H3K27ac TF enrichment

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Last updated: 2026-02-23

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Knit directory: DXR_continue/

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---

library(tidyverse)
library(GenomicRanges)
library(plyranges)
library(genomation)
library(readr)
library(rtracklayer)
library(stringr)
library(DT)

Summit calls method 1

This is actually summit +/- 200 bp (and 300bp for initial investigation)

H3K27ac_Set2_sea_disc_out <-read_delim("C:/Users/renee/Other_projects_data/DXR_data/H3K27ac/H3K27ac_set2_400/sea_disc_out/sea.tsv", delim = "\t", escape_double = FALSE,     trim_ws = TRUE) %>% mutate(source="disc") %>% slice_head(n = length(.$ID)-3)

H3K27ac_Set2_sea_known <-read_delim("C:/Users/renee/Other_projects_data/DXR_data/H3K27ac/H3K27ac_set2_400/sea_out/sea.tsv", delim = "\t", escape_double = FALSE,     trim_ws = TRUE) %>% mutate(source="known") %>% slice_head(n = length(.$ID)-3)

H3K27ac_Set2_xstreme <- read_delim("C:/Users/renee/Other_projects_data/DXR_data/H3K27ac/H3K27ac_set2_400/xstreme.tsv", delim = "\t", escape_double = FALSE,     trim_ws = TRUE) %>% mutate(source="all") %>% slice_head(n = length(.$ID)-3)


H3K27ac_Set2_tomtom <- read_delim("C:/Users/renee/Other_projects_data/DXR_data/H3K27ac/H3K27ac_set2_400/streme_tomtom_out/tomtom.tsv", 
    delim = "\t", escape_double = FALSE, 
    trim_ws = TRUE)

test_bind <- bind_rows(H3K27ac_Set2_sea_disc_out, H3K27ac_Set2_sea_known) %>% 
  dplyr::select(DB:ENR_RATIO) %>% 
  group_by(ID,ALT_ID, ENR_RATIO) %>% distinct()

H3K27ac_Set3_sea_disc_out <-read_delim("C:/Users/renee/Other_projects_data/DXR_data/H3K27ac/H3K27ac_set3_400/sea_disc_out/sea.tsv", delim = "\t", escape_double = FALSE,     trim_ws = TRUE) %>% mutate(source="disc") %>% slice_head(n = length(.$ID)-3)

H3K27ac_Set3_sea_known <-read_delim("C:/Users/renee/Other_projects_data/DXR_data/H3K27ac/H3K27ac_set3_400/sea_out/sea.tsv", delim = "\t", escape_double = FALSE,     trim_ws = TRUE) %>% mutate(source="known") %>% slice_head(n = length(.$ID)-3)

H3K27ac_Set3_xstreme <- read_delim("C:/Users/renee/Other_projects_data/DXR_data/H3K27ac/H3K27ac_set3_400/xstreme.tsv", delim = "\t", escape_double = FALSE,     trim_ws = TRUE) %>% mutate(source="all") %>% slice_head(n = length(.$ID)-3)


H3K27ac_Set3_tomtom <- read_delim("C:/Users/renee/Other_projects_data/DXR_data/H3K27ac/H3K27ac_set3_400/streme_tomtom_out/tomtom.tsv", 
    delim = "\t", escape_double = FALSE, 
    trim_ws = TRUE)

test_bind3 <-bind_rows(H3K27ac_Set3_sea_disc_out, H3K27ac_Set3_sea_known) %>%
  dplyr::select(DB:ENR_RATIO) %>% 
  group_by(ID,ALT_ID) %>% 
  distinct()

H3K27ac_Set2_data <- H3K27ac_Set2_xstreme %>% 
  dplyr::select(RANK:CLUSTER,ID:CONSENSUS,EVALUE,SIM_MOTIF,MOTIF_URL) %>% 
  mutate(MOTIF_URL=str_replace(MOTIF_URL,"https://jaspar2024.elixir.no/matrix/","")) %>% 
  mutate(motif_name=case_when(
    str_detect(SIM_MOTIF, "\\(") ~ str_extract(SIM_MOTIF, "(?<=\\().+?(?=\\))"),
    str_detect(SIM_MOTIF, "^MA\\d+\\.\\d+") ~ ALT_ID,
    str_detect(SIM_MOTIF, "^\\d+-") ~ str_replace(SIM_MOTIF, "^\\d+-", ""),
  TRUE ~ SIM_MOTIF)) %>% 
  left_join(test_bind) %>% 
  mutate(diff_per=`TP%` -`FP%`)

H3K27ac_Set3_data <- H3K27ac_Set3_xstreme %>% 
  dplyr::select(RANK:CLUSTER,ID:CONSENSUS,EVALUE,SIM_MOTIF,MOTIF_URL) %>% 
  mutate(MOTIF_URL=str_replace(MOTIF_URL,"https://jaspar2024.elixir.no/matrix/","")) %>% 
  mutate(motif_name=case_when(
    str_detect(SIM_MOTIF, "\\(") ~ str_extract(SIM_MOTIF, "(?<=\\().+?(?=\\))"),
    str_detect(SIM_MOTIF, "^MA\\d+\\.\\d+") ~ ALT_ID,
    str_detect(SIM_MOTIF, "^\\d+-") ~ str_replace(SIM_MOTIF, "^\\d+-", ""),
  TRUE ~ SIM_MOTIF)) %>% 
  left_join(test_bind3, by=c("ID"="ID","ALT_ID"="ALT_ID")) %>% 
  mutate(diff_per=`TP%` -`FP%`)

H3K27ac_Set2_data %>% 
  dplyr::filter(ENR_RATIO>1.2) %>% 
  group_by(CLUSTER) %>% 
  slice_min(EVALUE, with_ties = FALSE) %>% 
   mutate(log10Evalue= log(EVALUE, base = 10)*(-1)) %>% 
  ggplot(., aes (y= reorder(motif_name,log10Evalue))) +
  geom_col(aes(x=log10Evalue))+
  geom_point(aes(x=`TP%`*2), size =4)+
  scale_x_continuous(expand=c (0,.125),sec.axis = sec_axis(transform= ~./2,name="Percent of peaks with motif"))+
  theme_classic()+
  ylab("Enriched TF motif")+
  ggtitle(paste("SET2 enrichment over SET1, Enrichment ratio >1.2"))

Past versions of unnamed-chunk-2-1.png

Version	Author	Date
c560d24	reneeisnowhere	2026-01-15

H3K27ac_Set3_data %>% 
  dplyr::filter(ENR_RATIO>1.2) %>%
  group_by(CLUSTER) %>% 
  slice_min(EVALUE, with_ties = FALSE) %>% 
   mutate(log10Evalue= log(EVALUE, base = 10)*(-1)) %>% 
  ggplot(., aes (y= reorder(motif_name,log10Evalue))) +
  geom_col(aes(x=log10Evalue))+
  geom_point(aes(x=`TP%`*1), size =4)+
  scale_x_continuous(expand=c (0,.125),sec.axis = sec_axis(transform= ~./1,name="Percent of peaks with motif"))+
  theme_classic()+
  ylab("Enriched TF motif")+
  ggtitle(paste("SET3 enrichment over SET1, Enrichment ratio > 1.2"))

