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final_summary_table_gen_evo-I.R
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final_summary_table_gen_evo-I.R
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#!/usr/bin/Rscript
# Install dependencies
library(Biostrings)
library(splitstackshape)
library(dplyr)
library(getopt)
library(splitstackshape)
library(data.table)
args<-commandArgs(TRUE)
#############################################################
## Command-line preparations and getopt parsing ##
#############################################################
options<-matrix(c('lincRNA', 'l', 1, "character",
'lincRNAbed', 'b', 1, "character",
'overlap', 'v', 2, "character",
'tss', 't', 2, "character",
'help', 'h', 0, "logical"),
ncol=4, byrow=TRUE)
ret.opts<-getopt(options,args)
if ( !is.null(ret.opts$help) ) {
cat(getopt(options, usage=TRUE));
q(status=1);
}
###############################################################################################################
# No TSS or No Overlap
###############################################################################################################
if(is.null(ret.opts$tss) && is.null(ret.opts$overlap)){
# LincRNA fasta file
fastaFile <- readDNAStringSet(ret.opts$lincRNA)
lincRNA_ID = names(fastaFile)
sequence = paste(fastaFile)
size = width(fastaFile)
df <- data.frame(lincRNA_ID, size)
# Bed file
# split concatenated column by `;`
bed_File <- read.csv(ret.opts$lincRNAbed, sep = "\t", header = F)
# Search the tss column
new <- bed_File[grep("tss_id", bed_File$V10),]
if (nrow(new) == 0) {
# Without tss
new2 <- bed_File[!grepl("tss_id", bed_File$V10),]
results2 <- cSplit(new2, splitCols= "V10", sep = ";", drop = TRUE)
results2 <- as.data.frame(results2)
gene2_co <- which(apply(results2, 2, function(x) any(grepl("XLOC_*", x))))
TCONS2_co <- which(apply(results2, 2, function(x) any(grepl("TCONS*", x))))
exon2_co <- which(apply(results2, 2, function(x) any(grepl("exon_number", x))))
cc2_co <- which(apply(results2, 2, function(x) any(grepl("class_code", x))))
comb2 <- cbind(results2[gene2_co], results2[TCONS2_co], results2[exon2_co], results2[cc2_co])
comb2.m <- as.data.frame(cSplit(comb2, splitCols = c("V10_1", "V10_5", "V10_3"), sep = " ", drop = TRUE))
comb2.m <- comb2.m[,c(3,5,7,1)]
names(comb2.m) <- c("gene", "transcript", "exon_numb", "class_code")
t <- paste0(comb2.m$transcript, ".gene=", comb2.m$gene)
bind <- as.data.frame(cbind(t,comb2.m$exon_numb))
bind$t <- as.character(bind$t)
bind$V2 <- as.character(bind$V2)
bedfinal <- as.data.frame(bind %>% group_by(t) %>% summarise(V2 = max(V2)))
# non present columns
cols <- ncol(bedfinal)
cols <- cols + 1
bedfinal[,cols] <- NA
cols <- cols + 1
bedfinal[,cols] <- NA
cols <- cols + 1
bedfinal[,cols] <- NA
merge1 <- merge(df, bedfinal, by=1)
merge1 <- merge1[,c(1,2,4:6,3)]
names(merge1) <- c("lincRNA_ID", "Size(bp)", "Overlapping_known_lincRNA", "gene_ID", "Has_TSS_data", "Number_of_exons")
write.table(merge1, file = "final_Summary_table.tsv", row.names = F, col.names = T, quote = F, sep = "\t")
} else {
# With tss
results <- as.data.frame(cSplit(new, splitCols= "V10", sep = ";", drop = TRUE))
