO:0032611	interleukin-1 beta production	33	93	9.917e-03
GO:BP	GO:0007198	adenylate cyclase-inhibiting serotonin receptor signaling pathway	6	7	1.046e-02
GO:BP	GO:0050795	regulation of behavior	28	75	1.046e-02
GO:BP	GO:0010273	detoxification of copper ion	9	14	1.054e-02
GO:BP	GO:0070942	neutrophil mediated cytotoxicity	9	14	1.054e-02
GO:BP	GO:0034116	positive regulation of heterotypic cell-cell adhesion	9	14	1.054e-02
GO:BP	GO:1990169	stress response to copper ion	9	14	1.054e-02
GO:BP	GO:0043330	response to exogenous dsRNA	21	51	1.193e-02
GO:BP	GO:0044706	multi-multicellular organism process	63	212	1.215e-02
GO:BP	GO:0001523	retinoid metabolic process	30	83	1.228e-02
GO:BP	GO:0032729	positive regulation of type II interferon production	28	76	1.312e-02
GO:BP	GO:0034097	response to cytokine	228	937	1.314e-02
GO:BP	GO:0006775	fat-soluble vitamin metabolic process	20	48	1.330e-02
GO:BP	GO:0008228	opsonization	10	17	1.330e-02
GO:BP	GO:0050766	positive regulation of phagocytosis	26	69	1.364e-02
GO:BP	GO:0002709	regulation of T cell mediated immunity	33	95	1.470e-02
GO:BP	GO:0002449	lymphocyte mediated immunity	98	361	1.513e-02
GO:BP	GO:0032661	regulation of interleukin-18 production	8	12	1.545e-02
GO:BP	GO:0018149	peptide cross-linking	14	29	1.545e-02
GO:BP	GO:0070943	neutrophil-mediated killing of symbiont cell	8	12	1.545e-02
GO:BP	GO:0032621	interleukin-18 production	8	12	1.545e-02
GO:BP	GO:0001912	positive regulation of leukocyte mediated cytotoxicity	25	66	1.549e-02
GO:BP	GO:0042445	hormone metabolic process	70	243	1.549e-02
GO:BP	GO:0098581	detection of external biotic stimulus	13	26	1.571e-02
GO:BP	GO:0016101	diterpenoid metabolic process	31	88	1.584e-02
GO:BP	GO:1901652	response to peptide	230	950	1.603e-02
GO:BP	GO:0042116	macrophage activation	36	107	1.629e-02
GO:BP	GO:0051607	defense response to virus	86	311	1.666e-02
GO:BP	GO:0031349	positive regulation of defense response	126	484	1.670e-02
GO:BP	GO:0044703	multi-organism reproductive process	60	203	1.791e-02
GO:BP	GO:0050867	positive regulation of cell activation	100	372	1.845e-02
GO:BP	GO:0042269	regulation of natural killer cell mediated cytotoxicity	19	46	1.967e-02
GO:BP	GO:0141005	transposable element silencing by heterochromatin formation	9	15	2.007e-02
GO:BP	GO:0002819	regulation of adaptive immune response	60	204	2.027e-02
GO:BP	GO:0010669	epithelial structure maintenance	15	33	2.106e-02
GO:BP	GO:0042573	retinoic acid metabolic process	15	33	2.106e-02
GO:BP	GO:0002700	regulation of production of molecular mediator of immune response	56	188	2.117e-02
GO:BP	GO:0008343	adult feeding behavior	7	10	2.169e-02
GO:BP	GO:0071947	protein deubiquitination involved in ubiquitin-dependent protein catabolic process	7	10	2.169e-02
GO:BP	GO:0035747	natural killer cell chemotaxis	7	10	2.169e-02
GO:BP	GO:0048523	negative regulation of cellular process	1209	5646	2.169e-02
GO:BP	GO:0001562	response to protozoan	14	30	2.230e-02
GO:BP	GO:0006869	lipid transport	113	431	2.256e-02
GO:BP	GO:0019373	epoxygenase P450 pathway	10	18	2.256e-02
GO:BP	GO:0046456	icosanoid biosynthetic process	22	57	2.269e-02
GO:BP	GO:0002675	positive regulation of acute inflammatory response	13	27	2.330e-02
GO:BP	GO:0002577	regulation of antigen processing and presentation	11	21	2.357e-02
GO:BP	GO:0002822	regulation of adaptive immune response based on somatic recombination of immune receptors built from immunoglobulin superfamily domains	56	189	2.357e-02
GO:BP	GO:0002523	leukocyte migration involved in inflammatory response	11	21	2.357e-02
GO:BP	GO:0022408	negative regulation of cell-cell adhesion	56	189	2.357e-02
GO:BP	GO:0009074	aromatic amino acid family catabolic process	12	24	2.367e-02
GO:BP	GO:0002708	positive regulation of lymphocyte mediated immunity	40	125	2.419e-02
GO:BP	GO:0009582	detection of abiotic stimulus	45	145	2.498e-02
GO:BP	GO:0042130	negative regulation of T cell proliferation	26	72	2.572e-02
GO:BP	GO:0010817	regulation of hormone levels	139	548	2.650e-02
GO:BP	GO:0002768	immune response-regulating cell surface receptor signaling pathway	90	334	2.845e-02
GO:BP	GO:0002690	positive regulation of leukocyte chemotaxis	32	95	2.859e-02
GO:BP	GO:0002701	negative regulation of production of molecular mediator of immune response	18	44	2.861e-02
GO:BP	GO:0032741	positive regulation of interleukin-18 production	6	8	2.932e-02
GO:BP	GO:0070268	cornification	6	8	2.932e-02
GO:BP	GO:2000501	regulation of natural killer cell chemotaxis	6	8	2.932e-02
GO:BP	GO:0060456	positive regulation of digestive system process	8	13	2.948e-02
GO:BP	GO:1900015	regulation of cytokine production involved in inflammatory response	23	62	3.141e-02
GO:BP	GO:0002534	cytokine production involved in inflammatory response	23	62	3.141e-02
GO:BP	GO:0042267	natural killer cell mediated cytotoxicity	26	73	3.153e-02
GO:BP	GO:0002683	negative regulation of immune system process	128	502	3.217e-02
GO:BP	GO:0060046	regulation of acrosome reaction	9	16	3.408e-02
GO:BP	GO:0002704	negative regulation of leukocyte mediated immunity	24	66	3.408e-02
GO:BP	GO:0035821	modulation of process of another organism	9	16	3.408e-02
GO:BP	GO:0072378	blood coagulation, fibrin clot formation	9	16	3.408e-02
GO:BP	GO:0051969	regulation of transmission of nerve impulse	9	16	3.408e-02
GO:BP	GO:0050878	regulation of body fluid levels	98	371	3.419e-02
GO:BP	GO:0042320	regulation of circadian sleep/wake cycle, REM sleep	4	4	3.485e-02
GO:BP	GO:0002325	natural killer cell differentiation involved in immune response	4	4	3.485e-02
GO:BP	GO:0048520	positive regulation of behavior	12	25	3.485e-02
GO:BP	GO:0042747	circadian sleep/wake cycle, REM sleep	4	4	3.485e-02
GO:BP	GO:0036101	leukotriene B4 catabolic process	4	4	3.485e-02
GO:BP	GO:0042430	indole-containing compound metabolic process	12	25	3.485e-02
GO:BP	GO:0042377	vitamin K catabolic process	4	4	3.485e-02
GO:BP	GO:0042376	phylloquinone catabolic process	4	4	3.485e-02
GO:BP	GO:0045938	positive regulation of circadian sleep/wake cycle, sleep	4	4	3.485e-02
GO:BP	GO:0042374	phylloquinone metabolic process	4	4	3.485e-02
GO:BP	GO:0036100	leukotriene catabolic process	5	6	3.485e-02
GO:BP	GO:0044278	disruption of cell wall in another organism	4	4	3.485e-02
GO:BP	GO:0097272	ammonium homeostasis	5	6	3.485e-02
GO:BP	GO:0034382	chylomicron remnant clearance	5	6	3.485e-02
GO:BP	GO:0097501	stress response to metal ion	10	19	3.485e-02
GO:BP	GO:0072376	protein activation cascade	10	19	3.485e-02
GO:BP	GO:0019370	leukotriene biosynthetic process	10	19	3.485e-02
GO:BP	GO:0098543	detection of other organism	10	19	3.485e-02
GO:BP	GO:0019805	quinolinate biosynthetic process	4	4	3.485e-02
GO:BP	GO:0035743	CD4-positive, alpha-beta T cell cytokine production	10	19	3.485e-02
GO:BP	GO:0060480	lung goblet cell differentiation	4	4	3.485e-02
GO:BP	GO:0032826	regulation of natural killer cell differentiation involved in immune response	4	4	3.485e-02
GO:BP	GO:0051464	positive regulation of cortisol secretion	4	4	3.485e-02
GO:BP	GO:0002827	positive regulation of T-helper 1 type immune response	10	19	3.485e-02
GO:BP	GO:2000851	positive regulation of glucocorticoid secretion	4	4	3.485e-02
GO:BP	GO:2000503	positive regulation of natural killer cell chemotaxis	5	6	3.485e-02
GO:BP	GO:0002456	T cell mediated immunity	39	124	3.533e-02
GO:BP	GO:0030098	lymphocyte differentiation	113	438	3.570e-02
GO:BP	GO:0140962	multicellular organismal-level chemical homeostasis	26	74	3.612e-02
GO:BP	GO:0002696	positive regulation of leukocyte activation	94	355	3.613e-02
GO:BP	GO:0034105	positive regulation of tissue remodeling	7	11	4.159e-02
GO:BP	GO:0021562	vestibulocochlear nerve development	7	11	4.159e-02
GO:BP	GO:0032372	negative regulation of sterol transport	7	11	4.159e-02
GO:BP	GO:0032375	negative regulation of cholesterol transport	7	11	4.159e-02
GO:BP	GO:1903027	regulation of opsonization	7	11	4.159e-02
GO:BP	GO:0070944	neutrophil-mediated killing of bacterium	7	11	4.159e-02
GO:BP	GO:0032732	positive regulation of interleukin-1 production	25	71	4.166e-02
GO:BP	GO:0032731	positive regulation of interleukin-1 beta production	22	60	4.209e-02
GO:BP	GO:0046942	carboxylic acid transport	91	344	4.277e-02
GO:BP	GO:0002440	production of molecular mediator of immune response	62	220	4.368e-02
GO:BP	GO:1903039	positive regulation of leukocyte cell-cell adhesion	74	271	4.404e-02
GO:BP	GO:0032814	regulation of natural killer cell activation	16	39	4.443e-02
GO:BP	GO:0006910	phagocytosis, recognition	13	29	4.443e-02
GO:BP	GO:0015849	organic acid transport	91	345	4.636e-02
GO:BP	GO:0022409	positive regulation of cell-cell adhesion	85	319	4.654e-02
GO:BP	GO:0002430	complement receptor mediated signaling pathway	8	14	4.950e-02
KEGG	KEGG:04740	Olfactory transduction	368	428	7.954e-184
KEGG	KEGG:04060	Cytokine-cytokine receptor interaction	148	291	9.354e-26
KEGG	KEGG:04080	Neuroactive ligand-receptor interaction	173	365	9.354e-26
KEGG	KEGG:05206	MicroRNAs in cancer	146	310	2.799e-21
KEGG	KEGG:05150	Staphylococcus aureus infection	58	86	1.424e-17
KEGG	KEGG:04061	Viral protein interaction with cytokine and cytokine receptor	59	98	1.828e-14
KEGG	KEGG:04742	Taste transduction	46	85	4.526e-09
KEGG	KEGG:05320	Autoimmune thyroid disease	32	49	4.526e-09
KEGG	KEGG:00830	Retinol metabolism	39	68	1.056e-08
KEGG	KEGG:00980	Metabolism of xenobiotics by cytochrome P450	38	74	1.027e-06
KEGG	KEGG:04640	Hematopoietic cell lineage	44	92	1.236e-06
KEGG	KEGG:05204	Chemical carcinogenesis - DNA adducts	35	67	1.708e-06
KEGG	KEGG:05310	Asthma	19	27	2.846e-06
KEGG	KEGG:04672	Intestinal immune network for IgA production	26	44	2.846e-06
KEGG	KEGG:00982	Drug metabolism - cytochrome P450	34	68	8.326e-06
KEGG	KEGG:05323	Rheumatoid arthritis	40	88	1.881e-05
KEGG	KEGG:00053	Ascorbate and aldarate metabolism	19	30	2.755e-05
KEGG	KEGG:04630	JAK-STAT signaling pathway	62	162	3.659e-05
KEGG	KEGG:05332	Graft-versus-host disease	21	37	8.608e-05
KEGG	KEGG:00591	Linoleic acid metabolism	18	30	1.351e-04
KEGG	KEGG:00590	Arachidonic acid metabolism	29	61	1.530e-04
KEGG	KEGG:04976	Bile secretion	38	89	1.598e-04
KEGG	KEGG:05322	Systemic lupus erythematosus	51	132	1.676e-04
KEGG	KEGG:00140	Steroid hormone biosynthesis	29	62	1.909e-04
KEGG	KEGG:05321	Inflammatory bowel disease	29	62	1.909e-04
KEGG	KEGG:05144	Malaria	24	49	3.872e-04
KEGG	KEGG:00040	Pentose and glucuronate interconversions	19	36	6.806e-04
KEGG	KEGG:05330	Allograft rejection	18	34	9.773e-04
KEGG	KEGG:00592	alpha-Linolenic acid metabolism	15	26	1.019e-03
KEGG	KEGG:04650	Natural killer cell mediated cytotoxicity	45	124	2.337e-03
KEGG	KEGG:04975	Fat digestion and absorption	20	43	3.383e-03
KEGG	KEGG:04940	Type I diabetes mellitus	19	40	3.383e-03
KEGG	KEGG:05340	Primary immunodeficiency	18	37	3.383e-03
KEGG	KEGG:05164	Influenza A	56	167	4.074e-03
KEGG	KEGG:04610	Complement and coagulation cascades	33	86	4.297e-03
KEGG	KEGG:05152	Tuberculosis	58	175	4.297e-03
KEGG	KEGG:05143	African trypanosomiasis	17	36	6.533e-03
KEGG	KEGG:00350	Tyrosine metabolism	17	36	6.533e-03
KEGG	KEGG:04514	Cell adhesion molecules	51	153	7.350e-03
KEGG	KEGG:00983	Drug metabolism - other enzymes	30	79	8.217e-03
KEGG	KEGG:00860	Porphyrin metabolism	19	43	8.340e-03
KEGG	KEGG:04620	Toll-like receptor signaling pathway	37	106	1.339e-02
KEGG	KEGG:04972	Pancreatic secretion	35	102	2.385e-02
KEGG	KEGG:04950	Maturity onset diabetes of the young	12	26	4.247e-02