Past versions of unnamed-chunk-2-2.png

Version	Author	Date
78269d9	reneeisnowhere	2026-02-09
c560d24	reneeisnowhere	2026-01-15

H3K27ac_Set2_data %>% 
  dplyr::filter(ENR_RATIO>1.2) %>% 
  group_by(CLUSTER) %>% 
  slice_min(EVALUE, with_ties = FALSE) %>% 
   mutate(log10Evalue= log(EVALUE, base = 10)*(-1)) %>% 
  ggplot(., aes (y= reorder(motif_name,log10Evalue))) +
  geom_col(aes(x=log10Evalue))+
  geom_point(aes(x=`TP%`*2), size =4)+
  scale_x_continuous(expand=c (0,.125),sec.axis = sec_axis(transform= ~./2,name="Percent of peaks with motif"))+
  theme_classic()+
  ylab("Enriched TF motif")+
  ggtitle(paste("SET2 enrichment over SET1, Enrichment ratio >1.2"))

Past versions of "enrichment by cluster-1.png"

Version	Author	Date
3f3d9a4	reneeisnowhere	2026-02-02

H3K27ac_Set3_data %>% 
  dplyr::filter(ENR_RATIO>1.1) %>%
  group_by(CLUSTER) %>% 
  slice_min(EVALUE, with_ties = FALSE) %>% 
   mutate(log10Evalue= log(EVALUE, base = 10)*(-1)) %>% 
  ggplot(., aes (y= reorder(motif_name,log10Evalue))) +
  geom_col(aes(x=log10Evalue))+
  geom_point(aes(x=`TP%`*1), size =4)+
  scale_x_continuous(expand=c (0,.125),sec.axis = sec_axis(transform= ~./1,name="Percent of peaks with motif"))+
  theme_classic()+
  ylab("Enriched TF motif")+
  ggtitle(paste("SET3 enrichment over SET1, Enrichment ratio > 1.1"))

Past versions of "enrichment by cluster-2.png"

Version	Author	Date
3f3d9a4	reneeisnowhere	2026-02-02

H3K27ac_Set2_data %>% 
  ggplot(., aes (x= ENR_RATIO)) +
  geom_density()+
  # geom_point(aes(x=`TP%`*2), size =4)+
  # scale_x_continuous(expand=c (0,.125),sec.axis = sec_axis(transform= ~./2,name="Percent of peaks with motif"))+
  theme_classic()+
  # ylab("Enriched TF motif")+
  ggtitle(paste("Span of enrichment ratios for Set2"))

Past versions of "enrichment ratio dispersion-1.png"

Version	Author	Date
c560d24	reneeisnowhere	2026-01-15

H3K27ac_Set3_data %>% 
  ggplot(., aes (x= ENR_RATIO)) +
  geom_density()+
  theme_classic()+
  ggtitle(paste("Span of enrichment ratios for Set3"))

Past versions of "enrichment ratio dispersion-2.png"

Version	Author	Date
c560d24	reneeisnowhere	2026-01-15

H3K27ac_Set3_data %>% 
  ggplot(., aes (x= ENR_RATIO)) +
  geom_density()+
  theme_classic()+
  ggtitle(paste("Span of enrichment ratios for Set3"))+
  coord_cartesian(xlim=c(0,6))

Past versions of "enrichment ratio dispersion-3.png"

Version	Author	Date
c560d24	reneeisnowhere	2026-01-15

ggVennDiagram::ggVennDiagram(list("H3K27ac_Set2"=H3K27ac_Set2_data$motif_name,"H3K27ac_Set3"=H3K27ac_Set3_data$motif_name))+
  ggtitle("H3K27ac motif overlap")+
  coord_cartesian(clip = "off") +
  theme(
    plot.margin = margin(20, 60, 20, 60)  # top, right, bottom, left
  )

Past versions of unnamed-chunk-3-1.png

Version	Author	Date
c560d24	reneeisnowhere	2026-01-15

# test_bind
# xstreme_rank_bind
DT::datatable((H3K27ac_Set2_data %>% 
  dplyr::select(RANK,CLUSTER,ID,ALT_ID,EVALUE, CONSENSUS)),
  rownames = FALSE,
  caption = htmltools::tags$caption(
    style = "caption-side: top; text-align: left; font-weight: bold;",
    "Method 1: Set 2 H3K27ac"
  ),
  filter = 'top',       # add filter/search boxes
  options = list(
    pageLength = 10,
    autoWidth = FALSE,
    scrollX = TRUE)) 

DT::datatable((H3K27ac_Set3_data %>% 
  dplyr::select(RANK,CLUSTER,ID,ALT_ID,EVALUE, CONSENSUS.x)),
  rownames = FALSE,
  caption = htmltools::tags$caption(
    style = "caption-side: top; text-align: left; font-weight: bold;",
    "Method 1: Set 3 H3K27ac"
  ),
  filter = 'top',       # add filter/search boxes
  options = list(
    pageLength = 10,
    autoWidth = FALSE,
    scrollX = TRUE)) 

H3K27ac_Set2_data %>% 
dplyr::filter(EVALUE<0.05) %>% 
   group_by(CLUSTER) %>% 
  slice_min(RANK, with_ties = FALSE) %>% 
  ungroup() %>% 
   mutate(log10Evalue= log(EVALUE, base = 10)*(-1)) %>%
    mutate(Facets=case_when(RANK <15~"A",
                              log10Evalue >15 & log10Evalue <40~"B",
            log10Evalue>40~"C")) %>% 
  dplyr::filter(Facets=="A") %>% 
    ggplot(., aes (y= reorder(motif_name, log10Evalue))) +
  geom_col(aes(x=log10Evalue))+
   geom_point(aes(x=ENR_RATIO*40, color=ENR_RATIO), size =4)+
  scale_x_continuous(expand = c(0, .125),
  sec.axis = sec_axis(~ . /40, name = "Enrichment Ratio"))+
 
  facet_wrap(~Facets )+
  theme_classic()+
  ylab("Enriched TF motif")+
  ggtitle(paste("SET2 enrichment over SET1\n top Enrichment Ratio by Cluster H3K27ac"))

Past versions of "set 2 by facet-1.png"

Version	Author	Date
3f3d9a4	reneeisnowhere	2026-02-02

H3K27ac_Set2_data %>% 
dplyr::filter(EVALUE<0.05) %>% 
   group_by(CLUSTER) %>% 
  slice_min(RANK, with_ties = FALSE) %>% 
  ungroup() %>% 
   mutate(log10Evalue= log(EVALUE, base = 10)*(-1)) %>%
    mutate(Facets=case_when(RANK <15~"A",
                              log10Evalue >15 & log10Evalue <40~"B",
            log10Evalue>40~"C")) %>% 
  dplyr::filter(Facets=="B") %>% 
     ggplot(., aes (y= reorder(motif_name, log10Evalue))) +
  geom_col(aes(x=log10Evalue))+
  geom_point(aes(x=ENR_RATIO*10, color=ENR_RATIO), size =4)+
  
  scale_x_continuous(
  expand = c(0, .125),
  sec.axis = sec_axis(~ . / 10, name = "Enrichment Ratio")
)+
  scale_color_viridis_c(
    name = "Enrichment Ratio",
    option = "plasma") +
  tidytext::scale_y_reordered()+
  facet_wrap(~Facets )+
  theme_classic()+
  ylab("Enriched TF motif")+
  ggtitle(paste("SET2 enrichment over SET1\n top Enrichment Ratio by Cluster H3K27ac"))

