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Copy path02C_Conservation_func.R
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02C_Conservation_func.R
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# 0. Import libraries
#library(readxl)
library(stringr)
library(reshape)
library(ggplot2)
library(dplyr)
library(tidyr)
# 1. Import data
ImportSignDE <- function(main_dir, ext, row_col) {
if (missing(ext)) {
deg_files <- list.files(path = main_dir, pattern = "\\.csv$",full.names = TRUE)
if (missing(row_col)) {
deg <- lapply(deg_files, read.csv, row.names=1)
}
else {
deg <- lapply(deg_files, read.csv, row.names=row_col)
}
}
else {
deg_files <- list.files(path = main_dir, pattern = paste0("\\.",ext,"$"),full.names = TRUE)
if (missing(row_col)) {
deg <- lapply(deg_files, read.csv, row.names=1)
}
else {
deg <- lapply(deg_files, read.csv, row.names=row_col)
}
}
names_deg <- list.files(path = main_dir, pattern = "\\.csv$",full.names = FALSE)
names(deg) <- substr(names_deg, 1, nchar(names_deg)-4)
return(deg)
}
# 2. Retrieve DEGs
ReadRawData <- function(main_dir, sex, ext, row_col) {
path <- paste0(main_dir, "/01B_num_DEGs")
sub_ct <- list.dirs(path, recursive=FALSE, full.names = FALSE)
df_sex <- list()
df_names <- vector()
for (ct in 1:length(sub_ct)) {
deg <- ImportSignDE(paste(path, sub_ct[ct], sep="/"))
for (i in names(deg)) {
if (grepl(sex, i, fixed=TRUE)){
df_names <- c(df_names, paste(sub_ct[ct], i, sep="_"))
df_sex <- append(df_sex, list(deg[[i]]))
}
}
}
names(df_sex) <- df_names
names(df_sex) <- sapply(1:length(names(df_sex)), function(i) str_replace(names(df_sex)[i], paste0("_", sex, "_filt"), ""))
return(df_sex)
}
# 3. Retrieve all genes expressed in the cell types in a specific disease - from DISCO
AllGenes <- function(all_df, ct_ordered) {
all_df <- subset(all_df, subset = ct %in% ct_ordered)
all_df$ct <- droplevels(all_df$ct)
return(all_df)
}
# 4. Calculate Frction of Sex-biased conserved genes
SexFrac <- function(cons_filt, df_sex, sex) {
sex_cons <- sapply(1:length(names(df_sex)), function(x) length(intersect(rownames(df_sex[[x]]), cons_filt$gene_name)))
fr_sex <- sapply(1:length(names(df_sex)), function(x) sex_cons[x] / nrow(df_sex[[x]]))
return(fr_sex)
}
# 5. Calculate Fraction of all DEGs
AllFrac <- function(cons_filt, genes_df, ct_names, sex) {
fr_all <- vector()
for (ct in ct_names) {
ct_genes <- genes_df[which(genes_df$ct==ct & genes_df$sex==sex), "genes"]
fr_ct <- length(intersect(ct_genes, cons_filt$gene_name)) / length(ct_genes)
fr_all <- c(fr_all, fr_ct)
}
return(fr_all)
}
# 6. Create new Df
DfFrac <- function(main_dir, cons_df, threshold, out_name, all_df, ct_ordered) {
df_F <- ReadRawData(main_dir, "F")
df_M <- ReadRawData(main_dir, "M")
genes_df <- AllGenes(all_df, ct_ordered)
if (out_name == "Primates") {
cons_filt <- subset(cons_df, rowSums(cons_df[, c(5:10)])>=threshold)
} else if (out_name == "SAGD") {
cons_filt <- subset(cons_df, rowSums(cons_df[, c(2:22)])>=threshold)
} else if (out_name == "ENSEMBL") {
cons_filt <- subset(cons_df, rowSums(cons_df[, c(2:ncol(cons_df))])>=threshold)
}
fr_all_F <- AllFrac(cons_filt, genes_df, names(df_F), "F")
fr_all_M <- AllFrac(cons_filt, genes_df, names(df_M), "M")
fr_F <- SexFrac(cons_filt, df_F, "F")
fr_M <- SexFrac(cons_filt, df_M, "M")
df_frac <- data.frame(c(rep("F", length(names(df_F))), rep("M", length(names(df_M)))),
c(names(df_F), names(df_M)),
c(fr_all_F, fr_all_M),
c(fr_F, fr_M)
)
colnames(df_frac) <- c("sex", "ct", "All", "DEG_fraction")
df_frac$ct <- as.factor(df_frac$ct)
dir.create(paste(main_dir, "02C_Conservation", sep="/"), showWarnings = FALSE)
write.csv(df_frac, paste0(main_dir, "/02C_Conservation/", out_name, "_fraction_in_", threshold, "_species.csv"), row.names = F)
df_frac <- melt(df_frac)
names(df_frac)[names(df_frac) == 'variable'] <- 'group'
names(df_frac)[names(df_frac) == 'value'] <- 'fractions'
df_frac$group <- paste(df_frac$sex, df_frac$group, sep="_")
return(df_frac)
}
# 7. Plot
PlotFrac <- function(main_dir, df_frac, threshold, out_name, ct_ordered) {
dis_ct_ordered <- ct_ordered[which(ct_ordered %in% levels(df_frac$ct))]
df_frac$ct <- factor(df_frac$ct, dis_ct_ordered)
df_frac <- df_frac[order(df_frac$ct), ]
pdf(paste0(main_dir, "/02C_Conservation/", out_name, "_fraction_in_", threshold, "_species.pdf"))
print(
ggplot(df_frac, aes(ct, fractions, fill=group)) +
geom_bar(stat='identity', position='dodge', color="black") +
labs(title=paste0(out_name, " - conserved in at least ",threshold, " species"), x="Cell types", y=paste0("Fraction of conserved genes"), fill="Groups") +
scale_fill_discrete(labels=c("All Female Genes", "Female-biased genes", "All Male Genes", "Male-biased genes")) +
theme(panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
panel.background = element_blank(),
axis.line = element_line(colour = "black"),
axis.title.x = element_blank(),
axis.text.x = element_text(size=8, colour = "black", vjust = 0.7, hjust=0.5),
axis.ticks.x=element_blank(),
axis.title.y = element_text(size=12, face="bold", colour = "black"),
legend.position = "bottom",
legend.title = element_text(size=12, face="bold", colour = "black"))
)
dev.off()
}
# 8. MAIN
ConservedFractions <- function(main_dir, cons_df, threshold, out_name, all_df, ct_ordered) {
df_frac <- DfFrac(main_dir, cons_df, threshold, out_name, all_df, ct_ordered)
PlotFrac(main_dir, df_frac, threshold, out_name, ct_ordered)
}