Figure 3
ERM
2023-07-07
Last updated: 2023-07-07
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Knit directory: Cardiotoxicity/
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library(car)
library(tidyverse)
library(BiocGenerics)
library(data.table)
library(cowplot)
library(ggsignif)
library(RColorBrewer)
library(broom)level_order2 <- c('75','87','77','79','78','71')
drug_palexpand <- c("#41B333","#8B006D","#DF707E","#F1B72B", "#3386DD","#707031","purple3","darkgreen", "darkblue")
#named colors: dark pink,Red,yellow,blue, dark grey, green(green is always control, may need to move pal around)
calcium_data <- readRDS("data/calcium_data.RDS")
clamp_summary <- readRDS("data/clamp_summary.RDS")Figure 2
Calcium dysregulation occurs at sub-lethal concentrations of TOP2i
A. Representative line graph of individual 3
drug_pal_fact <- c("#8B006D","#DF707E","#F1B72B", "#3386DD","#707031","#41B333")
Normalization_And_Set_File <- function(file_path) {
# Read in the data from the file
CALIMA_obj <- read.csv(file_path)
# Normalize the data
ROI_cut <- CALIMA_obj[,2:ncol(CALIMA_obj)]
ROI_cut_rowmeans <- rowMeans(ROI_cut)
Intensity <- (ROI_cut_rowmeans/min(ROI_cut_rowmeans))
Final_ROI <- tibble::as_tibble(cbind(CALIMA_obj[,1], Intensity, ROI_cut))
Final_ROI$Intensity <- Final_ROI$Intensity -1
return(Final_ROI)
}
Plot_Line_df <- function(directory) {
holder <- list()
# List CSV files in the folder that is output from CALIMA
file_list <- list.files(directory, pattern = "*.csv", full.names = TRUE)
file_list <- file_list %>% as.tibble() %>%
mutate(filenames=value) %>%
separate(filenames, c(NA,NA,NA,"file"), sep="/") %>%
separate(file, c("Drug","indv"))
# Loop over all files in directory
for (i in 1:length(file_list$value)) {
normalized_data <- data.frame("indv"=file_list$indv[i], "drug"=file_list$Drug[i])
# Normalize the data from the file
norm_out <- Normalization_And_Set_File(file_list$value[i])
holder[[file_list$Drug[i]]] <- cbind(normalized_data,norm_out[,1:2])
# Return the plot
}
return(holder)
}plot_77 <- Plot_Line_df("data/CALIMA_Data/77-1/")
df_77forplot <- plot_77 %>%
bind_rows() %>%
mutate(drug=factor(drug, levels = c( "DOX",
"EPI",
"DNR",
"MTX",
"TRZ",
"VEH"))) %>%
rename("Xaxis"=`CALIMA_obj[, 1]`)
Line_plot3<- ggplot(df_77forplot, aes(x=Xaxis, y= Intensity, group=drug))+
geom_line(size=1.5,aes(color=drug))+
xlab("")+
theme_bw()+
guides(color=guide_legend(override.aes = list(size=1)))+
ggtitle("Individual 3")+
scale_x_continuous(expand = c(0, 0))+
scale_color_manual(values=drug_pal_fact,name=" ")+
theme(plot.title = element_text(size=14,hjust = 0.5),
axis.title = element_text(size = 10, color = "black"),
axis.ticks = element_line(linewidth = 1),
legend.position="right",
axis.line = element_line(linewidth = 1),
axis.text = element_text(size = 10, color = "black", angle = 0),
strip.text.x = element_text(size = 12, color = "black", face = "bold"))
Line_plot3 