Past versions of "set 2 by facet-2.png"

Version	Author	Date
3f3d9a4	reneeisnowhere	2026-02-02

H3K27ac_Set2_data %>% 
dplyr::filter(EVALUE<0.05) %>% 
   group_by(CLUSTER) %>% 
  slice_min(RANK, with_ties = FALSE) %>% 
  ungroup() %>% 
   mutate(log10Evalue= log(EVALUE, base = 10)*(-1)) %>%
     mutate(Facets=case_when(RANK <15~"A",
                              log10Evalue >15 & log10Evalue <40~"B",
            log10Evalue>40~"C")) %>% 
  dplyr::filter(Facets=="C") %>% 
     ggplot(., aes (y= reorder(motif_name, log10Evalue))) +
  geom_col(aes(x=log10Evalue))+
  geom_point(aes(x=ENR_RATIO*.8, color=ENR_RATIO), size =4)+
  scale_x_continuous(
  expand = c(0, .125),
  sec.axis = sec_axis(~ . / .8, name = "Enrichment Ratio")
)+
  scale_color_viridis_c(
    name = "Enrichment Ratio",
    option = "plasma") +
  facet_wrap(~Facets )+
  theme_classic()+
  ylab("Enriched TF motif")+
  ggtitle(paste("SET2 enrichment over SET1\n top Enrichment Ratio by Cluster H3K27ac"))

Past versions of "set 2 by facet-3.png"

Version	Author	Date
3f3d9a4	reneeisnowhere	2026-02-02

H3K27ac_Set3_data %>% 
dplyr::filter(EVALUE<0.05) %>% 
   group_by(CLUSTER) %>% 
  slice_min(RANK, with_ties = FALSE) %>% 
  ungroup() %>% 
   mutate(log10Evalue= log(EVALUE, base = 10)*(-1)) %>%
    mutate(Facets=case_when(log10Evalue >10~"A",
                              log10Evalue <10 & log10Evalue >5~"B",
            log10Evalue<5~"C")) %>% 
  dplyr::filter(Facets=="A") %>% 
    ggplot(., aes (y= reorder(motif_name, log10Evalue))) +
  geom_col(aes(x=log10Evalue))+
  geom_point(aes(x=ENR_RATIO*10, color=ENR_RATIO), size =4)+
  geom_vline(
  xintercept = 1*10,
  linetype = "dotted",
  linewidth = 1, color="red")+
  scale_x_continuous(
  expand = c(0, .125),
  sec.axis = sec_axis(~ . / 10, name = "Enrichment Ratio")
)+
   scale_color_viridis_c(
    name = "Enrichment Ratio",
    option = "plasma") +
  tidytext::scale_y_reordered()+
  facet_wrap(~Facets )+
  theme_classic()+
  ylab("Enriched TF motif")+
  ggtitle(paste("SET3 enrichment over SET1\n top Enrichment Ratio by Cluster H3K27ac"))

Past versions of "set 3 by facet-1.png"

Version	Author	Date
3f3d9a4	reneeisnowhere	2026-02-02

H3K27ac_Set3_data %>% 
  dplyr::filter(EVALUE<0.05) %>% 
   group_by(CLUSTER) %>% 
  slice_min(RANK, with_ties = FALSE) %>% 
  ungroup() %>% 
   mutate(log10Evalue= log(EVALUE, base = 10)*(-1)) %>%
    mutate(Facets=case_when(log10Evalue >10~"A",
                              log10Evalue <10 & log10Evalue >5~"B",
            log10Evalue<5~"C")) %>% 
  dplyr::filter(Facets=="B") %>% 
    ggplot(., aes (y= tidytext::reorder_within(motif_name, log10Evalue, Facets))) +
  geom_col(aes(x=log10Evalue))+
  geom_point(aes(x=ENR_RATIO*5, color=ENR_RATIO), size =4)+
  geom_vline(
  xintercept = 1*5,
  linetype = "dotted",
  linewidth = 1, color="red")+
  scale_x_continuous(
  expand = c(0, .125),
  sec.axis = sec_axis(~ . / 5, name = "Enrichment Ratio")
)+ scale_color_viridis_c(
    name = "Enrichment Ratio",
    option = "plasma"
  ) +
  tidytext::scale_y_reordered()+
  facet_wrap(~Facets )+
  theme_classic()+
  ylab("Enriched TF motif")+
  ggtitle(paste("SET3 enrichment over SET1\n top Enrichment Ratio by Cluster H3K27ac"))

Past versions of "set 3 by facet-2.png"

Version	Author	Date
3f3d9a4	reneeisnowhere	2026-02-02

H3K27ac_Set3_data %>% 
dplyr::filter(EVALUE<0.05) %>% 
   group_by(CLUSTER) %>% 
  slice_min(RANK, with_ties = FALSE) %>% 
  ungroup() %>% 
   mutate(log10Evalue= log(EVALUE, base = 10)*(-1)) %>%
    mutate(Facets=case_when(log10Evalue >10~"A",
                              log10Evalue <10 & log10Evalue >5~"B",
            log10Evalue<5~"C")) %>% 
  dplyr::filter(Facets=="C") %>% 
    ggplot(., aes (y= tidytext::reorder_within(motif_name, log10Evalue, Facets))) +
  geom_col(aes(x=log10Evalue))+
  geom_point(aes(x=ENR_RATIO*.05,color= pmin(ENR_RATIO, 5)), size =4)+
  scale_x_continuous(
  expand = c(0, .125),
  sec.axis = sec_axis(~ . /.05, name = "Enrichment Ratio")
)+
   scale_color_viridis_c(
    name = "Enrichment Ratio",
    option = "plasma"
  ) +
  tidytext::scale_y_reordered()+
  facet_wrap(~Facets )+
  theme_classic()+
  ylab("Enriched TF motif")+
  ggtitle(paste("SET3 enrichment over SET1\n top Enrichment Ratio by Cluster H3K27ac"))

Past versions of "set 3 by facet-3.png"

Version	Author	Date
3f3d9a4	reneeisnowhere	2026-02-02

plot_topnum_ratio_full <- function(df, title = NULL, signif.num = 0.05,top_num=20, color_limits = NULL){
  
  ### getting the name of the data frame for plotting
 if (is.null(title)) {
    title <- deparse(substitute(df))
 }
  
   

  ### Getting the data ready
  plot_df <- df %>%
    dplyr::filter(EVALUE < signif.num) %>%
    group_by(CLUSTER) %>%
    slice_min(RANK, with_ties = FALSE) %>%
    ungroup() %>%
    mutate(log10Evalue = -log10(EVALUE)) %>%
    arrange(desc(log10Evalue)) %>%
    mutate(motif_name_wrapped = stringr::str_wrap(motif_name, width = 10)) %>% 
     mutate(
    enr_shape = ifelse(ENR_RATIO > 1, "Enriched", "Depleted")) %>% 
    slice_head(., n=top_num)
#   
  scaler <- max(plot_df$log10Evalue) / max(plot_df$ENR_RATIO)