#write.csv(tableNR, "output/table_NRmotif.csv")

#GO:BP
tableNR_GOBP_pp <- tableNR_pp %>% 
  dplyr::filter(source=="GO:BP") %>% 
  dplyr::select(p_value, term_name, intersection_size) %>% 
  dplyr::slice_min(., n=10, order_by=p_value) %>% 
  mutate(log_val = -log10(p_value))

#saveRDS(tableNR_GOBP_pp, "data/tableNR_GOBP_postprob.RDS")

tableNR_GOBP_pp %>% ggplot(., aes(x = log_val, y = reorder(term_name, p_value), col= intersection_size)) +
  geom_point(aes(size = intersection_size)) +
  ggtitle("No Response Enriched GO:BP Terms")+
  xlab(expression("-log"[10]~"p-value"))+
  guides(col="none", size= guide_legend(title = "# of intersected \n terms"))+
  ylab("GO:BP term")+
  scale_y_discrete(labels = scales::label_wrap(30))+
  theme_bw()+
  theme(plot.title = element_text(size = rel(1.5), hjust = 0.5),
        axis.title = element_text(size = 15, colour = "black"),
        axis.ticks = element_line(linewidth = 1.5),
        axis.line = element_line(linewidth = 1.5),
        axis.text = element_text(size = 10, colour = "black", angle = 0),
        strip.text = element_text(size = 15, colour = "black", face = "bold"))

Past versions of "No Response Motif Genes Post Prob-2.png"

Version	Author	Date
ff644ec	emmapfort	2025-04-18
cee6b3d	emmapfort	2025-04-18
84d5599	emmapfort	2025-04-14

#KEGG
tableNR_KEGG_pp <- tableNR_pp %>% 
  dplyr::filter(source=="KEGG") %>% 
  dplyr::select(p_value, term_name, intersection_size) %>% 
  dplyr::slice_min(., n=10, order_by=p_value) %>% 
  mutate(log_val = -log10(p_value))

tableNR_KEGG_pp %>% ggplot(., aes(x = log_val, y = reorder(term_name, p_value), col= intersection_size)) +
  geom_point(aes(size = intersection_size)) +
  ggtitle("No Response Enriched KEGG Terms")+
  xlab(expression("-log"[10]~"p-value"))+
  guides(col="none", size= guide_legend(title = "# of intersected \n terms"))+
  ylab("KEGG term")+
  scale_y_discrete(labels = scales::label_wrap(30))+
  theme_bw()+
  theme(plot.title = element_text(size = rel(1.5), hjust = 0.5),
        axis.title = element_text(size = 15, colour = "black"),
        axis.ticks = element_line(linewidth = 1.5),
        axis.line = element_line(linewidth = 1.5),
        axis.text = element_text(size = 10, colour = "black", angle = 0),
        strip.text = element_text(size = 15, colour = "black", face = "bold"))

Past versions of "No Response Motif Genes Post Prob-3.png"

Version	Author	Date
ff644ec	emmapfort	2025-04-18
cee6b3d	emmapfort	2025-04-18
84d5599	emmapfort	2025-04-14

The Acute Response had no genes pop up for clustlike at the cutoff of > 0.5 However, when we changed the cutoff and used post prob we got some genes, so let’s use them for GO analysis This is from motif 2, where there is a light gray box in the first study (DOX 24hr) This one doesn’t seem to work, most likely since it’s not really picking up a motif

Next, we’ll look at the Late Response (motif 3)

motif_LD_d <- clust3_d


LDmotif_genes_d <- gost(query = motif_LD_d,
                      organism = "hsapiens",
                      ordered_query = FALSE,
                      measure_underrepresentation = FALSE,
                      evcodes = FALSE,
                      user_threshold = 0.05,
                      correction_method = c("fdr"),
                      sources = c("GO:BP", "KEGG"))

cormotifLDclust_d <- gostplot(LDmotif_genes_d, capped = FALSE, interactive = TRUE)
cormotifLDclust_d

tableLD_d <- LDmotif_genes_d$result %>% 
  dplyr::select(c(source, term_id, term_name, intersection_size, term_size, p_value))

tableLD_d %>% 
  mutate_at(.vars = 6, .funs = scales::label_scientific(digits=4)) %>% 
  kableExtra::kable(.,) %>% 
  kableExtra::kable_paper("striped", full_width = FALSE) %>% 
  kableExtra::kable_styling(full_width = FALSE, position = "left", bootstrap_options = c("striped", "hover")) %>% 
  kableExtra::scroll_box(width = "100%", height = "400px")