nlLine_plot3 <- Line_plot3+theme(legend.position = "none")B. Mean amplitude
MA_plot <- clamp_summary %>%
dplyr::select(Drug,Conc,indv,Mean_Amplitude) %>%
ggplot(.,aes(Drug,Mean_Amplitude))+
geom_boxplot(position = "identity", fill= drug_pal_fact)+
geom_point(aes(col=indv, size=2, alpha=0.5))+
guides(size = "none",alpha="none",colour = "none")+
scale_color_brewer(palette = "Dark2", name = "Individual",label=c("2","3","5"))+
geom_signif(comparisons = list(c("VEH","TRZ"),
c("VEH","MTX"),
c( "VEH","DNR"),
c("VEH","EPI"),
c( "VEH","DOX")),
test = "t.test",
map_signif_level = TRUE,
step_increase = 0.1,
textsize = 3)+
ylab( "a.u.")+
xlab(" ")+
ggtitle("Mean amplitude")+
theme_classic()+
theme(plot.title = element_text(siz=12,hjust = 0.5),
axis.title = element_text(size = 12, color = "black"),
axis.ticks = element_line(linewidth = 1.0),
axis.line = element_line(linewidth = 1.0),
axis.text = element_text(size = 12, color = "black", angle = 0),
strip.text.x = element_text(size = 12, color = "black", face = "bold"))
MA_plot
C. Rising slope
RS_plot <- clamp_summary %>%
dplyr::select(Drug,Conc,indv,Rise_Slope) %>%
ggplot(.,aes(Drug,Rise_Slope))+
geom_boxplot(position = "identity", fill= drug_pal_fact)+
geom_boxplot(position = "identity", fill= drug_pal_fact)+
geom_point(aes(col=indv, size=2, alpha=0.5))+
guides(size = "none",alpha="none",colour = "none")+
scale_color_brewer(palette = "Dark2", name = "Individual",label=c("2","3","5"))+
geom_signif(comparisons = list(c("VEH","TRZ"),
c("VEH","MTX"),
c( "VEH","DNR"),
c("VEH","EPI"),
c( "VEH","DOX")),
test = "t.test",
map_signif_level = TRUE,
step_increase = 0.1,
textsize = 3)+
ylab("a.u./ sec")+
xlab(" ")+
theme_classic()+
ggtitle("Rising slope")+
theme_classic()+
theme(plot.title = element_text(siz=12,hjust = 0.5),
axis.title = element_text(size = 12, color = "black"),
axis.ticks = element_line(linewidth = 1.0),
axis.line = element_line(linewidth = 1.0),
axis.text = element_text(size = 12, color = "black", angle = 0),
strip.text.x = element_text(size = 12, color = "black", face = "bold"))
RS_plot
D. Decay slope
Decay_plot <- clamp_summary %>%
dplyr::select(Drug,Conc,indv,Decay_Slope) %>%
ggplot(.,aes(Drug,Decay_Slope))+
geom_boxplot(position = "identity", fill= drug_pal_fact)+
geom_point(aes(col=indv, size=2, alpha=0.5))+
guides(size = "none",alpha="none",colour = "none")+
scale_color_brewer(palette = "Dark2", name = "Individual",label=c("2","3","5"))+
geom_signif(comparisons = list(c("VEH","TRZ"),
c("VEH","MTX"),
c( "VEH","DNR"),
c("VEH","EPI"),
c( "VEH","DOX")),
test = "t.test",
map_signif_level = TRUE,
step_increase = 0.1,
textsize = 3)+
ylab("a.u.")+
xlab(" ")+
theme_classic()+
ggtitle("Decay slope")+
theme_classic()+
theme(plot.title = element_text(siz=12,hjust = 0.5),
axis.title = element_text(size = 12, color = "black"),
axis.ticks = element_line(linewidth = 1.0),
axis.line = element_line(linewidth = 1.0),
axis.text = element_text(size = 12, color = "black", angle = 0),