  ##plotting the data
   ggplot(plot_df, aes(y = reorder(motif_name_wrapped, log10Evalue))) +
    geom_col(aes(x = log10Evalue)) +
    geom_point(aes(x = ENR_RATIO* scaler, color = ENR_RATIO, shape = enr_shape), size = 4)+
    scale_x_continuous(
      expand = c(0, .125),
      sec.axis = sec_axis(~ . / scaler, name = "Enrichment Ratio")
    ) +
   scale_color_viridis_c(
  name = "Enrichment Ratio",
  option = "plasma",
  limits = color_limits,
  oob = scales::squish
)+
    scale_y_discrete(labels = function(x) stringr::str_wrap(gsub("__.*$", "", x), width = 10)) +
     scale_shape_manual(values = c("Enriched" = 16, "Depleted" = 17))+
    theme_classic() +
    ylab("Enriched TF motif") +
    ggtitle(paste(title, "-", top_num))
}

plot_A <- plot_topnum_ratio_full(H3K27ac_Set3_data,signif.num = 0.05, top_num = 10)

plot_B <- plot_topnum_ratio_full(H3K27ac_Set2_data,signif.num = 0.05, top_num = 10)

aligned_plots <- cowplot::align_plots(plot_A, plot_B, align = "v", axis = "l")

cowplot::plot_grid(aligned_plots[[1]],
          aligned_plots[[2]],
          ncol = 2)

Past versions of "functional full plot-1.png"

Version	Author	Date
7840a6d	reneeisnowhere	2026-02-12

RNA filtering

RNA_full_toptable <-  readRDS("data/Other_paper_data/RNA_full_toptable.RDS")

RNA_expressed <- RNA_full_toptable %>% 
  dplyr::select(Entrez_ID, SYMBOL)

### had to add in a special filter to account for the :: in the names of the motifs
symbols <- str_to_upper(RNA_expressed$SYMBOL)

filtered_H3K27ac_Set3_data <- H3K27ac_Set3_data %>%
  ##create the motif-tokens column so I can keep names where there is a partial match in the RNA Symbols
  mutate(motif_tokens = str_split(str_to_upper(motif_name), "::")) %>%
  ##Because this is a list, now I need to filter using sapply, but then remove the motif token column
  filter(sapply(motif_tokens, function(x) any(x %in% symbols))) %>%
  select(-motif_tokens)


filtered_H3K27ac_Set2_data <- H3K27ac_Set2_data %>%
  mutate(motif_tokens = str_split(str_to_upper(motif_name), "::")) %>%
  filter(sapply(motif_tokens, function(x) any(x %in% symbols))) %>%
  select(-motif_tokens)


## binding both together to get them to set a global limit on the secondary axis using quantiles so color range is identical
global_combo <- bind_rows(filtered_H3K27ac_Set2_data, filtered_H3K27ac_Set3_data)

global_limits <-  quantile(global_combo$ENR_RATIO, probs = c(0.05, 0.95), na.rm = TRUE)
### plot seperately
  filt_A <- plot_topnum_ratio_full(filtered_H3K27ac_Set3_data,signif.num = 0.05, top_num = 10,color_limits = global_limits)
  
  filt_B <- plot_topnum_ratio_full(filtered_H3K27ac_Set2_data,signif.num = 0.05, top_num = 10,color_limits = global_limits)
 ## Good ole cowplot to align plots vertically 
  aligned_filt_plots <- cowplot::align_plots(filt_A, filt_B, align = "v", axis = "l")

cowplot::plot_grid(aligned_filt_plots[[1]],
          aligned_filt_plots[[2]],
          ncol = 2)

Past versions of "RNA filtering-1.png"

Version	Author	Date
e7a3fff	reneeisnowhere	2026-02-18

Case and Summit calls method 1, subset A and B

This section looks at the enrichment of A and B cases of each Set.
Case A is defined as all ROIs with an LFC > 0 at each timepoint. Case B is defined as all ROIs with an LFC < 0 at each timepoint. Case C is defined as all other ROIs. The List of ROI summits was filtered for ROI that fit these cases, and enrichment was done using xstreme on TACC for each set-case compared to all of set1.

Because I have so many sets, I am now creating a function to import/visualize each section:

import_function <- function(set_description, base_dir = "C:/Users/renee/Other_projects_data/DXR_data/H3K27ac") {
  
  sea_disc_out <-read_delim(
    file.path(base_dir, set_description, "sea_disc_out", "sea.tsv"),
    delim = "\t", trim_ws = TRUE
  ) %>%
    mutate(source = "disc") %>%
    slice(1:(dplyr::n() - 3))

  sea_known <-read_delim(
    file.path(base_dir, set_description, "sea_out", "sea.tsv"),
    delim = "\t", trim_ws = TRUE
  ) %>%
    mutate(source = "known") %>%
    slice(1:(dplyr::n() - 3))


  xstreme <- read_delim(
    file.path(base_dir, set_description, "xstreme.tsv"),
    delim = "\t", trim_ws = TRUE
  ) %>%
    mutate(source = "all") %>%
    slice(1:(dplyr::n() - 3))


 #### adding in later fuctions
  tomtom <- read_delim(
    file.path(base_dir, set_description, "streme_tomtom_out", "tomtom.tsv"),
    delim = "\t", trim_ws = TRUE
  )
### function to renormalize dataframes before the join
  
  clean_consensus <- function(x) {
  stringr::str_remove(x, "^\\d+-")
}
bind_df <- bind_rows(sea_disc_out, sea_known) %>% 
   mutate(CONSENSUS = clean_consensus(CONSENSUS)) %>%
  dplyr::select(DB:ENR_RATIO) %>% 
  distinct(ID, ALT_ID, ENR_RATIO, .keep_all = TRUE)



set_data <- xstreme %>% 
   mutate(CONSENSUS = clean_consensus(CONSENSUS)) %>%
  dplyr::select(RANK:CLUSTER,ID:CONSENSUS,EVALUE,SIM_MOTIF,MOTIF_URL) %>% 
  mutate(MOTIF_URL=str_replace(MOTIF_URL,"https://jaspar2024.elixir.no/matrix/","")) %>% 
  mutate(motif_name=case_when(
    str_detect(SIM_MOTIF, "\\(") ~ str_extract(SIM_MOTIF, "(?<=\\().+?(?=\\))"),
    str_detect(SIM_MOTIF, "^MA\\d+\\.\\d+") ~ ALT_ID,
    str_detect(SIM_MOTIF, "^\\d+-") ~ str_replace(SIM_MOTIF, "^\\d+-", ""),
  TRUE ~ SIM_MOTIF)) %>% 
  left_join(bind_df,by = c("ALT_ID", 
                           "ID","CONSENSUS")) %>% 
  mutate(diff_per=`TP%` -`FP%`)

return(list(
  sea = bind_df,
  xstreme = set_data))

}

H3K27ac_set2_A<- import_function("H3K27ac_set2_A_400",base_dir = "C:/Users/renee/Other_projects_data/DXR_data/H3K27ac")

H3K27ac_set2_B<- import_function("H3K27ac_set2_B_400",base_dir = "C:/Users/renee/Other_projects_data/DXR_data/H3K27ac")
H3K27ac_set3_A<- import_function("H3K27ac_set3_A_400",base_dir = "C:/Users/renee/Other_projects_data/DXR_data/H3K27ac")
H3K27ac_set3_B<- import_function("H3K27ac_set3_B_400",base_dir = "C:/Users/renee/Other_projects_data/DXR_data/H3K27ac")