source	term_id	term_name	intersection_size	term_size	p_value
GO:BP	GO:0006811	monoatomic ion transport	76	1256	1.859e-16
GO:BP	GO:0034220	monoatomic ion transmembrane transport	66	1017	1.150e-15
GO:BP	GO:0055085	transmembrane transport	81	1538	1.275e-14
GO:BP	GO:0098660	inorganic ion transmembrane transport	59	903	4.056e-14
GO:BP	GO:0015698	inorganic anion transport	25	165	6.202e-13
GO:BP	GO:0006820	monoatomic anion transport	25	167	6.916e-13
GO:BP	GO:0006821	chloride transport	20	122	8.036e-11
GO:BP	GO:0098661	inorganic anion transmembrane transport	20	127	1.544e-10
GO:BP	GO:0006812	monoatomic cation transport	56	1032	3.213e-10
GO:BP	GO:0030001	metal ion transport	50	875	8.778e-10
GO:BP	GO:0098656	monoatomic anion transmembrane transport	20	142	9.669e-10
GO:BP	GO:1902476	chloride transmembrane transport	17	107	5.174e-09
GO:BP	GO:0098655	monoatomic cation transmembrane transport	47	832	5.174e-09
GO:BP	GO:0006810	transport	137	4341	8.659e-09
GO:BP	GO:0050896	response to stimulus	229	8993	7.328e-08
GO:BP	GO:0098662	inorganic cation transmembrane transport	44	811	7.328e-08
GO:BP	GO:0048869	cellular developmental process	133	4382	2.366e-07
GO:BP	GO:0030154	cell differentiation	133	4381	2.366e-07
GO:BP	GO:0032502	developmental process	177	6478	3.165e-07
GO:BP	GO:0032501	multicellular organismal process	191	7234	6.618e-07
GO:BP	GO:0051234	establishment of localization	140	4869	2.283e-06
GO:BP	GO:0048468	cell development	94	2833	2.327e-06
GO:BP	GO:0065008	regulation of biological quality	94	2847	2.843e-06
GO:BP	GO:0035725	sodium ion transmembrane transport	17	169	3.857e-06
GO:BP	GO:0007267	cell-cell signaling	54	1316	7.714e-06
GO:BP	GO:0007188	adenylate cyclase-modulating G protein-coupled receptor signaling pathway	20	248	8.700e-06
GO:BP	GO:0006814	sodium ion transport	19	235	1.747e-05
GO:BP	GO:0048856	anatomical structure development	158	5924	2.143e-05
GO:BP	GO:0030003	intracellular monoatomic cation homeostasis	29	521	3.048e-05
GO:BP	GO:0007193	adenylate cyclase-inhibiting G protein-coupled receptor signaling pathway	11	79	3.777e-05
GO:BP	GO:0006873	intracellular monoatomic ion homeostasis	29	530	4.076e-05
GO:BP	GO:0051179	localization	148	5521	4.773e-05
GO:BP	GO:0055080	monoatomic cation homeostasis	31	598	4.781e-05
GO:BP	GO:0002521	leukocyte differentiation	32	632	5.022e-05
GO:BP	GO:0050801	monoatomic ion homeostasis	31	608	6.443e-05
GO:BP	GO:0006813	potassium ion transport	18	238	7.650e-05
GO:BP	GO:0098771	inorganic ion homeostasis	28	531	1.150e-04
GO:BP	GO:0055074	calcium ion homeostasis	21	326	1.192e-04
GO:BP	GO:0015711	organic anion transport	25	442	1.210e-04
GO:BP	GO:0006874	intracellular calcium ion homeostasis	20	302	1.341e-04
GO:BP	GO:0023052	signaling	165	6471	1.385e-04
GO:BP	GO:0065007	biological regulation	281	12671	1.491e-04
GO:BP	GO:0002429	immune response-activating cell surface receptor signaling pathway	20	306	1.529e-04
GO:BP	GO:0007154	cell communication	165	6496	1.673e-04
GO:BP	GO:0099536	synaptic signaling	35	783	1.918e-04
GO:BP	GO:0050877	nervous system process	54	1489	2.051e-04
GO:BP	GO:0055082	intracellular chemical homeostasis	33	723	2.347e-04
GO:BP	GO:0007155	cell adhesion	54	1511	3.030e-04
GO:BP	GO:0042592	homeostatic process	59	1711	3.030e-04
GO:BP	GO:0050851	antigen receptor-mediated signaling pathway	15	192	3.228e-04
GO:BP	GO:0048878	chemical homeostasis	41	1026	3.612e-04
GO:BP	GO:0002768	immune response-regulating cell surface receptor signaling pathway	20	334	4.779e-04
GO:BP	GO:0048232	male gamete generation	30	654	5.513e-04
GO:BP	GO:0099537	trans-synaptic signaling	33	759	5.699e-04
GO:BP	GO:0022414	reproductive process	54	1556	6.223e-04
GO:BP	GO:0050957	equilibrioception	4	8	6.636e-04
GO:BP	GO:0071805	potassium ion transmembrane transport	15	213	9.978e-04
GO:BP	GO:0051480	regulation of cytosolic calcium ion concentration	8	59	1.073e-03
GO:BP	GO:0098916	anterograde trans-synaptic signaling	32	753	1.104e-03
GO:BP	GO:0007186	G protein-coupled receptor signaling pathway	46	1275	1.104e-03
GO:BP	GO:0007268	chemical synaptic transmission	32	753	1.104e-03
GO:BP	GO:0019725	cellular homeostasis	34	826	1.131e-03
GO:BP	GO:0009605	response to external stimulus	72	2367	1.429e-03
GO:BP	GO:0003006	developmental process involved in reproduction	39	1022	1.436e-03
GO:BP	GO:0098609	cell-cell adhesion	37	948	1.439e-03
GO:BP	GO:0010951	negative regulation of endopeptidase activity	6	31	1.439e-03
GO:BP	GO:0051716	cellular response to stimulus	176	7320	1.444e-03
GO:BP	GO:0007275	multicellular organism development	122	4658	1.472e-03
GO:BP	GO:1903131	mononuclear cell differentiation	25	529	1.557e-03
GO:BP	GO:0006816	calcium ion transport	22	433	1.614e-03
GO:BP	GO:0009410	response to xenobiotic stimulus	22	436	1.767e-03
GO:BP	GO:0007283	spermatogenesis	28	637	1.793e-03
GO:BP	GO:0048731	system development	107	3985	1.988e-03
GO:BP	GO:0015747	urate transport	4	11	2.264e-03
GO:BP	GO:0042221	response to chemical	104	3867	2.455e-03
GO:BP	GO:0010817	regulation of hormone levels	25	548	2.522e-03
GO:BP	GO:1902105	regulation of leukocyte differentiation	18	325	2.672e-03
GO:BP	GO:0006968	cellular defense response	7	52	2.928e-03
GO:BP	GO:0050853	B cell receptor signaling pathway	8	71	3.113e-03
GO:BP	GO:1901700	response to oxygen-containing compound	53	1632	3.186e-03
GO:BP	GO:0060004	reflex	5	23	3.275e-03
GO:BP	GO:0007200	phospholipase C-activating G protein-coupled receptor signaling pathway	10	116	3.665e-03
GO:BP	GO:0019722	calcium-mediated signaling	14	218	3.665e-03
GO:BP	GO:0050805	negative regulation of synaptic transmission	7	55	3.931e-03
GO:BP	GO:0060348	bone development	14	220	3.948e-03
GO:BP	GO:0009581	detection of external stimulus	11	142	4.080e-03
GO:BP	GO:0030098	lymphocyte differentiation	21	438	4.545e-03
GO:BP	GO:0030217	T cell differentiation	17	312	4.635e-03
GO:BP	GO:0009582	detection of abiotic stimulus	11	145	4.761e-03
GO:BP	GO:0140013	meiotic nuclear division	13	198	4.891e-03
GO:BP	GO:0002253	activation of immune response	24	543	4.891e-03
GO:BP	GO:0002757	immune response-activating signaling pathway	22	477	5.142e-03
GO:BP	GO:0019953	sexual reproduction	39	1103	5.143e-03
GO:BP	GO:0060078	regulation of postsynaptic membrane potential	11	148	5.417e-03
GO:BP	GO:0007600	sensory perception	35	955	5.823e-03
GO:BP	GO:0007610	behavior	27	665	6.963e-03
GO:BP	GO:0042110	T cell activation	24	558	6.963e-03
GO:BP	GO:0050789	regulation of biological process	264	12278	7.266e-03
GO:BP	GO:0006817	phosphate ion transport	5	28	7.266e-03
GO:BP	GO:0046631	alpha-beta T cell activation	12	181	7.448e-03
GO:BP	GO:0003008	system process	66	2266	7.662e-03
GO:BP	GO:0007276	gamete generation	31	822	8.125e-03
GO:BP	GO:0010466	negative regulation of peptidase activity	6	45	8.188e-03
GO:BP	GO:0006869	lipid transport	20	431	8.627e-03
GO:BP	GO:0048609	multicellular organismal reproductive process	35	980	8.638e-03
GO:BP	GO:0042391	regulation of membrane potential	20	433	8.859e-03
GO:BP	GO:0042445	hormone metabolic process	14	243	8.859e-03
GO:BP	GO:0021879	forebrain neuron differentiation	6	46	8.859e-03
GO:BP	GO:0002366	leukocyte activation involved in immune response	16	305	9.166e-03
GO:BP	GO:0045588	positive regulation of gamma-delta T cell differentiation	3	7	9.166e-03
GO:BP	GO:0002764	immune response-regulating signaling pathway	22	504	9.211e-03
GO:BP	GO:0014070	response to organic cyclic compound	33	909	9.211e-03
GO:BP	GO:1902107	positive regulation of leukocyte differentiation	12	189	9.684e-03
GO:BP	GO:1903708	positive regulation of hemopoiesis	12	189	9.684e-03
GO:BP	GO:0070588	calcium ion transmembrane transport	17	339	9.684e-03
GO:BP	GO:0002263	cell activation involved in immune response	16	309	1.006e-02
GO:BP	GO:0050870	positive regulation of T cell activation	14	248	1.008e-02
GO:BP	GO:0007601	visual perception	13	219	1.008e-02
GO:BP	GO:0035249	synaptic transmission, glutamatergic	9	112	1.008e-02
GO:BP	GO:1903046	meiotic cell cycle process	13	220	1.045e-02
GO:BP	GO:0098657	import into cell	33	921	1.071e-02
GO:BP	GO:0046942	carboxylic acid transport	17	344	1.071e-02
GO:BP	GO:0002923	regulation of humoral immune response mediated by circulating immunoglobulin	4	18	1.086e-02
GO:BP	GO:0050852	T cell receptor signaling pathway	10	139	1.086e-02
GO:BP	GO:0032604	granulocyte macrophage colony-stimulating factor production	4	18	1.086e-02
GO:BP	GO:0032645	regulation of granulocyte macrophage colony-stimulating factor production	4	18	1.086e-02
GO:BP	GO:0050953	sensory perception of light stimulus	13	222	1.086e-02
GO:BP	GO:0015849	organic acid transport	17	345	1.086e-02
GO:BP	GO:0050778	positive regulation of immune response	28	732	1.086e-02
GO:BP	GO:0008283	cell population proliferation	59	2009	1.123e-02
GO:BP	GO:0021630	olfactory nerve maturation	2	2	1.163e-02
GO:BP	GO:0009628	response to abiotic stimulus	38	1130	1.163e-02
GO:BP	GO:0036368	cone photoresponse recovery	2	2	1.163e-02
GO:BP	GO:0015913	short-chain fatty acid transmembrane transport	2	2	1.163e-02
GO:BP	GO:0030573	bile acid catabolic process	2	2	1.163e-02
GO:BP	GO:0046645	positive regulation of gamma-delta T cell activation	3	8	1.163e-02
GO:BP	GO:0048513	animal organ development	82	3047	1.163e-02
GO:BP	GO:0030097	hemopoiesis	34	971	1.163e-02
GO:BP	GO:0015741	fumarate transport	2	2	1.163e-02
GO:BP	GO:2000471	regulation of hematopoietic stem cell migration	2	2	1.163e-02
GO:BP	GO:2000473	positive regulation of hematopoietic stem cell migration	2	2	1.163e-02
GO:BP	GO:0045055	regulated exocytosis	13	229	1.290e-02
GO:BP	GO:0001775	cell activation	37	1098	1.290e-02
GO:BP	GO:0045582	positive regulation of T cell differentiation	9	119	1.295e-02
GO:BP	GO:0042127	regulation of cell population proliferation	51	1682	1.295e-02
GO:BP	GO:0046649	lymphocyte activation	29	787	1.338e-02
GO:BP	GO:0051321	meiotic cell cycle	15	294	1.437e-02
GO:BP	GO:0007165	signal transduction	142	5979	1.448e-02
GO:BP	GO:0070372	regulation of ERK1 and ERK2 cascade	15	295	1.469e-02
GO:BP	GO:0048518	positive regulation of biological process	147	6235	1.486e-02
GO:BP	GO:0006909	phagocytosis	13	234	1.500e-02
GO:BP	GO:0045321	leukocyte activation	33	951	1.511e-02
GO:BP	GO:0030450	regulation of complement activation, classical pathway	3	9	1.527e-02
GO:BP	GO:0045586	regulation of gamma-delta T cell differentiation	3	9	1.527e-02
GO:BP	GO:0040020	regulation of meiotic nuclear division	5	36	1.571e-02
GO:BP	GO:0002683	negative regulation of immune system process	21	502	1.599e-02
GO:BP	GO:0050982	detection of mechanical stimulus	6	55	1.625e-02
GO:BP	GO:0007140	male meiotic nuclear division	6	55	1.625e-02
GO:BP	GO:0009653	anatomical structure morphogenesis	73	2692	1.769e-02
GO:BP	GO:0021872	forebrain generation of neurons	6	56	1.769e-02
GO:BP	GO:1903039	positive regulation of leukocyte cell-cell adhesion	14	271	1.784e-02
GO:BP	GO:0048871	multicellular organismal-level homeostasis	29	809	1.871e-02
GO:BP	GO:0048485	sympathetic nervous system development	4	22	1.902e-02
GO:BP	GO:0046903	secretion	33	968	1.902e-02
GO:BP	GO:0046629	gamma-delta T cell activation	4	22	1.902e-02
GO:BP	GO:0141124	intracellular signaling cassette	55	1895	1.902e-02
GO:BP	GO:0071695	anatomical structure maturation	14	274	1.915e-02
GO:BP	GO:2001204	regulation of osteoclast development	3	10	1.960e-02
GO:BP	GO:0046643	regulation of gamma-delta T cell activation	3	10	1.960e-02
GO:BP	GO:0007166	cell surface receptor signaling pathway	75	2803	2.028e-02
GO:BP	GO:0010876	lipid localization	20	480	2.066e-02
GO:BP	GO:0050776	regulation of immune response	31	897	2.110e-02
GO:BP	GO:0002064	epithelial cell development	12	217	2.226e-02
GO:BP	GO:0098742	cell-cell adhesion via plasma-membrane adhesion molecules	14	280	2.269e-02
GO:BP	GO:0007127	meiosis I	9	132	2.275e-02
GO:BP	GO:0051932	synaptic transmission, GABAergic	6	60	2.330e-02
GO:BP	GO:0010481	epidermal cell division	2	3	2.428e-02
GO:BP	GO:0009888	tissue development	57	2012	2.428e-02
GO:BP	GO:0015850	organic hydroxy compound transport	14	283	2.428e-02
GO:BP	GO:0070543	response to linoleic acid	2	3	2.428e-02
GO:BP	GO:1903706	regulation of hemopoiesis	18	420	2.428e-02
GO:BP	GO:0071486	cellular response to high light intensity	2	3	2.428e-02
GO:BP	GO:1903306	negative regulation of regulated secretory pathway	4	24	2.428e-02
GO:BP	GO:0015912	short-chain fatty acid transport	2	3	2.428e-02
GO:BP	GO:0006959	humoral immune response	13	254	2.428e-02
GO:BP	GO:0070371	ERK1 and ERK2 cascade	15	318	2.428e-02
GO:BP	GO:0010482	regulation of epidermal cell division	2	3	2.428e-02
GO:BP	GO:0050954	sensory perception of mechanical stimulus	11	190	2.428e-02
GO:BP	GO:0021605	cranial nerve maturation	2	3	2.428e-02
GO:BP	GO:0072313	metanephric glomerular epithelial cell development	2	3	2.428e-02
GO:BP	GO:0032663	regulation of interleukin-2 production	6	62	2.428e-02
GO:BP	GO:0032623	interleukin-2 production	6	62	2.428e-02
GO:BP	GO:0045621	positive regulation of lymphocyte differentiation	9	134	2.428e-02
GO:BP	GO:0072312	metanephric glomerular epithelial cell differentiation	2	3	2.428e-02
GO:BP	GO:0072249	metanephric podocyte development	2	3	2.428e-02
GO:BP	GO:0072248	metanephric podocyte differentiation	2	3	2.428e-02
GO:BP	GO:0072244	metanephric glomerular epithelium development	2	3	2.428e-02
GO:BP	GO:0033563	dorsal/ventral axon guidance	2	3	2.428e-02
GO:BP	GO:1903977	positive regulation of glial cell migration	3	11	2.428e-02
GO:BP	GO:0006311	meiotic gene conversion	2	3	2.428e-02
GO:BP	GO:0048522	positive regulation of cellular process	138	5886	2.428e-02
GO:BP	GO:0009887	animal organ morphogenesis	34	1037	2.505e-02
GO:BP	GO:0043408	regulation of MAPK cascade	24	645	2.620e-02
GO:BP	GO:0007605	sensory perception of sound	10	166	2.660e-02
GO:BP	GO:0001501	skeletal system development	21	536	2.785e-02
GO:BP	GO:0044341	sodium-dependent phosphate transport	3	12	2.867e-02
GO:BP	GO:0043410	positive regulation of MAPK cascade	19	465	2.882e-02
GO:BP	GO:0021895	cerebral cortex neuron differentiation	4	26	2.925e-02
GO:BP	GO:0045494	photoreceptor cell maintenance	5	44	2.972e-02
GO:BP	GO:0050794	regulation of cellular process	251	11876	2.996e-02
GO:BP	GO:0061982	meiosis I cell cycle process	9	141	3.006e-02
GO:BP	GO:0009266	response to temperature stimulus	10	170	3.063e-02
GO:BP	GO:0035270	endocrine system development	9	142	3.128e-02
GO:BP	GO:0046634	regulation of alpha-beta T cell activation	8	115	3.144e-02
GO:BP	GO:0002704	negative regulation of leukocyte mediated immunity	6	66	3.152e-02
GO:BP	GO:0001894	tissue homeostasis	13	264	3.164e-02
GO:BP	GO:0060249	anatomical structure homeostasis	13	264	3.164e-02
GO:BP	GO:0007263	nitric oxide mediated signal transduction	4	27	3.228e-02
GO:BP	GO:0021953	central nervous system neuron differentiation	11	203	3.372e-02
GO:BP	GO:0043383	negative T cell selection	3	13	3.411e-02
GO:BP	GO:0043301	negative regulation of leukocyte degranulation	3	13	3.411e-02
GO:BP	GO:0042492	gamma-delta T cell differentiation	3	13	3.411e-02
GO:BP	GO:0051446	positive regulation of meiotic cell cycle	4	28	3.628e-02
GO:BP	GO:0050867	positive regulation of cell activation	16	372	3.730e-02
GO:BP	GO:0046633	alpha-beta T cell proliferation	5	47	3.730e-02
GO:BP	GO:0050848	regulation of calcium-mediated signaling	7	93	3.730e-02
GO:BP	GO:0014074	response to purine-containing compound	9	147	3.730e-02
GO:BP	GO:0051445	regulation of meiotic cell cycle	6	69	3.736e-02
GO:BP	GO:0045597	positive regulation of cell differentiation	29	866	3.736e-02
GO:BP	GO:2001205	negative regulation of osteoclast development	2	4	3.794e-02
GO:BP	GO:0141006	transposable element silencing by piRNA-mediated heterochromatin formation	2	4	3.794e-02
GO:BP	GO:1903942	positive regulation of respiratory gaseous exchange	2	4	3.794e-02
GO:BP	GO:0140966	piRNA-mediated heterochromatin formation	2	4	3.794e-02
GO:BP	GO:0071639	positive regulation of monocyte chemotactic protein-1 production	3	14	3.794e-02
GO:BP	GO:1990834	response to odorant	2	4	3.794e-02
GO:BP	GO:0000165	MAPK cascade	26	749	3.794e-02
GO:BP	GO:0042475	odontogenesis of dentin-containing tooth	7	95	3.794e-02
GO:BP	GO:0042403	thyroid hormone metabolic process	4	29	3.794e-02
GO:BP	GO:0010520	regulation of reciprocal meiotic recombination	2	4	3.794e-02
GO:BP	GO:0035822	gene conversion	2	4	3.794e-02
GO:BP	GO:0035589	G protein-coupled purinergic nucleotide receptor signaling pathway	3	14	3.794e-02
GO:BP	GO:0045728	respiratory burst after phagocytosis	2	4	3.794e-02
GO:BP	GO:0046305	alkanesulfonate biosynthetic process	2	4	3.794e-02
GO:BP	GO:0046352	disaccharide catabolic process	2	4	3.794e-02
GO:BP	GO:0007214	gamma-aminobutyric acid signaling pathway	4	29	3.794e-02
GO:BP	GO:0042412	taurine biosynthetic process	2	4	3.794e-02
GO:BP	GO:0048562	embryonic organ morphogenesis	14	305	3.794e-02
GO:BP	GO:0048806	genitalia development	5	48	3.794e-02
GO:BP	GO:0048870	cell motility	49	1716	3.794e-02
GO:BP	GO:0021682	nerve maturation	2	4	3.794e-02
GO:BP	GO:0010845	positive regulation of reciprocal meiotic recombination	2	4	3.794e-02
GO:BP	GO:0060117	auditory receptor cell development	4	29	3.794e-02
GO:BP	GO:0043266	regulation of potassium ion transport	7	94	3.794e-02
GO:BP	GO:0021700	developmental maturation	15	343	3.902e-02
GO:BP	GO:0002703	regulation of leukocyte mediated immunity	12	243	3.953e-02
GO:BP	GO:0008277	regulation of G protein-coupled receptor signaling pathway	9	151	3.974e-02
GO:BP	GO:0009566	fertilization	11	212	4.027e-02
GO:BP	GO:0003341	cilium movement	11	212	4.027e-02
GO:BP	GO:1904888	cranial skeletal system development	6	72	4.099e-02
GO:BP	GO:0002706	regulation of lymphocyte mediated immunity	10	182	4.121e-02
GO:BP	GO:0050764	regulation of phagocytosis	7	97	4.121e-02
GO:BP	GO:0030900	forebrain development	17	417	4.129e-02
GO:BP	GO:0006911	phagocytosis, engulfment	5	50	4.206e-02
GO:BP	GO:0045580	regulation of T cell differentiation	10	183	4.216e-02
GO:BP	GO:1903530	regulation of secretion by cell	21	567	4.216e-02
GO:BP	GO:0007626	locomotory behavior	11	214	4.216e-02
GO:BP	GO:0070887	cellular response to chemical stimulus	59	2186	4.216e-02
GO:BP	GO:0046635	positive regulation of alpha-beta T cell activation	6	73	4.231e-02
GO:BP	GO:0051239	regulation of multicellular organismal process	75	2928	4.231e-02
GO:BP	GO:0045471	response to ethanol	8	125	4.231e-02
GO:BP	GO:0023061	signal release	19	493	4.260e-02
GO:BP	GO:0045619	regulation of lymphocyte differentiation	11	215	4.260e-02
GO:BP	GO:0006955	immune response	55	2008	4.263e-02
GO:BP	GO:1902358	sulfate transmembrane transport	3	15	4.277e-02
GO:BP	GO:1901698	response to nitrogen compound	32	1010	4.350e-02
GO:BP	GO:0002065	columnar/cuboidal epithelial cell differentiation	8	126	4.350e-02
GO:BP	GO:0051346	negative regulation of hydrolase activity	7	99	4.350e-02
GO:BP	GO:0046632	alpha-beta T cell differentiation	8	128	4.751e-02
GO:BP	GO:0022409	positive regulation of cell-cell adhesion	14	319	4.770e-02
GO:BP	GO:0001906	cell killing	11	219	4.770e-02
GO:BP	GO:0060429	epithelium development	37	1229	4.838e-02
GO:BP	GO:0002696	positive regulation of leukocyte activation	15	355	4.871e-02
GO:BP	GO:0007189	adenylate cyclase-activating G protein-coupled receptor signaling pathway	9	158	4.881e-02
GO:BP	GO:0006957	complement activation, alternative pathway	3	16	4.947e-02
GO:BP	GO:0007194	negative regulation of adenylate cyclase activity	3	16	4.947e-02
GO:BP	GO:0061101	neuroendocrine cell differentiation	3	16	4.947e-02
GO:BP	GO:0043374	CD8-positive, alpha-beta T cell differentiation	3	16	4.947e-02
GO:BP	GO:0042102	positive regulation of T cell proliferation	7	102	4.947e-02
GO:BP	GO:0030183	B cell differentiation	9	159	4.985e-02
KEGG	KEGG:04080	Neuroactive ligand-receptor interaction	29	365	1.040e-06
KEGG	KEGG:00430	Taurine and hypotaurine metabolism	5	16	2.720e-03