strip.text.x = element_text(size = 12, color = "black", face = "bold"))
Decay_plot
E. Full-width at half-max
FWHM_plot <- clamp_summary %>%
dplyr::select(Drug,Conc,indv,FWHM) %>%
ggplot(.,aes(Drug,FWHM))+
geom_boxplot(position = "identity", fill= drug_pal_fact)+
geom_point(aes(col=indv, size=2, alpha=0.5))+
guides(size = "none",alpha="none",colour = "none")+
scale_color_brewer(palette = "Dark2", name = "Individual",
label=c("2","3","5"))+
geom_signif(comparisons = list(c("VEH","TRZ"),
c("VEH","MTX"),
c( "VEH","DNR"),
c("VEH","EPI"),
c( "VEH","DOX")),
test = "t.test",
map_signif_level = TRUE,
step_increase = 0.1,
textsize = 3)+
ylab("a.u.")+
xlab(" ")+
theme_classic()+
ggtitle("Full-width at half-max")+
theme_classic()+
theme(plot.title = element_text(siz=12,hjust = 0.5),
axis.title = element_text(size = 12, color = "black"),
axis.ticks = element_line(linewidth = 1.0),
axis.line = element_line(linewidth = 1.0),
axis.text = element_text(size = 12, color = "black", angle = 0),
strip.text.x = element_text(size = 12, color = "black", face = "bold"))
FWHM_plot
F. Contraction rate
BR_plot <- calcium_data %>%
dplyr::select(Drug,Conc,indv,Rate) %>%
mutate(indv=substr(indv,1,2)) %>%
mutate(indv=factor(indv, levels = level_order2)) %>%
mutate(contrl= 0.383) %>%
mutate(norm_rate=Rate/contrl) %>%
filter(Conc==0| Conc==0.5) %>%
ggplot(., aes(x=Drug, y=Rate))+
geom_boxplot(position = "identity", fill= drug_pal_fact)+
geom_point(aes(col=indv, size=2, alpha=0.5))+
guides(size = "none",alpha="none",colour = guide_legend(override.aes = list(alpha= 0.5)))+
# guides(size = "none",alpha="none",colour = "none")+
scale_color_brewer(palette = "Dark2", name = "Individual",label=c("2","3","5"))+
geom_signif(comparisons = list(c("VEH","TRZ"),
c("VEH","MTX"),
c( "VEH","DNR"),
c("VEH","EPI"),
c( "VEH","DOX")),
test = "t.test",
map_signif_level = TRUE,
step_increase = 0.1,
textsize = 3)+
ylab("avg. beats/sec")+
xlab(" ")+
ggtitle("Contraction rate")+
theme_classic()+
theme(plot.title = element_text(siz=12,hjust = 0.5),
axis.title = element_text(size = 12, color = "black"),
axis.ticks = element_line(linewidth = 1.0),
axis.line = element_line(linewidth = 1.0),
axis.text = element_text(size = 12, color = "black", angle = 0),
strip.text.x = element_text(size = 12 ,color = "black", face = "bold"))
BR_plot
BR_plot2 <- BR_plot+theme(legend.position = "none")
legend <- get_legend(BR_plot)G. PCA of Calcium data
k_means <- read.csv("data/K_cluster_kisthree.csv")
PCA_calciumplot <- k_means %>% mutate(Drug =case_match(Drug_Name,
"Dau_0.5"~"DNR",
"Dau_0.5.1" ~"DNR",
"Dau_0.5.2" ~"DNR",
"Dox_0.5"~"DOX",
"Dox_0.5.1" ~"DOX",
"Dox_0.5.2" ~"DOX",
"Epi_0.5"~"EPI",
"Epi_0.5.1"~"EPI",
"Epi_0.5.2"~"EPI",
"Mito_0.5"~"MTX",
"Mito_0.5.1"~"MTX",
"Mito_0.5.2"~"MTX",
"Tras_0.5"~"TRZ",
"Tras_0.5.1"~"TRZ",
"Tras_0.5.2"~"TRZ",
"Control.1"~"VEH",
"Control.2"~"VEH",
"Control"~"VEH",.default = Drug_Name)) %>%