DT::datatable((H3K27ac_set2_A$xstreme %>% 
  dplyr::select(RANK,CLUSTER,ID,ALT_ID,EVALUE, CONSENSUS)),
  rownames = FALSE,
  caption = htmltools::tags$caption(
    style = "caption-side: top; text-align: left; font-weight: bold;",
    "Method 1: Set 2A H3K27ac"
  ),
  filter = 'top',       # add filter/search boxes
  options = list(
    pageLength = 10,
    autoWidth = FALSE,
    scrollX = TRUE)) 

###Code below for testing issues in the function.  this helped fix the consensus .x .y issue.
# all(rest_test$xstreme$CONSENSUS.x == rest_test$xstreme$CONSENSUS.y, na.rm = TRUE)
# 
# rest_test$xstreme%>%
#   summarise(
#     n_total = dplyr::n(),
#     n_match = sum(CONSENSUS.x == CONSENSUS.y, na.rm = TRUE),
#     n_diff  = sum(CONSENSUS.x != CONSENSUS.y, na.rm = TRUE)
#   )

DT::datatable((H3K27ac_set2_B$xstreme %>% 
  dplyr::select(RANK,CLUSTER,ID,ALT_ID,EVALUE, CONSENSUS)),
  rownames = FALSE,
  caption = htmltools::tags$caption(
    style = "caption-side: top; text-align: left; font-weight: bold;",
    "Method 1: Set 2B H3K27ac"
  ),
  filter = 'top',       # add filter/search boxes
  options = list(
    pageLength = 10,
    autoWidth = FALSE,
    scrollX = TRUE)) 

DT::datatable((H3K27ac_set3_A$xstreme %>% 
  dplyr::select(RANK,CLUSTER,ID,ALT_ID,EVALUE, CONSENSUS)),
  rownames = FALSE,
  caption = htmltools::tags$caption(
    style = "caption-side: top; text-align: left; font-weight: bold;",
    "Method 1: Set 3A H3K27ac"
  ),
  filter = 'top',       # add filter/search boxes
  options = list(
    pageLength = 10,
    autoWidth = FALSE,
    scrollX = TRUE)) 

DT::datatable((H3K27ac_set3_B$xstreme %>% 
  dplyr::select(RANK,CLUSTER,ID,ALT_ID,EVALUE, CONSENSUS)),
  rownames = FALSE,
  caption = htmltools::tags$caption(
    style = "caption-side: top; text-align: left; font-weight: bold;",
    "Method 1: Set 3B H3K27ac"
  ),
  filter = 'top',       # add filter/search boxes
  options = list(
    pageLength = 10,
    autoWidth = FALSE,
    scrollX = TRUE)) 

plot_ENR_RATIO <- function(df, title = NULL, signif.num = 0.05, page = 1){
  
  ### getting the name of the data frame for plotting
 if (is.null(title)) {
    title <- deparse(substitute(df))
  }

  ### Getting the data ready
  plot_df <- df$xstreme %>%
    dplyr::filter(EVALUE < signif.num) %>%
    group_by(CLUSTER) %>%
    slice_min(RANK, with_ties = FALSE) %>%
    ungroup() %>%
    mutate(log10Evalue = -log10(EVALUE)) %>%
    arrange(desc(log10Evalue)) %>%
    mutate(Facets = cut(
      log10Evalue,
      breaks = quantile(log10Evalue, probs = c(0, 0.33, 0.66, 1), na.rm = TRUE),
      labels = c("Low", "Medium", "High"),
      include.lowest = TRUE
    )) %>% 
    mutate(motif_name_wrapped = stringr::str_wrap(motif_name, width = 10)) %>% 
     mutate(
    enr_shape = ifelse(ENR_RATIO > 1, "Enriched", "Depleted")
  )
  
  scaler <- max(plot_df$log10Evalue) / max(plot_df$ENR_RATIO)
  facet_levels <- levels(plot_df$Facets)
if(page > length(facet_levels)) stop("page number exceeds available facets")
facet_name <- facet_levels[page]
  ##plotting the data
   ggplot(plot_df, aes(y = tidytext::reorder_within(motif_name, log10Evalue, Facets))) +
    geom_col(aes(x = log10Evalue)) +
    geom_point(aes(x = ENR_RATIO * scaler, color = ENR_RATIO, shape = enr_shape), size = 4)+
    scale_x_continuous(
      expand = c(0, .125),
      sec.axis = sec_axis(~ . / scaler, name = "Enrichment Ratio")
    ) +
    scale_color_viridis_c(name = "Enrichment Ratio", option = "plasma") +
    scale_y_discrete(labels = function(x) stringr::str_wrap(gsub("__.*$", "", x), width = 10)) +
    ggforce::facet_wrap_paginate(
      ~Facets,
      ncol = 1,
      nrow = 1,
      page = page,
      scales = "free_y"
    ) +
     scale_shape_manual(values = c("Enriched" = 16, "Depleted" = 17))+
    theme_classic() +
    ylab("Enriched TF motif") +
    ggtitle(paste(title, "-", facet_name))
}
########################################################
plot_topnum_RATIO <- function(df, title = NULL, signif.num = 0.05,top_num=20){
  
  ### getting the name of the data frame for plotting
 if (is.null(title)) {
    title <- deparse(substitute(df))
  }

  ### Getting the data ready
  plot_df <- df$xstreme %>%
    dplyr::filter(EVALUE < signif.num) %>%
    group_by(CLUSTER) %>%
    slice_min(RANK, with_ties = FALSE) %>%
    ungroup() %>%
    mutate(log10Evalue = -log10(EVALUE)) %>%
    arrange(desc(log10Evalue)) %>%
    mutate(motif_name_wrapped = stringr::str_wrap(motif_name, width = 10)) %>% 
     mutate(
    enr_shape = ifelse(ENR_RATIO > 1, "Enriched", "Depleted")) %>% 
    slice_head(., n=top_num)
#   
  scaler <- max(plot_df$log10Evalue) / max(plot_df$ENR_RATIO)

  ##plotting the data
   ggplot(plot_df, aes(y = reorder(motif_name, log10Evalue))) +
    geom_col(aes(x = log10Evalue)) +
    geom_point(aes(x = ENR_RATIO* scaler, color = ENR_RATIO, shape = enr_shape), size = 4)+
    scale_x_continuous(
      expand = c(0, .125),
      sec.axis = sec_axis(~ . / scaler, name = "Enrichment Ratio")
    ) +
    scale_color_viridis_c(name = "Enrichment Ratio", option = "plasma") +
    scale_y_discrete(labels = function(x) stringr::str_wrap(gsub("__.*$", "", x), width = 10)) +
     scale_shape_manual(values = c("Enriched" = 16, "Depleted" = 17))+
    theme_classic() +
    ylab("Enriched TF motif") +
    ggtitle(paste(title, "-", top_num))
}

plot_ENR_RATIO(H3K27ac_set2_A, signif.num = 0.05, page = 3)

Past versions of unnamed-chunk-5-1.png

Version	Author	Date
7840a6d	reneeisnowhere	2026-02-12
78269d9	reneeisnowhere	2026-02-09

plot_ENR_RATIO(H3K27ac_set2_A, signif.num = 0.05, page = 2)