#write.csv(tableLD, "output/table_LateDOXmotif.csv")

#GO:BP
tableLD_GOBP_d <- tableLD_d %>% 
  dplyr::filter(source=="GO:BP") %>% 
  dplyr::select(p_value, term_name, intersection_size) %>% 
  dplyr::slice_min(., n=10, order_by=p_value) %>% 
  mutate(log_val = -log10(p_value))

#saveRDS(tableLD_GOBP, "data/tableLD_GOBP.RDS")

tableLD_GOBP_d %>% ggplot(., aes(x = log_val, y = reorder(term_name, p_value), col= intersection_size)) +
  geom_point(aes(size = intersection_size)) +
  ggtitle("Late Response Enriched GO:BP Terms")+
  xlab(expression("-log"[10]~"p-value"))+
  guides(col="none", size= guide_legend(title = "# of intersected \n terms"))+
  ylab("GO:BP term")+
  scale_y_discrete(labels = scales::label_wrap(30))+
  theme_bw()+
  theme(plot.title = element_text(size = rel(1.5), hjust = 0.5),
        axis.title = element_text(size = 15, colour = "black"),
        axis.ticks = element_line(linewidth = 1.5),
        axis.line = element_line(linewidth = 1.5),
        axis.text = element_text(size = 10, colour = "black", angle = 0),
        strip.text = element_text(size = 15, colour = "black", face = "bold"))

Past versions of "Late DOX Response Motif Genes-2.png"

Version	Author	Date
ff644ec	emmapfort	2025-04-18
cee6b3d	emmapfort	2025-04-18
84d5599	emmapfort	2025-04-14

#KEGG
tableLD_KEGG_d <- tableLD_d %>% 
  dplyr::filter(source=="KEGG") %>% 
  dplyr::select(p_value, term_name, intersection_size) %>% 
  dplyr::slice_min(., n=10, order_by=p_value) %>% 
  mutate(log_val = -log10(p_value))

tableLD_KEGG_d %>% ggplot(., aes(x = log_val, y = reorder(term_name, p_value), col= intersection_size)) +
  geom_point(aes(size = intersection_size)) +
  ggtitle("Late Response Enriched KEGG Terms")+
  xlab(expression("-log"[10]~"p-value"))+
  guides(col="none", size= guide_legend(title = "# of intersected \n terms"))+
  ylab("KEGG term")+
  scale_y_discrete(labels = scales::label_wrap(30))+
  theme_bw()+
  theme(plot.title = element_text(size = rel(1.5), hjust = 0.5),
        axis.title = element_text(size = 15, colour = "black"),
        axis.ticks = element_line(linewidth = 1.5),
        axis.line = element_line(linewidth = 1.5),
        axis.text = element_text(size = 10, colour = "black", angle = 0),
        strip.text = element_text(size = 15, colour = "black", face = "bold"))

Past versions of "Late DOX Response Motif Genes-3.png"

Version	Author	Date
ff644ec	emmapfort	2025-04-18
cee6b3d	emmapfort	2025-04-18
84d5599	emmapfort	2025-04-14

Now let’s look at this motif 3 (Late Response) with the posterior probability

motif_LR_pp <- prob_motif_3

LRmotif_genes_pp <- gost(query = motif_LR_pp,
                      organism = "hsapiens",
                      ordered_query = FALSE,
                      measure_underrepresentation = FALSE,
                      evcodes = FALSE,
                      user_threshold = 0.05,
                      correction_method = c("fdr"),
                      sources = c("GO:BP", "KEGG"))

cormotifLRclust_pp <- gostplot(LRmotif_genes_pp, capped = FALSE, interactive = TRUE)
cormotifLRclust_pp

tableLR_pp <- LRmotif_genes_pp$result %>% 
  dplyr::select(c(source, term_id, term_name, intersection_size, term_size, p_value))

tableLR_pp %>% 
  mutate_at(.vars = 6, .funs = scales::label_scientific(digits=4)) %>% 
  kableExtra::kable(.,) %>% 
  kableExtra::kable_paper("striped", full_width = FALSE) %>% 
  kableExtra::kable_styling(full_width = FALSE, position = "left", bootstrap_options = c("striped", "hover")) %>% 
  kableExtra::scroll_box(width = "100%", height = "400px")

source	term_id	term_name	intersection_size	term_size	p_value
GO:BP	GO:0006811	monoatomic ion transport	60	1256	6.212e-11
GO:BP	GO:0034220	monoatomic ion transmembrane transport	52	1017	1.681e-10
GO:BP	GO:0055085	transmembrane transport	65	1538	4.113e-10
GO:BP	GO:0098660	inorganic ion transmembrane transport	45	903	1.161e-08
GO:BP	GO:0015698	inorganic anion transport	18	165	1.375e-07
GO:BP	GO:0006820	monoatomic anion transport	18	167	1.400e-07
GO:BP	GO:0048869	cellular developmental process	118	4382	2.840e-07
GO:BP	GO:0030154	cell differentiation	118	4381	2.840e-07
GO:BP	GO:0006810	transport	117	4341	2.971e-07
GO:BP	GO:0006821	chloride transport	15	122	4.430e-07
GO:BP	GO:0032501	multicellular organismal process	167	7234	1.046e-06
GO:BP	GO:0006812	monoatomic cation transport	43	1032	2.823e-06
GO:BP	GO:0098656	monoatomic anion transmembrane transport	15	142	2.844e-06
GO:BP	GO:0032502	developmental process	152	6478	3.014e-06
GO:BP	GO:0048468	cell development	83	2833	4.124e-06
GO:BP	GO:1902476	chloride transmembrane transport	13	107	4.238e-06
GO:BP	GO:0098655	monoatomic cation transmembrane transport	37	832	4.606e-06
GO:BP	GO:0050896	response to stimulus	193	8993	4.865e-06
GO:BP	GO:0030001	metal ion transport	38	875	4.881e-06
GO:BP	GO:0007193	adenylate cyclase-inhibiting G protein-coupled receptor signaling pathway	11	79	1.047e-05
GO:BP	GO:0007267	cell-cell signaling	48	1316	1.298e-05
GO:BP	GO:0051234	establishment of localization	120	4869	1.533e-05
GO:BP	GO:0065008	regulation of biological quality	81	2847	1.552e-05
GO:BP	GO:0065007	biological regulation	247	12671	1.617e-05
GO:BP	GO:0007188	adenylate cyclase-modulating G protein-coupled receptor signaling pathway	18	248	1.781e-05
GO:BP	GO:0098661	inorganic anion transmembrane transport	13	127	2.060e-05
GO:BP	GO:0098662	inorganic cation transmembrane transport	34	811	4.571e-05
GO:BP	GO:0048856	anatomical structure development	136	5924	7.416e-05
GO:BP	GO:0022414	reproductive process	51	1556	9.471e-05
GO:BP	GO:0051179	localization	127	5521	2.049e-04
GO:BP	GO:0006813	potassium ion transport	16	238	2.050e-04
GO:BP	GO:0015711	organic anion transport	22	442	3.627e-04
GO:BP	GO:0023052	signaling	142	6471	4.510e-04
GO:BP	GO:0051480	regulation of cytosolic calcium ion concentration	8	59	5.282e-04
GO:BP	GO:0007154	cell communication	142	6496	5.345e-04
GO:BP	GO:0048232	male gamete generation	27	654	8.075e-04
GO:BP	GO:0003006	developmental process involved in reproduction	36	1022	8.341e-04
GO:BP	GO:0010817	regulation of hormone levels	24	548	9.563e-04
GO:BP	GO:0071805	potassium ion transmembrane transport	14	213	9.594e-04
GO:BP	GO:0002521	leukocyte differentiation	26	632	1.150e-03
GO:BP	GO:0007186	G protein-coupled receptor signaling pathway	41	1275	1.504e-03
GO:BP	GO:0050789	regulation of biological process	232	12278	1.750e-03
GO:BP	GO:0035725	sodium ion transmembrane transport	12	169	1.750e-03
GO:BP	GO:0007275	multicellular organism development	107	4658	1.750e-03
GO:BP	GO:0099536	synaptic signaling	29	783	2.264e-03
GO:BP	GO:0007283	spermatogenesis	25	637	3.208e-03
GO:BP	GO:0030003	intracellular monoatomic cation homeostasis	22	521	3.208e-03
GO:BP	GO:0019953	sexual reproduction	36	1103	3.281e-03
GO:BP	GO:0055082	intracellular chemical homeostasis	27	723	3.477e-03
GO:BP	GO:0042592	homeostatic process	49	1711	3.593e-03
GO:BP	GO:0006873	intracellular monoatomic ion homeostasis	22	530	3.743e-03
GO:BP	GO:0048731	system development	93	3985	3.743e-03
GO:BP	GO:0098771	inorganic ion homeostasis	22	531	3.776e-03
GO:BP	GO:0050877	nervous system process	44	1489	4.173e-03
GO:BP	GO:0055074	calcium ion homeostasis	16	326	5.815e-03
GO:BP	GO:0140013	meiotic nuclear division	12	198	6.435e-03
GO:BP	GO:0021879	forebrain neuron differentiation	6	46	6.491e-03
GO:BP	GO:0099537	trans-synaptic signaling	27	759	6.655e-03
GO:BP	GO:0035270	endocrine system development	10	142	6.926e-03
GO:BP	GO:0055080	monoatomic cation homeostasis	23	598	6.926e-03
GO:BP	GO:0048609	multicellular organismal reproductive process	32	980	7.045e-03
GO:BP	GO:0007200	phospholipase C-activating G protein-coupled receptor signaling pathway	9	116	7.045e-03
GO:BP	GO:0048878	chemical homeostasis	33	1026	7.079e-03
GO:BP	GO:0006814	sodium ion transport	13	235	7.216e-03
GO:BP	GO:0006874	intracellular calcium ion homeostasis	15	302	7.216e-03
GO:BP	GO:0010951	negative regulation of endopeptidase activity	5	31	7.902e-03
GO:BP	GO:0050801	monoatomic ion homeostasis	23	608	7.924e-03
GO:BP	GO:0002429	immune response-activating cell surface receptor signaling pathway	15	306	7.976e-03
GO:BP	GO:0007276	gamete generation	28	822	8.608e-03
GO:BP	GO:0042445	hormone metabolic process	13	243	9.261e-03
GO:BP	GO:0001775	cell activation	34	1098	1.012e-02
GO:BP	GO:0046903	secretion	31	968	1.091e-02
GO:BP	GO:0051716	cellular response to stimulus	148	7320	1.099e-02
GO:BP	GO:0007268	chemical synaptic transmission	26	753	1.099e-02
GO:BP	GO:0098916	anterograde trans-synaptic signaling	26	753	1.099e-02
GO:BP	GO:0042221	response to chemical	88	3867	1.099e-02
GO:BP	GO:0019722	calcium-mediated signaling	12	218	1.157e-02
GO:BP	GO:1901700	response to oxygen-containing compound	45	1632	1.161e-02
GO:BP	GO:0050957	equilibrioception	3	8	1.165e-02
GO:BP	GO:0060348	bone development	12	220	1.196e-02
GO:BP	GO:1903046	meiotic cell cycle process	12	220	1.196e-02
GO:BP	GO:0009410	response to xenobiotic stimulus	18	436	1.232e-02
GO:BP	GO:0007140	male meiotic nuclear division	6	55	1.232e-02
GO:BP	GO:0021630	olfactory nerve maturation	2	2	1.261e-02
GO:BP	GO:0042110	T cell activation	21	558	1.261e-02
GO:BP	GO:0021872	forebrain generation of neurons	6	56	1.261e-02
GO:BP	GO:0030098	lymphocyte differentiation	18	438	1.261e-02
GO:BP	GO:0036368	cone photoresponse recovery	2	2	1.261e-02
GO:BP	GO:0040020	regulation of meiotic nuclear division	5	36	1.261e-02
GO:BP	GO:0050851	antigen receptor-mediated signaling pathway	11	192	1.285e-02
GO:BP	GO:0051321	meiotic cell cycle	14	294	1.330e-02
GO:BP	GO:0098609	cell-cell adhesion	30	948	1.330e-02
GO:BP	GO:0007155	cell adhesion	42	1511	1.363e-02
GO:BP	GO:0045321	leukocyte activation	30	951	1.372e-02
GO:BP	GO:0021536	diencephalon development	7	81	1.409e-02
GO:BP	GO:0007600	sensory perception	30	955	1.413e-02
GO:BP	GO:0002768	immune response-regulating cell surface receptor signaling pathway	15	334	1.413e-02
GO:BP	GO:0045055	regulated exocytosis	12	229	1.413e-02
GO:BP	GO:0030450	regulation of complement activation, classical pathway	3	9	1.413e-02
GO:BP	GO:1903131	mononuclear cell differentiation	20	529	1.475e-02
GO:BP	GO:0019725	cellular homeostasis	27	826	1.487e-02
GO:BP	GO:0048485	sympathetic nervous system development	4	22	1.570e-02
GO:BP	GO:0046649	lymphocyte activation	26	787	1.582e-02
GO:BP	GO:0048732	gland development	18	454	1.582e-02
GO:BP	GO:0051932	synaptic transmission, GABAergic	6	60	1.582e-02
GO:BP	GO:0002366	leukocyte activation involved in immune response	14	305	1.666e-02
GO:BP	GO:0050794	regulation of cellular process	219	11876	1.689e-02
GO:BP	GO:0021953	central nervous system neuron differentiation	11	203	1.722e-02
GO:BP	GO:0046942	carboxylic acid transport	15	344	1.746e-02
GO:BP	GO:0015849	organic acid transport	15	345	1.783e-02
GO:BP	GO:0009581	detection of external stimulus	9	142	1.795e-02
GO:BP	GO:0002263	cell activation involved in immune response	14	309	1.795e-02
GO:BP	GO:0030217	T cell differentiation	14	312	1.958e-02
GO:BP	GO:1903306	negative regulation of regulated secretory pathway	4	24	1.990e-02
GO:BP	GO:0009582	detection of abiotic stimulus	9	145	2.023e-02
GO:BP	GO:0003008	system process	56	2266	2.064e-02
GO:BP	GO:0009888	tissue development	51	2012	2.112e-02
GO:BP	GO:0006869	lipid transport	17	431	2.155e-02
GO:BP	GO:1903977	positive regulation of glial cell migration	3	11	2.180e-02
GO:BP	GO:0015747	urate transport	3	11	2.180e-02
GO:BP	GO:0003341	cilium movement	11	212	2.195e-02
GO:BP	GO:0042391	regulation of membrane potential	17	433	2.195e-02
GO:BP	GO:0046631	alpha-beta T cell activation	10	181	2.355e-02
GO:BP	GO:0050848	regulation of calcium-mediated signaling	7	93	2.463e-02
GO:BP	GO:0006311	meiotic gene conversion	2	3	2.463e-02
GO:BP	GO:0010466	negative regulation of peptidase activity	5	45	2.463e-02
GO:BP	GO:0010481	epidermal cell division	2	3	2.463e-02
GO:BP	GO:0010482	regulation of epidermal cell division	2	3	2.463e-02
GO:BP	GO:0071486	cellular response to high light intensity	2	3	2.463e-02
GO:BP	GO:0033563	dorsal/ventral axon guidance	2	3	2.463e-02
GO:BP	GO:0021605	cranial nerve maturation	2	3	2.463e-02
GO:BP	GO:0021895	cerebral cortex neuron differentiation	4	26	2.463e-02
GO:BP	GO:1902105	regulation of leukocyte differentiation	14	325	2.463e-02
GO:BP	GO:0002064	epithelial cell development	11	217	2.463e-02
GO:BP	GO:0051445	regulation of meiotic cell cycle	6	69	2.584e-02
GO:BP	GO:0048513	animal organ development	70	3047	2.597e-02
GO:BP	GO:0030097	hemopoiesis	29	971	2.827e-02
GO:BP	GO:1903708	positive regulation of hemopoiesis	10	189	2.899e-02
GO:BP	GO:1902107	positive regulation of leukocyte differentiation	10	189	2.899e-02
GO:BP	GO:0002065	columnar/cuboidal epithelial cell differentiation	8	126	2.899e-02
GO:BP	GO:0008283	cell population proliferation	50	2009	2.927e-02
GO:BP	GO:0051446	positive regulation of meiotic cell cycle	4	28	2.927e-02
GO:BP	GO:0006817	phosphate ion transport	4	28	2.927e-02
GO:BP	GO:0048806	genitalia development	5	48	2.927e-02
GO:BP	GO:0009653	anatomical structure morphogenesis	63	2692	2.952e-02
GO:BP	GO:1904888	cranial skeletal system development	6	72	2.992e-02
GO:BP	GO:0001501	skeletal system development	19	536	3.011e-02
GO:BP	GO:0043301	negative regulation of leukocyte degranulation	3	13	3.011e-02
GO:BP	GO:0042403	thyroid hormone metabolic process	4	29	3.176e-02
GO:BP	GO:0007214	gamma-aminobutyric acid signaling pathway	4	29	3.176e-02
GO:BP	GO:0060249	anatomical structure homeostasis	12	264	3.206e-02
GO:BP	GO:0001894	tissue homeostasis	12	264	3.206e-02
GO:BP	GO:0030900	forebrain development	16	417	3.206e-02
GO:BP	GO:0060429	epithelium development	34	1229	3.455e-02
GO:BP	GO:0007127	meiosis I	8	132	3.539e-02
GO:BP	GO:0140352	export from cell	27	901	3.547e-02
GO:BP	GO:0035589	G protein-coupled purinergic nucleotide receptor signaling pathway	3	14	3.548e-02
GO:BP	GO:0048518	positive regulation of biological process	125	6235	3.604e-02
GO:BP	GO:0043410	positive regulation of MAPK cascade	17	465	3.669e-02
GO:BP	GO:0014070	response to organic cyclic compound	27	909	3.791e-02
GO:BP	GO:0006968	cellular defense response	5	52	3.791e-02
GO:BP	GO:0046352	disaccharide catabolic process	2	4	3.791e-02
GO:BP	GO:0010845	positive regulation of reciprocal meiotic recombination	2	4	3.791e-02
GO:BP	GO:0060294	cilium movement involved in cell motility	9	167	3.791e-02
GO:BP	GO:0021682	nerve maturation	2	4	3.791e-02
GO:BP	GO:0035822	gene conversion	2	4	3.791e-02
GO:BP	GO:0141006	transposable element silencing by piRNA-mediated heterochromatin formation	2	4	3.791e-02
GO:BP	GO:0140966	piRNA-mediated heterochromatin formation	2	4	3.791e-02
GO:BP	GO:0010520	regulation of reciprocal meiotic recombination	2	4	3.791e-02
GO:BP	GO:0045728	respiratory burst after phagocytosis	2	4	3.791e-02
GO:BP	GO:1990834	response to odorant	2	4	3.791e-02
GO:BP	GO:0009605	response to external stimulus	56	2367	3.880e-02
GO:BP	GO:0071695	anatomical structure maturation	12	274	3.887e-02
GO:BP	GO:0006816	calcium ion transport	16	433	4.134e-02
GO:BP	GO:0007165	signal transduction	120	5979	4.180e-02
GO:BP	GO:0007399	nervous system development	59	2541	4.341e-02
GO:BP	GO:2000241	regulation of reproductive process	10	206	4.341e-02
GO:BP	GO:0060285	cilium-dependent cell motility	9	172	4.341e-02
GO:BP	GO:0001539	cilium or flagellum-dependent cell motility	9	172	4.341e-02
GO:BP	GO:0030855	epithelial cell differentiation	23	741	4.442e-02
GO:BP	GO:0032940	secretion by cell	25	832	4.442e-02
GO:BP	GO:0007218	neuropeptide signaling pathway	7	110	4.452e-02
GO:BP	GO:0006957	complement activation, alternative pathway	3	16	4.452e-02
GO:BP	GO:0007194	negative regulation of adenylate cyclase activity	3	16	4.452e-02
GO:BP	GO:0010876	lipid localization	17	480	4.452e-02
GO:BP	GO:0061982	meiosis I cell cycle process	8	141	4.452e-02
GO:BP	GO:0061101	neuroendocrine cell differentiation	3	16	4.452e-02
GO:BP	GO:0043374	CD8-positive, alpha-beta T cell differentiation	3	16	4.452e-02
GO:BP	GO:0048522	positive regulation of cellular process	118	5886	4.481e-02
GO:BP	GO:1903530	regulation of secretion by cell	19	567	4.481e-02
GO:BP	GO:0003382	epithelial cell morphogenesis	4	34	4.481e-02
GO:BP	GO:0043270	positive regulation of monoatomic ion transport	10	209	4.481e-02
GO:BP	GO:0010526	transposable element silencing	4	34	4.481e-02
GO:BP	GO:0015701	bicarbonate transport	4	34	4.481e-02
GO:BP	GO:0045745	positive regulation of G protein-coupled receptor signaling pathway	4	34	4.481e-02
GO:BP	GO:0050870	positive regulation of T cell activation	11	248	4.822e-02
GO:BP	GO:0009566	fertilization	10	212	4.830e-02
GO:BP	GO:0045577	regulation of B cell differentiation	4	35	4.848e-02
GO:BP	GO:0051050	positive regulation of transport	25	844	4.848e-02
GO:BP	GO:0043299	leukocyte degranulation	6	84	4.848e-02
GO:BP	GO:0043949	regulation of cAMP-mediated signaling	4	35	4.848e-02
GO:BP	GO:0002679	respiratory burst involved in defense response	3	17	4.900e-02
GO:BP	GO:0009642	response to light intensity	3	17	4.900e-02
GO:BP	GO:0009628	response to abiotic stimulus	31	1130	4.900e-02
GO:BP	GO:0031280	negative regulation of cyclase activity	3	17	4.900e-02
GO:BP	GO:0045917	positive regulation of complement activation	2	5	4.921e-02
GO:BP	GO:0045920	negative regulation of exocytosis	4	36	4.921e-02
GO:BP	GO:0070995	NADPH oxidation	2	5	4.921e-02
GO:BP	GO:2000611	positive regulation of thyroid hormone generation	2	5	4.921e-02
GO:BP	GO:0032197	retrotransposition	4	36	4.921e-02
GO:BP	GO:0007610	behavior	21	665	4.921e-02
GO:BP	GO:0009644	response to high light intensity	2	5	4.921e-02
GO:BP	GO:0009887	animal organ morphogenesis	29	1037	4.921e-02
GO:BP	GO:0030317	flagellated sperm motility	8	147	4.921e-02
GO:BP	GO:0009914	hormone transport	13	328	4.921e-02
GO:BP	GO:0097722	sperm motility	8	147	4.921e-02
GO:BP	GO:0023061	signal release	17	493	4.921e-02
GO:BP	GO:0071484	cellular response to light intensity	2	5	4.921e-02
GO:BP	GO:0042127	regulation of cell population proliferation	42	1682	4.921e-02
GO:BP	GO:0002434	immune complex clearance	2	5	4.921e-02
GO:BP	GO:0045216	cell-cell junction organization	10	216	4.931e-02
KEGG	KEGG:04080	Neuroactive ligand-receptor interaction	25	365	1.188e-05