gene_co <- which(apply(results, 2, function(x) any(grepl("XLOC_*", x))))
TCONS_co <- which(apply(results, 2, function(x) any(grepl("TCONS*", x))))
exon_co <- which(apply(results, 2, function(x) any(grepl("exon_number", x))))
cc_co <- which(apply(results, 2, function(x) any(grepl("class_code", x))))
comb <- cbind(results[gene_co], results[TCONS_co], results[exon_co], results[cc_co])
comb.m <- as.data.frame(cSplit(comb, splitCols = c(1, 2, 3), sep = " ", drop = TRUE))
comb.m <- comb.m[,c(3,5,7,1)]
names(comb.m) <- c("gene", "transcript", "exon_numb", "class_code")
# Without tss
new2 <- bed_File[!grepl("tss_id", bed_File$V10),]
if (nrow(new2) != 0) {
results2 <- cSplit(new2, splitCols= "V10", sep = ";", drop = TRUE)
results2 <- as.data.frame(results2)
gene2_co <- which(apply(results2, 2, function(x) any(grepl("XLOC_*", x))))
TCONS2_co <- which(apply(results2, 2, function(x) any(grepl("TCONS*", x))))
exon2_co <- which(apply(results2, 2, function(x) any(grepl("exon_number", x))))
cc2_co <- which(apply(results2, 2, function(x) any(grepl("class_code", x))))
comb2 <- cbind(results2[gene2_co], results2[TCONS2_co], results2[exon2_co], results2[cc2_co])
comb2.m <- as.data.frame(cSplit(comb2, splitCols = c(1, 2, 3), sep = " ", drop = TRUE))
comb2.m <- comb2.m[,c(3,5,7,1)]
names(comb2.m) <- c("gene", "transcript", "exon_numb", "class_code")
# Combine now
results_all <- rbind(comb.m, comb2.m)
head(results_all)
# Adding gene, transcript and exon number columns
t <- paste0(results_all$transcript, ".gene=", results_all$gene)
bind <- as.data.frame(cbind(t,results_all$exon_numb))
bind$t <- as.character(bind$t)
bind$V2 <- as.character(bind$V2)
bedfinal <- as.data.frame(bind %>% group_by(t) %>% summarise(V2 = max(V2)))
# non present columns
cols <- ncol(bedfinal)
cols <- cols + 1
bedfinal[,cols] <- NA
cols <- cols + 1
bedfinal[,cols] <- NA
cols <- cols + 1
bedfinal[,cols] <- NA
merge1 <- merge(df, bedfinal, by=1)
merge1 <- merge1[,c(1,2,4:6,3)]
names(merge1) <- c("lincRNA_ID", "Size(bp)", "Overlapping_known_lincRNA", "gene_ID", "Has_TSS_data", "Number_of_exons")
write.table(merge1, file = "final_Summary_table.tsv", row.names = F, col.names = T, quote = F, sep = "\t")
} else {
t <- paste0(comb.m$transcript, ".gene=", comb.m$gene)
bind <- as.data.frame(cbind(t,comb.m$exon_numb))
bind$t <- as.character(bind$t)
bind$V2 <- as.character(bind$V2)
bedfinal <- as.data.frame(bind %>% group_by(t) %>% summarise(V2 = max(V2)))
# non present columns
cols <- ncol(bedfinal)
cols <- cols + 1
bedfinal[,cols] <- NA
cols <- cols + 1
bedfinal[,cols] <- NA
cols <- cols + 1
bedfinal[,cols] <- NA
merge1 <- merge(df, bedfinal, by=1)
merge1 <- merge1[,c(1,2,4:6,3)]
names(merge1) <- c("lincRNA_ID", "Size(bp)", "Overlapping_known_lincRNA", "gene_ID", "Has_TSS_data", "Number_of_exons")
write.table(merge1, file = "final_Summary_table.tsv", row.names = F, col.names = T, quote = F, sep = "\t")
}
}
###############################################################################################################
# No TSS file
###############################################################################################################