Past versions of unnamed-chunk-5-2.png

Version	Author	Date
7840a6d	reneeisnowhere	2026-02-12
78269d9	reneeisnowhere	2026-02-09

plot_ENR_RATIO(H3K27ac_set2_A, signif.num = 0.05, page = 1)

Past versions of unnamed-chunk-5-3.png

Version	Author	Date
7840a6d	reneeisnowhere	2026-02-12

plot_ENR_RATIO(H3K27ac_set2_B, signif.num = 0.05, page = 3)

Past versions of unnamed-chunk-5-4.png

Version	Author	Date
7840a6d	reneeisnowhere	2026-02-12

plot_ENR_RATIO(H3K27ac_set2_B, signif.num = 0.05, page = 2)

Past versions of unnamed-chunk-5-5.png

Version	Author	Date
7840a6d	reneeisnowhere	2026-02-12

plot_ENR_RATIO(H3K27ac_set2_B, signif.num = 0.05, page = 1)

Past versions of unnamed-chunk-5-6.png

Version	Author	Date
7840a6d	reneeisnowhere	2026-02-12

# plot_topnum_RATIO(H3K27ac_set2_A, signif.num = 0.05, top_num = 10)
# 
# plot_topnum_RATIO(H3K27ac_Set3_data,signif.num = 0.05, top_num = 10)

now for plotting Set 3 A and B

plot_ENR_RATIO(H3K27ac_set3_A, signif.num = 0.05, page = 3)

Past versions of "plotting set3-1.png"

Version	Author	Date
4392e80	reneeisnowhere	2026-02-09
78269d9	reneeisnowhere	2026-02-09

plot_ENR_RATIO(H3K27ac_set3_A, signif.num = 0.05, page = 2)

Past versions of "plotting set3-2.png"

Version	Author	Date
4392e80	reneeisnowhere	2026-02-09
78269d9	reneeisnowhere	2026-02-09

plot_ENR_RATIO(H3K27ac_set3_A, signif.num = 0.05, page = 1)

Past versions of "plotting set3-3.png"

Version	Author	Date
4392e80	reneeisnowhere	2026-02-09
78269d9	reneeisnowhere	2026-02-09

plot_ENR_RATIO(H3K27ac_set3_B, signif.num = 0.05, page = 3)

Past versions of "plotting set3-4.png"

Version	Author	Date
4392e80	reneeisnowhere	2026-02-09
78269d9	reneeisnowhere	2026-02-09

plot_ENR_RATIO(H3K27ac_set3_B, signif.num = 0.05, page = 2)

Past versions of "plotting set3-5.png"

Version	Author	Date
4392e80	reneeisnowhere	2026-02-09
78269d9	reneeisnowhere	2026-02-09

plot_ENR_RATIO(H3K27ac_set3_B, signif.num = 0.05, page = 1)

Past versions of "plotting set3-6.png"

Version	Author	Date
4392e80	reneeisnowhere	2026-02-09
78269d9	reneeisnowhere	2026-02-09

Summit calls method 2

H3K27ac_Set2_met2_sea_disc_out <-read_delim("C:/Users/renee/Other_projects_data/DXR_data/H3K27ac/H3K27ac_set2_400_alt/sea_disc_out/sea.tsv", delim = "\t", escape_double = FALSE,     trim_ws = TRUE) %>% mutate(source="disc") %>% slice_head(n = length(.$ID)-3)

H3K27ac_Set2_met2_sea_known <-read_delim("C:/Users/renee/Other_projects_data/DXR_data/H3K27ac/H3K27ac_set2_400_alt/sea_out/sea.tsv", delim = "\t", escape_double = FALSE,     trim_ws = TRUE) %>% mutate(source="known") %>% slice_head(n = length(.$ID)-3)

H3K27ac_Set2_met2_xstreme <- read_delim("C:/Users/renee/Other_projects_data/DXR_data/H3K27ac/H3K27ac_set2_400_alt/xstreme.tsv", delim = "\t", escape_double = FALSE,     trim_ws = TRUE) %>% mutate(source="all") %>% slice_head(n = length(.$ID)-3)


H3K27ac_Set2_met2_tomtom <- read_delim("C:/Users/renee/Other_projects_data/DXR_data/H3K27ac/H3K27ac_set2_400_alt/streme_tomtom_out/tomtom.tsv", 
    delim = "\t", escape_double = FALSE, 
    trim_ws = TRUE)

test_bind_met2 <- bind_rows(H3K27ac_Set2_met2_sea_disc_out, H3K27ac_Set2_met2_sea_known) %>% 
  dplyr::select(DB:ENR_RATIO) %>% 
  group_by(ID,ALT_ID, ENR_RATIO) %>% distinct()

H3K27ac_Set3_met2_sea_disc_out <-read_delim("C:/Users/renee/Other_projects_data/DXR_data/H3K27ac/H3K27ac_set3_400_alt/sea_disc_out/sea.tsv", delim = "\t", escape_double = FALSE,     trim_ws = TRUE) %>% mutate(source="disc") %>% slice_head(n = length(.$ID)-3)

H3K27ac_Set3_met2_sea_known <-read_delim("C:/Users/renee/Other_projects_data/DXR_data/H3K27ac/H3K27ac_set3_400_alt/sea_out/sea.tsv", delim = "\t", escape_double = FALSE,     trim_ws = TRUE) %>% mutate(source="known") %>% slice_head(n = length(.$ID)-3)

H3K27ac_Set3_met2_xstreme <- read_delim("C:/Users/renee/Other_projects_data/DXR_data/H3K27ac/H3K27ac_set3_400_alt/xstreme.tsv", delim = "\t", escape_double = FALSE,     trim_ws = TRUE) %>% mutate(source="all") %>% slice_head(n = length(.$ID)-3)


H3K27ac_Set3_met2_tomtom <- read_delim("C:/Users/renee/Other_projects_data/DXR_data/H3K27ac/H3K27ac_set3_400_alt/streme_tomtom_out/tomtom.tsv", 
    delim = "\t", escape_double = FALSE, 
    trim_ws = TRUE)

test_bind3_met2 <-bind_rows(H3K27ac_Set3_met2_sea_disc_out, H3K27ac_Set3_met2_sea_known) %>%
  dplyr::select(DB:ENR_RATIO) %>% 
  group_by(ID,ALT_ID) %>% 
  distinct()

H3K27ac_Set2_data_met2 <- H3K27ac_Set2_met2_xstreme %>% 
  dplyr::select(RANK:CLUSTER,ID:CONSENSUS,EVALUE,SIM_MOTIF,MOTIF_URL) %>% 
  mutate(MOTIF_URL=str_replace(MOTIF_URL,"https://jaspar2024.elixir.no/matrix/","")) %>% 
  mutate(motif_name=case_when(
    str_detect(SIM_MOTIF, "\\(") ~ str_extract(SIM_MOTIF, "(?<=\\().+?(?=\\))"),
    str_detect(SIM_MOTIF, "^MA\\d+\\.\\d+") ~ ALT_ID,
    str_detect(SIM_MOTIF, "^\\d+-") ~ str_replace(SIM_MOTIF, "^\\d+-", ""),
  TRUE ~ SIM_MOTIF)) %>% 
  left_join(test_bind_met2) %>% 
  mutate(diff_per=`TP%` -`FP%`)