#write.csv(tableLR_pp, "output/table_LRmotif.csv")

#GO:BP
tableLR_GOBP_pp <- tableLR_pp %>% 
  dplyr::filter(source=="GO:BP") %>% 
  dplyr::select(p_value, term_name, intersection_size) %>% 
  dplyr::slice_min(., n=10, order_by=p_value) %>% 
  mutate(log_val = -log10(p_value))

#saveRDS(tableLR_GOBP_pp, "data/tableLR_GOBP_postprob.RDS")

tableLR_GOBP_pp %>% ggplot(., aes(x = log_val, y = reorder(term_name, p_value), col= intersection_size)) +
  geom_point(aes(size = intersection_size)) +
  ggtitle("No Response Enriched GO:BP Terms")+
  xlab(expression("-log"[10]~"p-value"))+
  guides(col="none", size= guide_legend(title = "# of intersected \n terms"))+
  ylab("GO:BP term")+
  scale_y_discrete(labels = scales::label_wrap(30))+
  theme_bw()+
  theme(plot.title = element_text(size = rel(1.5), hjust = 0.5),
        axis.title = element_text(size = 15, colour = "black"),
        axis.ticks = element_line(linewidth = 1.5),
        axis.line = element_line(linewidth = 1.5),
        axis.text = element_text(size = 10, colour = "black", angle = 0),
        strip.text = element_text(size = 15, colour = "black", face = "bold"))

Past versions of "Late Response Motif 3 Posterior Probability-2.png"

Version	Author	Date
cee6b3d	emmapfort	2025-04-18
84d5599	emmapfort	2025-04-14

#KEGG
tableLR_KEGG_pp <- tableLR_pp %>% 
  dplyr::filter(source=="KEGG") %>% 
  dplyr::select(p_value, term_name, intersection_size) %>% 
  dplyr::slice_min(., n=10, order_by=p_value) %>% 
  mutate(log_val = -log10(p_value))

tableLR_KEGG_pp %>% ggplot(., aes(x = log_val, y = reorder(term_name, p_value), col= intersection_size)) +
  geom_point(aes(size = intersection_size)) +
  ggtitle("No Response Enriched KEGG Terms")+
  xlab(expression("-log"[10]~"p-value"))+
  guides(col="none", size= guide_legend(title = "# of intersected \n terms"))+
  ylab("KEGG term")+
  scale_y_discrete(labels = scales::label_wrap(30))+
  theme_bw()+
  theme(plot.title = element_text(size = rel(1.5), hjust = 0.5),
        axis.title = element_text(size = 15, colour = "black"),
        axis.ticks = element_line(linewidth = 1.5),
        axis.line = element_line(linewidth = 1.5),
        axis.text = element_text(size = 10, colour = "black", angle = 0),
        strip.text = element_text(size = 15, colour = "black", face = "bold"))

Past versions of "Late Response Motif 3 Posterior Probability-3.png"

Version	Author	Date
cee6b3d	emmapfort	2025-04-18
84d5599	emmapfort	2025-04-14

Now let’s look at motif 4 - Early Sustained Response

motif_ED_d <- clust4_d

EDmotif_genes_d <- gost(query = motif_ED_d,
                      organism = "hsapiens",
                      ordered_query = FALSE,
                      measure_underrepresentation = FALSE,
                      evcodes = FALSE,
                      user_threshold = 0.05,
                      correction_method = c("fdr"),
                      sources = c("GO:BP", "KEGG"))

cormotifEDclust_d <- gostplot(EDmotif_genes_d, capped = FALSE, interactive = TRUE)
cormotifEDclust_d

tableED_d <- EDmotif_genes_d$result %>% 
  dplyr::select(c(source, term_id, term_name, intersection_size, term_size, p_value))

tableED_d %>% 
  mutate_at(.vars = 6, .funs = scales::label_scientific(digits=4)) %>% 
  kableExtra::kable(.,) %>% 
  kableExtra::kable_paper("striped", full_width = FALSE) %>% 
  kableExtra::kable_styling(full_width = FALSE, position = "left", bootstrap_options = c("striped", "hover")) %>% 
  kableExtra::scroll_box(width = "100%", height = "400px")