} else if(is.null(ret.opts$tss)){
# Fasta file
fastaFile <- readDNAStringSet(ret.opts$lincRNA)
lincRNA_ID = names(fastaFile)
sequence = paste(fastaFile)
size = width(fastaFile)
df <- data.frame(lincRNA_ID, size)
# Overlapping lincRNA's
fastaFile_over <- readDNAStringSet(ret.opts$overlap)
lincRNA_ID_over <- names(fastaFile_over)
len <- length(lincRNA_ID_over)
newmat <- matrix(lincRNA_ID_over, ncol =1 , nrow = len, byrow = T)
overlap <- cSplit(as.data.table(newmat), "V1", "_o")
# Finding out the lincRNA gene id:
info = file.info("./intersect_output2.txt")
if (info$size == 0) {
data4 <- data.frame(gene_id = rep("NA",nrow(df)))
}else {
data1 <- read.table("./intersect_output2.txt", sep="\t")
names(data1) <- c("ID","gene")
data1$gene <- as.character(data1$gene)
gene2 <- unlist(strsplit(data1$gene, "_"))
data2 <- matrix(gene2, ncol = 4, byrow = T)
data3 <- as.data.frame(cbind(data1[1], data2[,2]))
names(data3) <- c("id", "gene")
data4 <- as.data.frame(data3 %>% group_by(id) %>% summarise(gene[1]))
names(data4)[2] <- "gene_id"
}
# Bed file
# split concatenated column by `;`
bed_File <- read.csv("lincRNAs.bed", sep = "\t", header = F)
# Search the tss column
new <- bed_File[grep("tss_id", bed_File$V10),]
if (nrow(new) == 0) {
# Without tss
new2 <- bed_File[!grepl("tss_id", bed_File$V10),]
results2 <- cSplit(new2, splitCols= "V10", sep = ";", drop = TRUE)
results2 <- as.data.frame(results2)
gene2_co <- which(apply(results2, 2, function(x) any(grepl("XLOC_*", x))))
TCONS2_co <- which(apply(results2, 2, function(x) any(grepl("TCONS*", x))))
exon2_co <- which(apply(results2, 2, function(x) any(grepl("exon_number", x))))
cc2_co <- which(apply(results2, 2, function(x) any(grepl("class_code", x))))
comb2 <- cbind(results2[gene2_co], results2[TCONS2_co], results2[exon2_co], results2[cc2_co])
comb2.m <- as.data.frame(cSplit(comb2, splitCols = c("V10_1", "V10_5", "V10_3"), sep = " ", drop = TRUE))
comb2.m <- comb2.m[,c(3,5,7,1)]
names(comb2.m) <- c("gene", "transcript", "exon_numb", "class_code")
t <- paste0(comb2.m$transcript, ".gene=", comb2.m$gene)
bind <- as.data.frame(cbind(t,comb2.m$exon_numb))
bind$t <- as.character(bind$t)
bind$V2 <- as.character(bind$V2)
bedfinal <- as.data.frame(bind %>% group_by(t) %>% summarise(V2 = max(V2)))
# non present columns
cols <- ncol(bedfinal)
cols <- cols + 1
bedfinal[,cols] <- NA
} else {
# With tss
results <- as.data.frame(cSplit(new, splitCols= "V10", sep = ";", drop = TRUE))
gene_co <- which(apply(results, 2, function(x) any(grepl("XLOC_*", x))))
TCONS_co <- which(apply(results, 2, function(x) any(grepl("TCONS*", x))))
exon_co <- which(apply(results, 2, function(x) any(grepl("exon_number", x))))
cc_co <- which(apply(results, 2, function(x) any(grepl("class_code", x))))
comb <- cbind(results[gene_co], results[TCONS_co], results[exon_co], results[cc_co])
comb.m <- as.data.frame(cSplit(comb, splitCols = c(1, 2, 3), sep = " ", drop = TRUE))
comb.m <- comb.m[,c(3,5,7,1)]
names(comb.m) <- c("gene", "transcript", "exon_numb", "class_code")
# Without tss
new2 <- bed_File[!grepl("tss_id", bed_File$V10),]
if (nrow(new2) != 0) {
results2 <- cSplit(new2, splitCols= "V10", sep = ";", drop = TRUE)