H3K27ac_Set3_data_met2 <- H3K27ac_Set3_met2_xstreme %>% 
  dplyr::select(RANK:CLUSTER,ID:CONSENSUS,EVALUE,SIM_MOTIF,MOTIF_URL) %>% 
  mutate(MOTIF_URL=str_replace(MOTIF_URL,"https://jaspar2024.elixir.no/matrix/","")) %>% 
  mutate(motif_name=case_when(
    str_detect(SIM_MOTIF, "\\(") ~ str_extract(SIM_MOTIF, "(?<=\\().+?(?=\\))"),
    str_detect(SIM_MOTIF, "^MA\\d+\\.\\d+") ~ ALT_ID,
    str_detect(SIM_MOTIF, "^\\d+-") ~ str_replace(SIM_MOTIF, "^\\d+-", ""),
  TRUE ~ SIM_MOTIF)) %>% 
  left_join(test_bind3_met2, by=c("ID"="ID","ALT_ID"="ALT_ID")) %>% 
  mutate(diff_per=`TP%` -`FP%`)

# test_bind
# xstreme_rank_bind
DT::datatable((H3K27ac_Set2_data_met2 %>% 
  dplyr::select(RANK,CLUSTER,ID,ALT_ID,EVALUE, CONSENSUS)),
  rownames = FALSE,
  caption = htmltools::tags$caption(
    style = "caption-side: top; text-align: left; font-weight: bold;",
    "Method 2: Set 2 H3K27ac"
  ),
  filter = 'top',       # add filter/search boxes
  options = list(
    pageLength = 10,
    autoWidth = FALSE,
    scrollX = TRUE)) 

DT::datatable((H3K27ac_Set3_data_met2 %>% 
  dplyr::select(RANK,CLUSTER,ID,ALT_ID,EVALUE, CONSENSUS.x)),
  rownames = FALSE,
  caption = htmltools::tags$caption(
    style = "caption-side: top; text-align: left; font-weight: bold;",
    "Method 2: Set 3 H3K27ac"
  ),
  filter = 'top',       # add filter/search boxes
  options = list(
    pageLength = 10,
    autoWidth = FALSE,
    scrollX = TRUE)) 

Summit calls method 3

H3K27ac_Set2_met3_sea_disc_out <-read_delim("C:/Users/renee/Other_projects_data/DXR_data/H3K27ac/H3K27ac_set2_400_alt_concat/sea_disc_out/sea.tsv", delim = "\t", escape_double = FALSE,     trim_ws = TRUE) %>% mutate(source="disc") %>% slice_head(n = length(.$ID)-3)

H3K27ac_Set2_met3_sea_known <-read_delim("C:/Users/renee/Other_projects_data/DXR_data/H3K27ac/H3K27ac_set2_400_alt_concat/sea_out/sea.tsv", delim = "\t", escape_double = FALSE,     trim_ws = TRUE) %>% mutate(source="known") %>% slice_head(n = length(.$ID)-3)

H3K27ac_Set2_met3_xstreme <- read_delim("C:/Users/renee/Other_projects_data/DXR_data/H3K27ac/H3K27ac_set2_400_alt_concat/xstreme.tsv", delim = "\t", escape_double = FALSE,     trim_ws = TRUE) %>% mutate(source="all") %>% slice_head(n = length(.$ID)-3)


H3K27ac_Set2_met3_tomtom <- read_delim("C:/Users/renee/Other_projects_data/DXR_data/H3K27ac/H3K27ac_set2_400_alt_concat/streme_tomtom_out/tomtom.tsv", 
    delim = "\t", escape_double = FALSE, 
    trim_ws = TRUE)

test_bind_met3 <- bind_rows(H3K27ac_Set2_met3_sea_disc_out, H3K27ac_Set2_met3_sea_known) %>% 
  dplyr::select(DB:ENR_RATIO) %>% 
  group_by(ID,ALT_ID, ENR_RATIO) %>% distinct()

H3K27ac_Set3_met3_sea_disc_out <-read_delim("C:/Users/renee/Other_projects_data/DXR_data/H3K27ac/H3K27ac_set3_400_alt_concat/sea_disc_out/sea.tsv", delim = "\t", escape_double = FALSE,     trim_ws = TRUE) %>% mutate(source="disc") %>% slice_head(n = length(.$ID)-3)

H3K27ac_Set3_met3_sea_known <-read_delim("C:/Users/renee/Other_projects_data/DXR_data/H3K27ac/H3K27ac_set3_400_alt_concat/sea_out/sea.tsv", delim = "\t", escape_double = FALSE,     trim_ws = TRUE) %>% mutate(source="known") %>% slice_head(n = length(.$ID)-3)

H3K27ac_Set3_met3_xstreme <- read_delim("C:/Users/renee/Other_projects_data/DXR_data/H3K27ac/H3K27ac_set3_400_alt_concat/xstreme.tsv", delim = "\t", escape_double = FALSE,     trim_ws = TRUE) %>% mutate(source="all") %>% slice_head(n = length(.$ID)-3)


H3K27ac_Set3_met3_tomtom <- read_delim("C:/Users/renee/Other_projects_data/DXR_data/H3K27ac/H3K27ac_set3_400_alt_concat/streme_tomtom_out/tomtom.tsv", 
    delim = "\t", escape_double = FALSE, 
    trim_ws = TRUE)

test_bind3_met3 <-bind_rows(H3K27ac_Set3_met3_sea_disc_out, H3K27ac_Set3_met3_sea_known) %>%
  dplyr::select(DB:ENR_RATIO) %>% 
  group_by(ID,ALT_ID) %>% 
  distinct()

H3K27ac_Set2_data_met3 <- H3K27ac_Set2_met3_xstreme %>% 
  dplyr::select(RANK:CLUSTER,ID:CONSENSUS,EVALUE,SIM_MOTIF,MOTIF_URL) %>% 
  mutate(MOTIF_URL=str_replace(MOTIF_URL,"https://jaspar2024.elixir.no/matrix/","")) %>% 
  mutate(motif_name=case_when(
    str_detect(SIM_MOTIF, "\\(") ~ str_extract(SIM_MOTIF, "(?<=\\().+?(?=\\))"),
    str_detect(SIM_MOTIF, "^MA\\d+\\.\\d+") ~ ALT_ID,
    str_detect(SIM_MOTIF, "^\\d+-") ~ str_replace(SIM_MOTIF, "^\\d+-", ""),
  TRUE ~ SIM_MOTIF)) %>% 
  left_join(test_bind_met3) %>% 
  mutate(diff_per=`TP%` -`FP%`)

H3K27ac_Set3_data_met3 <- H3K27ac_Set3_met3_xstreme %>% 
  dplyr::select(RANK:CLUSTER,ID:CONSENSUS,EVALUE,SIM_MOTIF,MOTIF_URL) %>% 
  mutate(MOTIF_URL=str_replace(MOTIF_URL,"https://jaspar2024.elixir.no/matrix/","")) %>% 
  mutate(motif_name=case_when(
    str_detect(SIM_MOTIF, "\\(") ~ str_extract(SIM_MOTIF, "(?<=\\().+?(?=\\))"),
    str_detect(SIM_MOTIF, "^MA\\d+\\.\\d+") ~ ALT_ID,
    str_detect(SIM_MOTIF, "^\\d+-") ~ str_replace(SIM_MOTIF, "^\\d+-", ""),
  TRUE ~ SIM_MOTIF)) %>% 
  left_join(test_bind3_met3, by=c("ID"="ID","ALT_ID"="ALT_ID")) %>% 
  mutate(diff_per=`TP%` -`FP%`)