source	term_id	term_name	intersection_size	term_size	p_value
GO:BP	GO:0032502	developmental process	355	6478	5.420e-13
GO:BP	GO:0048856	anatomical structure development	331	5924	5.420e-13
GO:BP	GO:0032501	multicellular organismal process	372	7234	6.854e-10
GO:BP	GO:0048869	cellular developmental process	249	4382	2.296e-09
GO:BP	GO:0030154	cell differentiation	249	4381	2.296e-09
GO:BP	GO:0045165	cell fate commitment	37	291	1.255e-07
GO:BP	GO:0007275	multicellular organism development	253	4658	1.298e-07
GO:BP	GO:0048731	system development	221	3985	4.809e-07
GO:BP	GO:0003002	regionalization	44	434	2.357e-06
GO:BP	GO:0007389	pattern specification process	45	478	1.363e-05
GO:BP	GO:0001708	cell fate specification	19	113	2.533e-05
GO:BP	GO:0048513	animal organ development	171	3047	2.533e-05
GO:BP	GO:0009891	positive regulation of biosynthetic process	155	2707	3.346e-05
GO:BP	GO:0048663	neuron fate commitment	15	73	3.397e-05
GO:BP	GO:0007399	nervous system development	147	2541	3.675e-05
GO:BP	GO:0009953	dorsal/ventral pattern formation	16	90	8.195e-05
GO:BP	GO:0060429	epithelium development	83	1229	8.195e-05
GO:BP	GO:0009653	anatomical structure morphogenesis	152	2692	8.195e-05
GO:BP	GO:0009887	animal organ morphogenesis	73	1037	8.710e-05
GO:BP	GO:0018958	phenol-containing compound metabolic process	18	116	1.125e-04
GO:BP	GO:0007204	positive regulation of cytosolic calcium ion concentration	22	169	1.341e-04
GO:BP	GO:0009888	tissue development	118	2012	3.034e-04
GO:BP	GO:0033993	response to lipid	65	921	3.055e-04
GO:BP	GO:0007423	sensory organ development	48	612	4.541e-04
GO:BP	GO:0048468	cell development	154	2833	4.613e-04
GO:BP	GO:0034220	monoatomic ion transmembrane transport	69	1017	5.073e-04
GO:BP	GO:0030182	neuron differentiation	89	1434	6.680e-04
GO:BP	GO:0006357	regulation of transcription by RNA polymerase II	141	2572	7.935e-04
GO:BP	GO:0048665	neuron fate specification	9	35	8.914e-04
GO:BP	GO:0007417	central nervous system development	69	1038	8.914e-04
GO:BP	GO:0010557	positive regulation of macromolecule biosynthetic process	141	2604	1.377e-03
GO:BP	GO:0048699	generation of neurons	91	1517	1.699e-03
GO:BP	GO:1901615	organic hydroxy compound metabolic process	42	549	2.643e-03
GO:BP	GO:1901616	organic hydroxy compound catabolic process	11	61	2.797e-03
GO:BP	GO:0030855	epithelial cell differentiation	52	741	2.797e-03
GO:BP	GO:0006366	transcription by RNA polymerase II	143	2698	3.046e-03
GO:BP	GO:0048880	sensory system development	34	414	3.661e-03
GO:BP	GO:0060579	ventral spinal cord interneuron fate commitment	5	11	4.463e-03
GO:BP	GO:0060581	cell fate commitment involved in pattern specification	5	11	4.463e-03
GO:BP	GO:0022008	neurogenesis	99	1746	5.269e-03
GO:BP	GO:0021513	spinal cord dorsal/ventral patterning	6	18	5.269e-03
GO:BP	GO:0150063	visual system development	33	408	5.729e-03
GO:BP	GO:0019336	phenol-containing compound catabolic process	5	12	6.722e-03
GO:BP	GO:0009952	anterior/posterior pattern specification	22	225	6.780e-03
GO:BP	GO:0006952	defense response	101	1809	7.147e-03
GO:BP	GO:0002118	aggressive behavior	4	7	8.370e-03
GO:BP	GO:0006811	monoatomic ion transport	75	1256	8.467e-03
GO:BP	GO:0098660	inorganic ion transmembrane transport	58	903	8.467e-03
GO:BP	GO:0021511	spinal cord patterning	6	20	8.625e-03
GO:BP	GO:0045944	positive regulation of transcription by RNA polymerase II	75	1261	8.709e-03
GO:BP	GO:0060732	positive regulation of inositol phosphate biosynthetic process	5	13	8.709e-03
GO:BP	GO:0001654	eye development	32	404	8.709e-03
GO:BP	GO:0006954	inflammatory response	55	847	8.709e-03
GO:BP	GO:0021514	ventral spinal cord interneuron differentiation	5	13	8.709e-03
GO:BP	GO:0042403	thyroid hormone metabolic process	7	29	8.866e-03
GO:BP	GO:0003407	neural retina development	12	85	8.906e-03
GO:BP	GO:0007281	germ cell development	30	370	8.906e-03
GO:BP	GO:0022412	cellular process involved in reproduction in multicellular organism	32	408	9.645e-03
GO:BP	GO:0035270	endocrine system development	16	142	1.008e-02
GO:BP	GO:0009893	positive regulation of metabolic process	179	3648	1.135e-02
GO:BP	GO:0060040	retinal bipolar neuron differentiation	4	8	1.224e-02
GO:BP	GO:2000179	positive regulation of neural precursor cell proliferation	10	64	1.319e-02
GO:BP	GO:0071542	dopaminergic neuron differentiation	8	42	1.456e-02
GO:BP	GO:0010919	regulation of inositol phosphate biosynthetic process	5	15	1.557e-02
GO:BP	GO:0007267	cell-cell signaling	76	1316	1.589e-02
GO:BP	GO:0009605	response to external stimulus	123	2367	1.634e-02
GO:BP	GO:0035115	embryonic forelimb morphogenesis	7	33	1.744e-02
GO:BP	GO:0043010	camera-type eye development	28	352	1.744e-02
GO:BP	GO:1903409	reactive oxygen species biosynthetic process	9	55	1.768e-02
GO:BP	GO:0042420	dopamine catabolic process	4	9	1.862e-02
GO:BP	GO:0007156	homophilic cell adhesion via plasma membrane adhesion molecules	17	168	1.930e-02
GO:BP	GO:0050793	regulation of developmental process	126	2453	1.952e-02
GO:BP	GO:0042127	regulation of cell population proliferation	92	1682	1.952e-02
GO:BP	GO:0062013	positive regulation of small molecule metabolic process	15	138	1.952e-02
GO:BP	GO:0072330	monocarboxylic acid biosynthetic process	20	218	2.027e-02
GO:BP	GO:1902932	positive regulation of alcohol biosynthetic process	6	25	2.104e-02
GO:BP	GO:0045595	regulation of cell differentiation	87	1577	2.104e-02
GO:BP	GO:0045893	positive regulation of DNA-templated transcription	93	1710	2.104e-02
GO:BP	GO:0051239	regulation of multicellular organismal process	146	2928	2.122e-02
GO:BP	GO:1902680	positive regulation of RNA biosynthetic process	93	1713	2.144e-02
GO:BP	GO:0071396	cellular response to lipid	41	609	2.226e-02
GO:BP	GO:0065007	biological regulation	528	12671	2.357e-02
GO:BP	GO:0003006	developmental process involved in reproduction	61	1022	2.358e-02
GO:BP	GO:0019614	catechol-containing compound catabolic process	4	10	2.479e-02
GO:BP	GO:0042424	catecholamine catabolic process	4	10	2.479e-02
GO:BP	GO:0006633	fatty acid biosynthetic process	16	159	2.560e-02
GO:BP	GO:0051094	positive regulation of developmental process	75	1331	2.715e-02
GO:BP	GO:0062012	regulation of small molecule metabolic process	25	314	2.821e-02
GO:BP	GO:0006334	nucleosome assembly	13	115	2.821e-02
GO:BP	GO:0042759	long-chain fatty acid biosynthetic process	6	27	2.857e-02
GO:BP	GO:0098742	cell-cell adhesion via plasma-membrane adhesion molecules	23	280	2.988e-02
GO:BP	GO:0010628	positive regulation of gene expression	68	1189	3.217e-02
GO:BP	GO:0046069	cGMP catabolic process	3	5	3.232e-02
GO:BP	GO:0060284	regulation of cell development	52	851	3.278e-02
GO:BP	GO:2000049	positive regulation of cell-cell adhesion mediated by cadherin	4	11	3.278e-02
GO:BP	GO:0021515	cell differentiation in spinal cord	8	50	3.278e-02
GO:BP	GO:0010752	regulation of cGMP-mediated signaling	4	11	3.278e-02
GO:BP	GO:0014049	positive regulation of glutamate secretion	4	11	3.278e-02
GO:BP	GO:2000026	regulation of multicellular organismal development	78	1413	3.360e-02
GO:BP	GO:2000177	regulation of neural precursor cell proliferation	12	104	3.422e-02
GO:BP	GO:0042391	regulation of membrane potential	31	433	3.442e-02
GO:BP	GO:0034728	nucleosome organization	14	135	3.596e-02
GO:BP	GO:0051254	positive regulation of RNA metabolic process	97	1844	3.596e-02
GO:BP	GO:0030900	forebrain development	30	417	3.759e-02
GO:BP	GO:0022414	reproductive process	84	1556	3.821e-02
GO:BP	GO:1903426	regulation of reactive oxygen species biosynthetic process	7	40	3.821e-02
GO:BP	GO:0055085	transmembrane transport	83	1538	4.038e-02
GO:BP	GO:0003008	system process	115	2266	4.038e-02
GO:BP	GO:0090596	sensory organ morphogenesis	23	290	4.038e-02
GO:BP	GO:0048598	embryonic morphogenesis	40	617	4.038e-02
GO:BP	GO:0014070	response to organic cyclic compound	54	909	4.145e-02
GO:BP	GO:0035136	forelimb morphogenesis	7	41	4.145e-02
GO:BP	GO:1901654	response to ketone	19	221	4.145e-02
GO:BP	GO:0045597	positive regulation of cell differentiation	52	866	4.145e-02
GO:BP	GO:0052652	cyclic purine nucleotide metabolic process	7	41	4.145e-02
GO:BP	GO:0061351	neural precursor cell proliferation	16	171	4.226e-02
GO:BP	GO:0010604	positive regulation of macromolecule metabolic process	160	3349	4.343e-02
GO:BP	GO:0001819	positive regulation of cytokine production	33	486	4.343e-02
GO:BP	GO:0009187	cyclic nucleotide metabolic process	7	42	4.343e-02
GO:BP	GO:0009713	catechol-containing compound biosynthetic process	5	21	4.343e-02
GO:BP	GO:0060322	head development	48	789	4.343e-02
GO:BP	GO:0060563	neuroepithelial cell differentiation	7	42	4.343e-02
GO:BP	GO:0021536	diencephalon development	10	81	4.343e-02
GO:BP	GO:0048609	multicellular organismal reproductive process	57	980	4.343e-02
GO:BP	GO:0065008	regulation of biological quality	139	2847	4.343e-02
GO:BP	GO:0007218	neuropeptide signaling pathway	12	110	4.343e-02
GO:BP	GO:1903142	positive regulation of establishment of endothelial barrier	3	6	4.343e-02
GO:BP	GO:0042475	odontogenesis of dentin-containing tooth	11	95	4.343e-02
GO:BP	GO:0042423	catecholamine biosynthetic process	5	21	4.343e-02
GO:BP	GO:0007610	behavior	42	665	4.343e-02
GO:BP	GO:0098662	inorganic cation transmembrane transport	49	811	4.343e-02
GO:BP	GO:0048568	embryonic organ development	32	463	4.343e-02
GO:BP	GO:0021554	optic nerve development	5	21	4.343e-02
GO:BP	GO:1901552	positive regulation of endothelial cell development	3	6	4.343e-02
GO:BP	GO:0043132	NAD transport	3	6	4.343e-02
GO:BP	GO:0002065	columnar/cuboidal epithelial cell differentiation	13	126	4.371e-02
GO:BP	GO:0008283	cell population proliferation	103	2009	4.371e-02
GO:BP	GO:0021983	pituitary gland development	7	43	4.596e-02
GO:BP	GO:0007501	mesodermal cell fate specification	4	13	4.663e-02
GO:BP	GO:0036006	cellular response to macrophage colony-stimulating factor stimulus	4	13	4.663e-02
GO:BP	GO:2001141	regulation of RNA biosynthetic process	164	3454	4.663e-02
GO:BP	GO:0045907	positive regulation of vasoconstriction	6	32	4.715e-02
GO:BP	GO:0045723	positive regulation of fatty acid biosynthetic process	5	22	4.864e-02
GO:BP	GO:0008544	epidermis development	28	394	4.864e-02
KEGG	KEGG:04080	Neuroactive ligand-receptor interaction	40	365	3.260e-07
KEGG	KEGG:05322	Systemic lupus erythematosus	22	132	6.042e-07
KEGG	KEGG:05034	Alcoholism	22	187	2.222e-04
KEGG	KEGG:04613	Neutrophil extracellular trap formation	20	188	2.170e-03
KEGG	KEGG:05032	Morphine addiction	12	89	6.221e-03
KEGG	KEGG:04060	Cytokine-cytokine receptor interaction	25	291	6.221e-03
KEGG	KEGG:05202	Transcriptional misregulation in cancer	18	192	1.531e-02

#write.csv(tableED, "output/table_EarlyDOXmotif.csv")


#GO:BP
tableED_GOBP_d <- tableED_d %>% 
  dplyr::filter(source=="GO:BP") %>% 
  dplyr::select(p_value, term_name, intersection_size) %>% 
  dplyr::slice_min(., n=10, order_by=p_value) %>% 
  mutate(log_val = -log10(p_value))

#saveRDS(tableED_GOBP, "data/tableED_GOBP.RDS")

tableED_GOBP_d %>% ggplot(., aes(x = log_val, y = reorder(term_name, p_value), col= intersection_size)) +
  geom_point(aes(size = intersection_size)) +
  ggtitle("Early Sustained Response Enriched GO:BP Terms")+
  xlab(expression("-log"[10]~"p-value"))+
  guides(col="none", size= guide_legend(title = "# of intersected \n terms"))+
  ylab("GO:BP term")+
  scale_y_discrete(labels = scales::label_wrap(30))+
  theme_bw()+
  theme(plot.title = element_text(size = rel(1.5), hjust = 0.5),
        axis.title = element_text(size = 15, colour = "black"),
        axis.ticks = element_line(linewidth = 1.5),
        axis.line = element_line(linewidth = 1.5),
        axis.text = element_text(size = 10, colour = "black", angle = 0),
        strip.text = element_text(size = 15, colour = "black", face = "bold"))

Past versions of "Early Sustained DOX Response Motif Genes-2.png"

Version	Author	Date
ff644ec	emmapfort	2025-04-18
cee6b3d	emmapfort	2025-04-18
84d5599	emmapfort	2025-04-14

#KEGG
tableED_KEGG_d <- tableED_d %>% 
  dplyr::filter(source=="KEGG") %>% 
  dplyr::select(p_value, term_name, intersection_size) %>% 
  dplyr::slice_min(., n=10, order_by=p_value) %>% 
  mutate(log_val = -log10(p_value))

tableED_KEGG_d %>% ggplot(., aes(x = log_val, y = reorder(term_name, p_value), col= intersection_size)) +
  geom_point(aes(size = intersection_size)) +
  ggtitle("Early Sustained Response Enriched KEGG Terms")+
  xlab(expression("-log"[10]~"p-value"))+
  guides(col="none", size= guide_legend(title = "# of intersected \n terms"))+
  ylab("KEGG term")+
  scale_y_discrete(labels = scales::label_wrap(30))+
  theme_bw()+
  theme(plot.title = element_text(size = rel(1.5), hjust = 0.5),
        axis.title = element_text(size = 15, colour = "black"),
        axis.ticks = element_line(linewidth = 1.5),
        axis.line = element_line(linewidth = 1.5),
        axis.text = element_text(size = 10, colour = "black", angle = 0),
        strip.text = element_text(size = 15, colour = "black", face = "bold"))

Past versions of "Early Sustained DOX Response Motif Genes-3.png"

Version	Author	Date
ff644ec	emmapfort	2025-04-18
cee6b3d	emmapfort	2025-04-18
84d5599	emmapfort	2025-04-14