mutate(Class= case_match(Drug,"DOX"~"TOP2i","DNR"~"TOP2i","EPI" ~"TOP2i","MTX" ~"TOP2i", "TRZ"~"not-TOP2i","VEH"~"not-TOP2i",.default = Drug)) %>%
mutate(Drug=factor(Drug, levels = c( "DOX",
"EPI",
"DNR",
"MTX",
"TRZ",
"VEH"))) %>%
ggplot(., aes(x=PC1, y=PC2, col= Drug,shape = factor(Class)))+
geom_point(size = 8)+
scale_shape_manual(values=c(19, 17,15))+
scale_color_manual(values=drug_pal_fact)+
ggtitle(expression("PCA of Ca"^"2+"~"data"))+
theme_bw()+
labs(x = "PC 1 (54 %)",y = "PC 2 (34%)")+
theme(plot.title=element_text(size= 14,hjust = 0.5),
axis.title = element_text(size = 10, color = "black"),
axis.ticks = element_line(size = 1.5),
axis.text = element_text(size = 12, color = "black", angle = 0),
strip.text.x = element_text(size = 15, color = "black", face = "bold"))
PCA_calciumplot 
legend2 <- get_legend(PCA_calciumplot)
PCA2 <- PCA_calciumplot+theme(legend.position = "none")
ggsave("output/Figures/calciumPCA.eps")library(cowplot)
# align all plots
plots <- align_plots(MA_plot, RS_plot,Decay_plot,FWHM_plot,BR_plot2,align='v',axis='l')
##make bottom row
bottom_row <- plot_grid(plots[[1]],plots[[2]],plots[[3]], plots[[4]],plots[[5]],legend,nrow=1, rel_widths = c(1,1,1,1,1,0.2))
# put together
top_row <- plot_grid(nlLine_plot3,legend2,PCA2, rel_widths=c(1,.2,1), nrow=1)
# middle_row <- plot_grid(legend, nrow=1, scale=4)
test <- plot_grid(top_row, bottom_row, ncol=1, rel_heights = c(2,1), rel_widths=c(1,1))
test
ggsave("output/Figures/Calciumgroup.eps",width = 8, height =16, units = "in")
sessionInfo()R version 4.2.2 (2022-10-31 ucrt)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 10 x64 (build 19045)
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
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] broom_1.0.5 RColorBrewer_1.1-3 ggsignif_0.6.4
[4] cowplot_1.1.1 data.table_1.14.8 BiocGenerics_0.42.0
[7] lubridate_1.9.2 forcats_1.0.0 stringr_1.5.0
[10] dplyr_1.1.2 purrr_1.0.1 readr_2.1.4
[13] tidyr_1.3.0 tibble_3.2.1 ggplot2_3.4.2
[16] tidyverse_2.0.0 car_3.1-2 carData_3.0-5
[19] workflowr_1.7.0
loaded via a namespace (and not attached):
[1] Rcpp_1.0.10 getPass_0.2-2 ps_1.7.5 rprojroot_2.0.3
[5] digest_0.6.31 utf8_1.2.3 R6_2.5.1 backports_1.4.1
[9] evaluate_0.21 highr_0.10 httr_1.4.6 pillar_1.9.0
[13] rlang_1.1.1 rstudioapi_0.14 whisker_0.4.1 callr_3.7.3
[17] jquerylib_0.1.4 rmarkdown_2.22 textshaping_0.3.6 labeling_0.4.2
[21] munsell_0.5.0 compiler_4.2.2 httpuv_1.6.11 xfun_0.39
[25] systemfonts_1.0.4 pkgconfig_2.0.3 htmltools_0.5.5 tidyselect_1.2.0
[29] fansi_1.0.4 tzdb_0.4.0 withr_2.5.0 later_1.3.1
[33] grid_4.2.2 jsonlite_1.8.5 gtable_0.3.3 lifecycle_1.0.3
[37] git2r_0.32.0 magrittr_2.0.3 scales_1.2.1 cli_3.6.1
[41] stringi_1.7.12 cachem_1.0.8 farver_2.1.1 fs_1.6.2
[45] promises_1.2.0.1 bslib_0.5.0 ragg_1.2.5 generics_0.1.3
[49] vctrs_0.6.3 tools_4.2.2 glue_1.6.2 hms_1.1.3
[53] processx_3.8.1 abind_1.4-5 fastmap_1.1.1 yaml_2.3.7
[57] timechange_0.2.0 colorspace_2.1-0 knitr_1.43 sass_0.4.6