# test_bind
# xstreme_rank_bind
DT::datatable((H3K27ac_Set2_data_met3 %>% 
  dplyr::select(RANK,CLUSTER,ID,ALT_ID,EVALUE, CONSENSUS)),
  rownames = FALSE,
  caption = htmltools::tags$caption(
    style = "caption-side: top; text-align: left; font-weight: bold;",
    "Method 3: Set 2 H3K27ac"
  ),
  filter = 'top',       # add filter/search boxes
  options = list(
    pageLength = 10,
    autoWidth = FALSE,
    scrollX = TRUE)) 

DT::datatable((H3K27ac_Set3_data_met3 %>% 
  dplyr::select(RANK,CLUSTER,ID,ALT_ID,EVALUE, CONSENSUS.x)),
  rownames = FALSE,
  caption = htmltools::tags$caption(
    style = "caption-side: top; text-align: left; font-weight: bold;",
    "Method 3: Set 3 H3K27ac"
  ),
  filter = 'top',       # add filter/search boxes
  options = list(
    pageLength = 10,
    autoWidth = FALSE,
    scrollX = TRUE)) 

toplist_direct_set2 <- list("set2_met1"=H3K27ac_Set2_data$ALT_ID,
"set2_met2"=H3K27ac_Set2_data_met2$ALT_ID,
"set2_met3"=H3K27ac_Set2_data_met3$ALT_ID)

toplist_direct_set3 <- list("set3_met1"=H3K27ac_Set3_data$ALT_ID,
"set3_met2"=H3K27ac_Set3_data_met2$ALT_ID,
"set3_met3"=H3K27ac_Set3_data_met3$ALT_ID)

 Shared_motifs_set2 <- Reduce(intersect, toplist_direct_set2)
ggVennDiagram::ggVennDiagram(toplist_direct_set2)+scale_fill_gradient(
    low = "white",
    high = "blue"
  )

Past versions of unnamed-chunk-6-1.png

Version	Author	Date
7840a6d	reneeisnowhere	2026-02-12

 Shared_motifs_set3 <- Reduce(intersect, toplist_direct_set3)
ggVennDiagram::ggVennDiagram(toplist_direct_set3)+scale_fill_gradient(
    low = "white",
    high = "red"
  )

Past versions of unnamed-chunk-6-2.png

Version	Author	Date
7840a6d	reneeisnowhere	2026-02-12

Session information

sessionInfo()

R version 4.4.2 (2024-10-31 ucrt)
Platform: x86_64-w64-mingw32/x64
Running under: Windows 11 x64 (build 26200)

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] grid      stats4    stats     graphics  grDevices utils     datasets 
[8] methods   base     

other attached packages:
 [1] DT_0.33              rtracklayer_1.66.0   genomation_1.38.0   
 [4] plyranges_1.26.0     GenomicRanges_1.58.0 GenomeInfoDb_1.42.3 
 [7] IRanges_2.40.1       S4Vectors_0.44.0     BiocGenerics_0.52.0 
[10] lubridate_1.9.4      forcats_1.0.0        stringr_1.5.1       
[13] dplyr_1.1.4          purrr_1.1.0          readr_2.1.5         
[16] tidyr_1.3.1          tibble_3.3.0         ggplot2_3.5.2       
[19] tidyverse_2.0.0      workflowr_1.7.1     

loaded via a namespace (and not attached):
  [1] bitops_1.0-9                rlang_1.1.6                
  [3] magrittr_2.0.3              git2r_0.36.2               
  [5] gridBase_0.4-7              tidytext_0.4.3             
  [7] matrixStats_1.5.0           compiler_4.4.2             
  [9] getPass_0.2-4               callr_3.7.6                
 [11] vctrs_0.6.5                 reshape2_1.4.4             
 [13] pkgconfig_2.0.3             crayon_1.5.3               
 [15] fastmap_1.2.0               XVector_0.46.0             
 [17] labeling_0.4.3              Rsamtools_2.22.0           
 [19] promises_1.3.3              rmarkdown_2.29             
 [21] tzdb_0.5.0                  UCSC.utils_1.2.0           
 [23] ps_1.9.1                    bit_4.6.0                  
 [25] xfun_0.52                   zlibbioc_1.52.0            
 [27] cachem_1.1.0                jsonlite_2.0.0             
 [29] SnowballC_0.7.1             later_1.4.2                
 [31] DelayedArray_0.32.0         tweenr_2.0.3               
 [33] BiocParallel_1.40.2         parallel_4.4.2             
 [35] R6_2.6.1                    bslib_0.9.0                
 [37] stringi_1.8.7               RColorBrewer_1.1-3         
 [39] jquerylib_0.1.4             Rcpp_1.1.0                 
 [41] SummarizedExperiment_1.36.0 knitr_1.50                 
 [43] httpuv_1.6.16               Matrix_1.7-3               
 [45] timechange_0.3.0            tidyselect_1.2.1           
 [47] rstudioapi_0.17.1           dichromat_2.0-0.1          
 [49] abind_1.4-8                 yaml_2.3.10                
 [51] seqPattern_1.38.0           ggVennDiagram_1.5.4        
 [53] codetools_0.2-20            curl_7.0.0                 
 [55] processx_3.8.6              lattice_0.22-7             
 [57] plyr_1.8.9                  Biobase_2.66.0             
 [59] withr_3.0.2                 evaluate_1.0.5             
 [61] polyclip_1.10-7             Biostrings_2.74.1          
 [63] pillar_1.11.0               janeaustenr_1.0.0          
 [65] MatrixGenerics_1.18.1       whisker_0.4.1              
 [67] KernSmooth_2.23-26          generics_0.1.4             
 [69] vroom_1.6.5                 rprojroot_2.1.1            
 [71] RCurl_1.98-1.17             hms_1.1.3                  
 [73] scales_1.4.0                glue_1.8.0                 
 [75] tools_4.4.2                 BiocIO_1.16.0              
 [77] tokenizers_0.3.0            data.table_1.17.8          
 [79] BSgenome_1.74.0             GenomicAlignments_1.42.0   
 [81] fs_1.6.6                    XML_3.99-0.18              
 [83] cowplot_1.2.0               impute_1.80.0              
 [85] plotrix_3.8-4               crosstalk_1.2.2            
 [87] colorspace_2.1-1            GenomeInfoDbData_1.2.13    
 [89] ggforce_0.5.0               restfulr_0.0.16            
 [91] cli_3.6.5                   viridisLite_0.4.2          
 [93] S4Arrays_1.6.0              gtable_0.3.6               
 [95] sass_0.4.10                 digest_0.6.37              
 [97] SparseArray_1.6.2           htmlwidgets_1.6.4          
 [99] rjson_0.2.23                farver_2.1.2               
[101] htmltools_0.5.8.1           lifecycle_1.0.4            
[103] httr_1.4.7                  MASS_7.3-65                
[105] bit64_4.6.0-1