Now let’s see this with the posterior probability for the Early Sustained Response motif 4

motif_ESR_pp <- prob_motif_4

ESRmotif_genes_pp <- gost(query = motif_ESR_pp,
                      organism = "hsapiens",
                      ordered_query = FALSE,
                      measure_underrepresentation = FALSE,
                      evcodes = FALSE,
                      user_threshold = 0.05,
                      correction_method = c("fdr"),
                      sources = c("GO:BP", "KEGG"))

cormotifESRclust_pp <- gostplot(ESRmotif_genes_pp, capped = FALSE, interactive = TRUE)
cormotifESRclust_pp

tableESR_pp <- LRmotif_genes_pp$result %>% 
  dplyr::select(c(source, term_id, term_name, intersection_size, term_size, p_value))

tableESR_pp %>% 
  mutate_at(.vars = 6, .funs = scales::label_scientific(digits=4)) %>% 
  kableExtra::kable(.,) %>% 
  kableExtra::kable_paper("striped", full_width = FALSE) %>% 
  kableExtra::kable_styling(full_width = FALSE, position = "left", bootstrap_options = c("striped", "hover")) %>% 
  kableExtra::scroll_box(width = "100%", height = "400px")

source	term_id	term_name	intersection_size	term_size	p_value
GO:BP	GO:0006811	monoatomic ion transport	60	1256	6.212e-11
GO:BP	GO:0034220	monoatomic ion transmembrane transport	52	1017	1.681e-10
GO:BP	GO:0055085	transmembrane transport	65	1538	4.113e-10
GO:BP	GO:0098660	inorganic ion transmembrane transport	45	903	1.161e-08
GO:BP	GO:0015698	inorganic anion transport	18	165	1.375e-07
GO:BP	GO:0006820	monoatomic anion transport	18	167	1.400e-07
GO:BP	GO:0048869	cellular developmental process	118	4382	2.840e-07
GO:BP	GO:0030154	cell differentiation	118	4381	2.840e-07
GO:BP	GO:0006810	transport	117	4341	2.971e-07
GO:BP	GO:0006821	chloride transport	15	122	4.430e-07
GO:BP	GO:0032501	multicellular organismal process	167	7234	1.046e-06
GO:BP	GO:0006812	monoatomic cation transport	43	1032	2.823e-06
GO:BP	GO:0098656	monoatomic anion transmembrane transport	15	142	2.844e-06
GO:BP	GO:0032502	developmental process	152	6478	3.014e-06
GO:BP	GO:0048468	cell development	83	2833	4.124e-06
GO:BP	GO:1902476	chloride transmembrane transport	13	107	4.238e-06
GO:BP	GO:0098655	monoatomic cation transmembrane transport	37	832	4.606e-06
GO:BP	GO:0050896	response to stimulus	193	8993	4.865e-06
GO:BP	GO:0030001	metal ion transport	38	875	4.881e-06
GO:BP	GO:0007193	adenylate cyclase-inhibiting G protein-coupled receptor signaling pathway	11	79	1.047e-05
GO:BP	GO:0007267	cell-cell signaling	48	1316	1.298e-05
GO:BP	GO:0051234	establishment of localization	120	4869	1.533e-05
GO:BP	GO:0065008	regulation of biological quality	81	2847	1.552e-05
GO:BP	GO:0065007	biological regulation	247	12671	1.617e-05
GO:BP	GO:0007188	adenylate cyclase-modulating G protein-coupled receptor signaling pathway	18	248	1.781e-05
GO:BP	GO:0098661	inorganic anion transmembrane transport	13	127	2.060e-05
GO:BP	GO:0098662	inorganic cation transmembrane transport	34	811	4.571e-05
GO:BP	GO:0048856	anatomical structure development	136	5924	7.416e-05
GO:BP	GO:0022414	reproductive process	51	1556	9.471e-05
GO:BP	GO:0051179	localization	127	5521	2.049e-04
GO:BP	GO:0006813	potassium ion transport	16	238	2.050e-04
GO:BP	GO:0015711	organic anion transport	22	442	3.627e-04
GO:BP	GO:0023052	signaling	142	6471	4.510e-04
GO:BP	GO:0051480	regulation of cytosolic calcium ion concentration	8	59	5.282e-04
GO:BP	GO:0007154	cell communication	142	6496	5.345e-04
GO:BP	GO:0048232	male gamete generation	27	654	8.075e-04
GO:BP	GO:0003006	developmental process involved in reproduction	36	1022	8.341e-04
GO:BP	GO:0010817	regulation of hormone levels	24	548	9.563e-04
GO:BP	GO:0071805	potassium ion transmembrane transport	14	213	9.594e-04
GO:BP	GO:0002521	leukocyte differentiation	26	632	1.150e-03
GO:BP	GO:0007186	G protein-coupled receptor signaling pathway	41	1275	1.504e-03
GO:BP	GO:0050789	regulation of biological process	232	12278	1.750e-03
GO:BP	GO:0035725	sodium ion transmembrane transport	12	169	1.750e-03
GO:BP	GO:0007275	multicellular organism development	107	4658	1.750e-03
GO:BP	GO:0099536	synaptic signaling	29	783	2.264e-03
GO:BP	GO:0007283	spermatogenesis	25	637	3.208e-03
GO:BP	GO:0030003	intracellular monoatomic cation homeostasis	22	521	3.208e-03
GO:BP	GO:0019953	sexual reproduction	36	1103	3.281e-03
GO:BP	GO:0055082	intracellular chemical homeostasis	27	723	3.477e-03
GO:BP	GO:0042592	homeostatic process	49	1711	3.593e-03
GO:BP	GO:0006873	intracellular monoatomic ion homeostasis	22	530	3.743e-03
GO:BP	GO:0048731	system development	93	3985	3.743e-03
GO:BP	GO:0098771	inorganic ion homeostasis	22	531	3.776e-03
GO:BP	GO:0050877	nervous system process	44	1489	4.173e-03
GO:BP	GO:0055074	calcium ion homeostasis	16	326	5.815e-03
GO:BP	GO:0140013	meiotic nuclear division	12	198	6.435e-03
GO:BP	GO:0021879	forebrain neuron differentiation	6	46	6.491e-03
GO:BP	GO:0099537	trans-synaptic signaling	27	759	6.655e-03
GO:BP	GO:0035270	endocrine system development	10	142	6.926e-03
GO:BP	GO:0055080	monoatomic cation homeostasis	23	598	6.926e-03
GO:BP	GO:0048609	multicellular organismal reproductive process	32	980	7.045e-03
GO:BP	GO:0007200	phospholipase C-activating G protein-coupled receptor signaling pathway	9	116	7.045e-03
GO:BP	GO:0048878	chemical homeostasis	33	1026	7.079e-03
GO:BP	GO:0006814	sodium ion transport	13	235	7.216e-03
GO:BP	GO:0006874	intracellular calcium ion homeostasis	15	302	7.216e-03
GO:BP	GO:0010951	negative regulation of endopeptidase activity	5	31	7.902e-03
GO:BP	GO:0050801	monoatomic ion homeostasis	23	608	7.924e-03
GO:BP	GO:0002429	immune response-activating cell surface receptor signaling pathway	15	306	7.976e-03
GO:BP	GO:0007276	gamete generation	28	822	8.608e-03
GO:BP	GO:0042445	hormone metabolic process	13	243	9.261e-03
GO:BP	GO:0001775	cell activation	34	1098	1.012e-02
GO:BP	GO:0046903	secretion	31	968	1.091e-02
GO:BP	GO:0051716	cellular response to stimulus	148	7320	1.099e-02
GO:BP	GO:0007268	chemical synaptic transmission	26	753	1.099e-02
GO:BP	GO:0098916	anterograde trans-synaptic signaling	26	753	1.099e-02
GO:BP	GO:0042221	response to chemical	88	3867	1.099e-02
GO:BP	GO:0019722	calcium-mediated signaling	12	218	1.157e-02
GO:BP	GO:1901700	response to oxygen-containing compound	45	1632	1.161e-02
GO:BP	GO:0050957	equilibrioception	3	8	1.165e-02
GO:BP	GO:0060348	bone development	12	220	1.196e-02
GO:BP	GO:1903046	meiotic cell cycle process	12	220	1.196e-02
GO:BP	GO:0009410	response to xenobiotic stimulus	18	436	1.232e-02
GO:BP	GO:0007140	male meiotic nuclear division	6	55	1.232e-02
GO:BP	GO:0021630	olfactory nerve maturation	2	2	1.261e-02
GO:BP	GO:0042110	T cell activation	21	558	1.261e-02
GO:BP	GO:0021872	forebrain generation of neurons	6	56	1.261e-02
GO:BP	GO:0030098	lymphocyte differentiation	18	438	1.261e-02
GO:BP	GO:0036368	cone photoresponse recovery	2	2	1.261e-02
GO:BP	GO:0040020	regulation of meiotic nuclear division	5	36	1.261e-02
GO:BP	GO:0050851	antigen receptor-mediated signaling pathway	11	192	1.285e-02
GO:BP	GO:0051321	meiotic cell cycle	14	294	1.330e-02
GO:BP	GO:0098609	cell-cell adhesion	30	948	1.330e-02
GO:BP	GO:0007155	cell adhesion	42	1511	1.363e-02
GO:BP	GO:0045321	leukocyte activation	30	951	1.372e-02
GO:BP	GO:0021536	diencephalon development	7	81	1.409e-02
GO:BP	GO:0007600	sensory perception	30	955	1.413e-02
GO:BP	GO:0002768	immune response-regulating cell surface receptor signaling pathway	15	334	1.413e-02
GO:BP	GO:0045055	regulated exocytosis	12	229	1.413e-02
GO:BP	GO:0030450	regulation of complement activation, classical pathway	3	9	1.413e-02
GO:BP	GO:1903131	mononuclear cell differentiation	20	529	1.475e-02
GO:BP	GO:0019725	cellular homeostasis	27	826	1.487e-02
GO:BP	GO:0048485	sympathetic nervous system development	4	22	1.570e-02
GO:BP	GO:0046649	lymphocyte activation	26	787	1.582e-02
GO:BP	GO:0048732	gland development	18	454	1.582e-02
GO:BP	GO:0051932	synaptic transmission, GABAergic	6	60	1.582e-02
GO:BP	GO:0002366	leukocyte activation involved in immune response	14	305	1.666e-02
GO:BP	GO:0050794	regulation of cellular process	219	11876	1.689e-02
GO:BP	GO:0021953	central nervous system neuron differentiation	11	203	1.722e-02
GO:BP	GO:0046942	carboxylic acid transport	15	344	1.746e-02
GO:BP	GO:0015849	organic acid transport	15	345	1.783e-02
GO:BP	GO:0009581	detection of external stimulus	9	142	1.795e-02
GO:BP	GO:0002263	cell activation involved in immune response	14	309	1.795e-02
GO:BP	GO:0030217	T cell differentiation	14	312	1.958e-02
GO:BP	GO:1903306	negative regulation of regulated secretory pathway	4	24	1.990e-02
GO:BP	GO:0009582	detection of abiotic stimulus	9	145	2.023e-02
GO:BP	GO:0003008	system process	56	2266	2.064e-02
GO:BP	GO:0009888	tissue development	51	2012	2.112e-02
GO:BP	GO:0006869	lipid transport	17	431	2.155e-02
GO:BP	GO:1903977	positive regulation of glial cell migration	3	11	2.180e-02
GO:BP	GO:0015747	urate transport	3	11	2.180e-02
GO:BP	GO:0003341	cilium movement	11	212	2.195e-02
GO:BP	GO:0042391	regulation of membrane potential	17	433	2.195e-02
GO:BP	GO:0046631	alpha-beta T cell activation	10	181	2.355e-02
GO:BP	GO:0050848	regulation of calcium-mediated signaling	7	93	2.463e-02
GO:BP	GO:0006311	meiotic gene conversion	2	3	2.463e-02
GO:BP	GO:0010466	negative regulation of peptidase activity	5	45	2.463e-02
GO:BP	GO:0010481	epidermal cell division	2	3	2.463e-02
GO:BP	GO:0010482	regulation of epidermal cell division	2	3	2.463e-02
GO:BP	GO:0071486	cellular response to high light intensity	2	3	2.463e-02
GO:BP	GO:0033563	dorsal/ventral axon guidance	2	3	2.463e-02
GO:BP	GO:0021605	cranial nerve maturation	2	3	2.463e-02
GO:BP	GO:0021895	cerebral cortex neuron differentiation	4	26	2.463e-02
GO:BP	GO:1902105	regulation of leukocyte differentiation	14	325	2.463e-02
GO:BP	GO:0002064	epithelial cell development	11	217	2.463e-02
GO:BP	GO:0051445	regulation of meiotic cell cycle	6	69	2.584e-02
GO:BP	GO:0048513	animal organ development	70	3047	2.597e-02
GO:BP	GO:0030097	hemopoiesis	29	971	2.827e-02
GO:BP	GO:1903708	positive regulation of hemopoiesis	10	189	2.899e-02
GO:BP	GO:1902107	positive regulation of leukocyte differentiation	10	189	2.899e-02
GO:BP	GO:0002065	columnar/cuboidal epithelial cell differentiation	8	126	2.899e-02
GO:BP	GO:0008283	cell population proliferation	50	2009	2.927e-02
GO:BP	GO:0051446	positive regulation of meiotic cell cycle	4	28	2.927e-02
GO:BP	GO:0006817	phosphate ion transport	4	28	2.927e-02
GO:BP	GO:0048806	genitalia development	5	48	2.927e-02
GO:BP	GO:0009653	anatomical structure morphogenesis	63	2692	2.952e-02
GO:BP	GO:1904888	cranial skeletal system development	6	72	2.992e-02
GO:BP	GO:0001501	skeletal system development	19	536	3.011e-02
GO:BP	GO:0043301	negative regulation of leukocyte degranulation	3	13	3.011e-02
GO:BP	GO:0042403	thyroid hormone metabolic process	4	29	3.176e-02
GO:BP	GO:0007214	gamma-aminobutyric acid signaling pathway	4	29	3.176e-02
GO:BP	GO:0060249	anatomical structure homeostasis	12	264	3.206e-02
GO:BP	GO:0001894	tissue homeostasis	12	264	3.206e-02
GO:BP	GO:0030900	forebrain development	16	417	3.206e-02
GO:BP	GO:0060429	epithelium development	34	1229	3.455e-02
GO:BP	GO:0007127	meiosis I	8	132	3.539e-02
GO:BP	GO:0140352	export from cell	27	901	3.547e-02
GO:BP	GO:0035589	G protein-coupled purinergic nucleotide receptor signaling pathway	3	14	3.548e-02
GO:BP	GO:0048518	positive regulation of biological process	125	6235	3.604e-02
GO:BP	GO:0043410	positive regulation of MAPK cascade	17	465	3.669e-02
GO:BP	GO:0014070	response to organic cyclic compound	27	909	3.791e-02
GO:BP	GO:0006968	cellular defense response	5	52	3.791e-02
GO:BP	GO:0046352	disaccharide catabolic process	2	4	3.791e-02
GO:BP	GO:0010845	positive regulation of reciprocal meiotic recombination	2	4	3.791e-02
GO:BP	GO:0060294	cilium movement involved in cell motility	9	167	3.791e-02
GO:BP	GO:0021682	nerve maturation	2	4	3.791e-02
GO:BP	GO:0035822	gene conversion	2	4	3.791e-02
GO:BP	GO:0141006	transposable element silencing by piRNA-mediated heterochromatin formation	2	4	3.791e-02
GO:BP	GO:0140966	piRNA-mediated heterochromatin formation	2	4	3.791e-02
GO:BP	GO:0010520	regulation of reciprocal meiotic recombination	2	4	3.791e-02
GO:BP	GO:0045728	respiratory burst after phagocytosis	2	4	3.791e-02
GO:BP	GO:1990834	response to odorant	2	4	3.791e-02
GO:BP	GO:0009605	response to external stimulus	56	2367	3.880e-02
GO:BP	GO:0071695	anatomical structure maturation	12	274	3.887e-02
GO:BP	GO:0006816	calcium ion transport	16	433	4.134e-02
GO:BP	GO:0007165	signal transduction	120	5979	4.180e-02
GO:BP	GO:0007399	nervous system development	59	2541	4.341e-02
GO:BP	GO:2000241	regulation of reproductive process	10	206	4.341e-02
GO:BP	GO:0060285	cilium-dependent cell motility	9	172	4.341e-02
GO:BP	GO:0001539	cilium or flagellum-dependent cell motility	9	172	4.341e-02
GO:BP	GO:0030855	epithelial cell differentiation	23	741	4.442e-02
GO:BP	GO:0032940	secretion by cell	25	832	4.442e-02
GO:BP	GO:0007218	neuropeptide signaling pathway	7	110	4.452e-02
GO:BP	GO:0006957	complement activation, alternative pathway	3	16	4.452e-02
GO:BP	GO:0007194	negative regulation of adenylate cyclase activity	3	16	4.452e-02
GO:BP	GO:0010876	lipid localization	17	480	4.452e-02
GO:BP	GO:0061982	meiosis I cell cycle process	8	141	4.452e-02
GO:BP	GO:0061101	neuroendocrine cell differentiation	3	16	4.452e-02
GO:BP	GO:0043374	CD8-positive, alpha-beta T cell differentiation	3	16	4.452e-02
GO:BP	GO:0048522	positive regulation of cellular process	118	5886	4.481e-02
GO:BP	GO:1903530	regulation of secretion by cell	19	567	4.481e-02
GO:BP	GO:0003382	epithelial cell morphogenesis	4	34	4.481e-02
GO:BP	GO:0043270	positive regulation of monoatomic ion transport	10	209	4.481e-02
GO:BP	GO:0010526	transposable element silencing	4	34	4.481e-02
GO:BP	GO:0015701	bicarbonate transport	4	34	4.481e-02
GO:BP	GO:0045745	positive regulation of G protein-coupled receptor signaling pathway	4	34	4.481e-02
GO:BP	GO:0050870	positive regulation of T cell activation	11	248	4.822e-02
GO:BP	GO:0009566	fertilization	10	212	4.830e-02
GO:BP	GO:0045577	regulation of B cell differentiation	4	35	4.848e-02
GO:BP	GO:0051050	positive regulation of transport	25	844	4.848e-02
GO:BP	GO:0043299	leukocyte degranulation	6	84	4.848e-02
GO:BP	GO:0043949	regulation of cAMP-mediated signaling	4	35	4.848e-02
GO:BP	GO:0002679	respiratory burst involved in defense response	3	17	4.900e-02
GO:BP	GO:0009642	response to light intensity	3	17	4.900e-02
GO:BP	GO:0009628	response to abiotic stimulus	31	1130	4.900e-02
GO:BP	GO:0031280	negative regulation of cyclase activity	3	17	4.900e-02
GO:BP	GO:0045917	positive regulation of complement activation	2	5	4.921e-02
GO:BP	GO:0045920	negative regulation of exocytosis	4	36	4.921e-02
GO:BP	GO:0070995	NADPH oxidation	2	5	4.921e-02
GO:BP	GO:2000611	positive regulation of thyroid hormone generation	2	5	4.921e-02
GO:BP	GO:0032197	retrotransposition	4	36	4.921e-02
GO:BP	GO:0007610	behavior	21	665	4.921e-02
GO:BP	GO:0009644	response to high light intensity	2	5	4.921e-02
GO:BP	GO:0009887	animal organ morphogenesis	29	1037	4.921e-02
GO:BP	GO:0030317	flagellated sperm motility	8	147	4.921e-02
GO:BP	GO:0009914	hormone transport	13	328	4.921e-02
GO:BP	GO:0097722	sperm motility	8	147	4.921e-02
GO:BP	GO:0023061	signal release	17	493	4.921e-02
GO:BP	GO:0071484	cellular response to light intensity	2	5	4.921e-02
GO:BP	GO:0042127	regulation of cell population proliferation	42	1682	4.921e-02
GO:BP	GO:0002434	immune complex clearance	2	5	4.921e-02
GO:BP	GO:0045216	cell-cell junction organization	10	216	4.931e-02
KEGG	KEGG:04080	Neuroactive ligand-receptor interaction	25	365	1.188e-05

write.csv(tableESR_pp, "output/table_ESRmotif.csv")

#GO:BP
tableESR_GOBP_pp <- tableESR_pp %>% 
  dplyr::filter(source=="GO:BP") %>% 
  dplyr::select(p_value, term_name, intersection_size) %>% 
  dplyr::slice_min(., n=10, order_by=p_value) %>% 
  mutate(log_val = -log10(p_value))

#saveRDS(tableESR_GOBP_pp, "data/tableESR_GOBP_postprob.RDS")

tableESR_GOBP_pp %>% ggplot(., aes(x = log_val, y = reorder(term_name, p_value), col= intersection_size)) +
  geom_point(aes(size = intersection_size)) +
  ggtitle("No Response Enriched GO:BP Terms")+
  xlab(expression("-log"[10]~"p-value"))+
  guides(col="none", size= guide_legend(title = "# of intersected \n terms"))+
  ylab("GO:BP term")+
  scale_y_discrete(labels = scales::label_wrap(30))+
  theme_bw()+
  theme(plot.title = element_text(size = rel(1.5), hjust = 0.5),
        axis.title = element_text(size = 15, colour = "black"),
        axis.ticks = element_line(linewidth = 1.5),
        axis.line = element_line(linewidth = 1.5),
        axis.text = element_text(size = 10, colour = "black", angle = 0),
        strip.text = element_text(size = 15, colour = "black", face = "bold"))

Past versions of "Early Sustained Response Posterior Probability-2.png"

Version	Author	Date
cee6b3d	emmapfort	2025-04-18
84d5599	emmapfort	2025-04-14

#KEGG
tableESR_KEGG_pp <- tableESR_pp %>% 
  dplyr::filter(source=="KEGG") %>% 
  dplyr::select(p_value, term_name, intersection_size) %>% 
  dplyr::slice_min(., n=10, order_by=p_value) %>% 
  mutate(log_val = -log10(p_value))

tableESR_KEGG_pp %>% ggplot(., aes(x = log_val, y = reorder(term_name, p_value), col= intersection_size)) +
  geom_point(aes(size = intersection_size)) +
  ggtitle("No Response Enriched KEGG Terms")+
  xlab(expression("-log"[10]~"p-value"))+
  guides(col="none", size= guide_legend(title = "# of intersected \n terms"))+
  ylab("KEGG term")+
  scale_y_discrete(labels = scales::label_wrap(30))+
  theme_bw()+
  theme(plot.title = element_text(size = rel(1.5), hjust = 0.5),
        axis.title = element_text(size = 15, colour = "black"),
        axis.ticks = element_line(linewidth = 1.5),
        axis.line = element_line(linewidth = 1.5),
        axis.text = element_text(size = 10, colour = "black", angle = 0),
        strip.text = element_text(size = 15, colour = "black", face = "bold"))

Past versions of "Early Sustained Response Posterior Probability-3.png"

Version	Author	Date
cee6b3d	emmapfort	2025-04-18
84d5599	emmapfort	2025-04-14

Currently for the posterior probability code - motif 3 and motif 4 are showing up identically

Session information

sessionInfo()

R version 4.4.2 (2024-10-31 ucrt)
Platform: x86_64-w64-mingw32/x64
Running under: Windows 11 x64 (build 22000)

Matrix products: default


locale:
[1] LC_COLLATE=English_United States.utf8 
[2] LC_CTYPE=English_United States.utf8   
[3] LC_MONETARY=English_United States.utf8
[4] LC_NUMERIC=C                          
[5] LC_TIME=English_United States.utf8    

time zone: America/Chicago
tzcode source: internal

attached base packages:
[1] stats4    stats     graphics  grDevices utils     datasets  methods  
[8] base     

other attached packages:
 [1] gprofiler2_0.2.3            cowplot_1.1.3              
 [3] Rfast_2.1.5.1               RcppParallel_5.1.10        
 [5] zigg_0.0.2                  Rcpp_1.0.13-1              
 [7] RUVSeq_1.40.0               EDASeq_2.40.0              
 [9] ShortRead_1.64.0            GenomicAlignments_1.42.0   
[11] SummarizedExperiment_1.36.0 MatrixGenerics_1.18.1      
[13] matrixStats_1.4.1           Rsamtools_2.22.0           
[15] GenomicRanges_1.58.0        Biostrings_2.74.0          
[17] GenomeInfoDb_1.42.3         XVector_0.46.0             
[19] IRanges_2.40.0              S4Vectors_0.44.0           
[21] BiocParallel_1.40.0         biomaRt_2.62.1             
[23] RColorBrewer_1.1-3          Cormotif_1.52.0            
[25] affy_1.84.0                 Biobase_2.66.0             
[27] BiocGenerics_0.52.0         PCAtools_2.18.0            
[29] ggfortify_0.4.17            pheatmap_1.0.12            
[31] edgeR_4.4.0                 limma_3.62.1               
[33] readxl_1.4.3                edgebundleR_0.1.4          
[35] lubridate_1.9.3             forcats_1.0.0              
[37] stringr_1.5.1               dplyr_1.1.4                
[39] purrr_1.0.2                 readr_2.1.5                
[41] tidyr_1.3.1                 tidyverse_2.0.0            
[43] tibble_3.2.1                hrbrthemes_0.8.7           
[45] reshape2_1.4.4              ggrepel_0.9.6              
[47] ggplot2_3.5.1               workflowr_1.7.1            

loaded via a namespace (and not attached):
  [1] later_1.4.1               BiocIO_1.16.0            
  [3] bitops_1.0-9              filelock_1.0.3           
  [5] R.oo_1.27.0               cellranger_1.1.0         
  [7] preprocessCore_1.68.0     XML_3.99-0.18            
  [9] lifecycle_1.0.4           httr2_1.1.0              
 [11] pwalign_1.2.0             rprojroot_2.0.4          
 [13] MASS_7.3-61               processx_3.8.5           
 [15] lattice_0.22-6            crosstalk_1.2.1          
 [17] magrittr_2.0.3            plotly_4.10.4            
 [19] sass_0.4.9                rmarkdown_2.29           
 [21] jquerylib_0.1.4           yaml_2.3.10              
 [23] httpuv_1.6.15             DBI_1.2.3                
 [25] abind_1.4-8               zlibbioc_1.52.0          
 [27] R.utils_2.12.3            RCurl_1.98-1.16          
 [29] rappdirs_0.3.3            git2r_0.35.0             
 [31] gdtools_0.4.1             GenomeInfoDbData_1.2.13  
 [33] irlba_2.3.5.1             dqrng_0.4.1              
 [35] svglite_2.1.3             DelayedMatrixStats_1.28.1
 [37] codetools_0.2-20          DelayedArray_0.32.0      
 [39] xml2_1.3.6                tidyselect_1.2.1         
 [41] farver_2.1.2              UCSC.utils_1.2.0         
 [43] ScaledMatrix_1.14.0       BiocFileCache_2.14.0     
 [45] jsonlite_1.8.9            systemfonts_1.1.0        
 [47] tools_4.4.2               progress_1.2.3           
 [49] glue_1.8.0                gridExtra_2.3            
 [51] Rttf2pt1_1.3.12           SparseArray_1.6.0        
 [53] xfun_0.49                 withr_3.0.2              
 [55] BiocManager_1.30.25       fastmap_1.2.0            
 [57] latticeExtra_0.6-30       callr_3.7.6              
 [59] digest_0.6.37             rsvd_1.0.5               
 [61] timechange_0.3.0          R6_2.6.1                 
 [63] mime_0.12                 colorspace_2.1-1         
 [65] jpeg_0.1-10               RSQLite_2.3.8            
 [67] R.methodsS3_1.8.2         generics_0.1.3           
 [69] data.table_1.16.4         fontLiberation_0.1.0     
 [71] rtracklayer_1.66.0        prettyunits_1.2.0        
 [73] httr_1.4.7                htmlwidgets_1.6.4        
 [75] S4Arrays_1.6.0            whisker_0.4.1            
 [77] pkgconfig_2.0.3           gtable_0.3.6             
 [79] blob_1.2.4                hwriter_1.3.2.1          
 [81] htmltools_0.5.8.1         fontBitstreamVera_0.1.1  
 [83] kableExtra_1.4.0          scales_1.3.0             
 [85] png_0.1-8                 knitr_1.49               
 [87] rstudioapi_0.17.1         tzdb_0.4.0               
 [89] rjson_0.2.23              curl_6.0.1               
 [91] cachem_1.1.0              parallel_4.4.2           
 [93] extrafont_0.19            AnnotationDbi_1.68.0     
 [95] restfulr_0.0.15           pillar_1.10.1            
 [97] grid_4.4.2                vctrs_0.6.5              
 [99] promises_1.3.2            BiocSingular_1.22.0      
[101] dbplyr_2.5.0              beachmat_2.22.0          
[103] xtable_1.8-4              extrafontdb_1.0          
[105] evaluate_1.0.3            GenomicFeatures_1.58.0   
[107] cli_3.6.3                 locfit_1.5-9.10          
[109] compiler_4.4.2            rlang_1.1.4              
[111] crayon_1.5.3              labeling_0.4.3           
[113] aroma.light_3.36.0        interp_1.1-6             
[115] ps_1.8.1                  getPass_0.2-4            
[117] plyr_1.8.9                fs_1.6.5                 
[119] stringi_1.8.4             viridisLite_0.4.2        
[121] deldir_2.0-4              munsell_0.5.1            
[123] lazyeval_0.2.2            fontquiver_0.2.1         
[125] Matrix_1.7-1              hms_1.1.3                
[127] sparseMatrixStats_1.18.0  bit64_4.5.2              
[129] KEGGREST_1.46.0           statmod_1.5.0            
[131] shiny_1.10.0              igraph_2.1.1             
[133] memoise_2.0.1             affyio_1.76.0            
[135] bslib_0.9.0               bit_4.5.0