results2 <- as.data.frame(results2)
gene2_co <- which(apply(results2, 2, function(x) any(grepl("XLOC_*", x))))
TCONS2_co <- which(apply(results2, 2, function(x) any(grepl("TCONS*", x))))
exon2_co <- which(apply(results2, 2, function(x) any(grepl("exon_number", x))))
cc2_co <- which(apply(results2, 2, function(x) any(grepl("class_code", x))))
comb2 <- cbind(results2[gene2_co], results2[TCONS2_co], results2[exon2_co], results2[cc2_co])
comb2.m <- as.data.frame(cSplit(comb2, splitCols = c(1, 2, 3), sep = " ", drop = TRUE))
comb2.m <- comb2.m[,c(3,5,7,1)]
names(comb2.m) <- c("gene", "transcript", "exon_numb", "class_code")
# Combine now
results_all <- rbind(comb.m, comb2.m)
head(results_all)
# Adding gene, transcript and exon number columns
t <- paste0(results_all$transcript, ".gene=", results_all$gene)
bind <- as.data.frame(cbind(t,results_all$exon_numb))
bind$t <- as.character(bind$t)
bind$V2 <- as.character(bind$V2)
bedfinal <- as.data.frame(bind %>% group_by(t) %>% summarise(V2 = max(V2)))
# non present columns
cols <- ncol(bedfinal)
cols <- cols + 1
bedfinal[,cols] <- NA
} else {
t <- paste0(comb.m$transcript, ".gene=", comb.m$gene)
bind <- as.data.frame(cbind(t,comb.m$exon_numb))
bind$t <- as.character(bind$t)
bind$V2 <- as.character(bind$V2)
bedfinal <- as.data.frame(bind %>% group_by(t) %>% summarise(V2 = max(V2)))
# non present columns
cols <- ncol(bedfinal)
cols <- cols + 1
bedfinal[,cols] <- NA
}
}
merge1 <- merge(x = df, y = overlap, by = 1, all = TRUE)
if (info$size == 0) {
merge2 <- cbind(merge1, data4)
} else {
merge2 <- merge(x = merge1, y = data4, by = 1, all = TRUE)
}
merge2$V1_2 <- as.character(merge2$V1_2)
merge2$gene_id <- as.character(merge2$gene_id)
merge2$V1_2[!is.na(merge2$V1_2)] <- "Yes"
merge2$V1_2[is.na(merge2$V1_2)] <- "No"
merge2$gene_id[is.na(merge2$gene_id)] <- "NA"
colnames(merge2)[2] <- "Size(bp)"
colnames(merge2)[3] <- "Overlapping_known_lincRNA"
merge3 <- merge(x = merge2, y = bedfinal, by = 1, all = TRUE)
colnames(merge3)[5] <- "Number_of_exons"
colnames(merge3)[6] <- "Has_TSS_data"
merge3 <- merge3[,c(1:4,6,5)]
# Writing data
write.table(merge3, file = "final_Summary_table.tsv", row.names = F, col.names = T, quote = F, sep = "\t")
###############################################################################################################
# No Overlap file
###############################################################################################################
} else if(is.null(ret.opts$overlap)) {
# Fasta file
fastaFile <- readDNAStringSet(ret.opts$lincRNA)
lincRNA_ID = names(fastaFile)
sequence = paste(fastaFile)
size = width(fastaFile)
df <- data.frame(lincRNA_ID, size)
# CAGE supported lincRNA's
fastaFile_Cage <- readDNAStringSet(ret.opts$tss)
lincRNA_ID_Cage <- names(fastaFile_Cage)
len1 <- length(lincRNA_ID_Cage)
newmat1 <- matrix(lincRNA_ID_Cage, ncol =1 , nrow = len1, byrow = T)
cage <- cSplit(as.data.table(newmat1), "V1", "_C")
# Bed file
# split concatenated column by `;`
bed_File <- read.csv(ret.opts$lincRNAbed, sep = "\t", header = F)
# Search the tss column
new <- bed_File[grep("tss_id", bed_File$V10),]
if (nrow(new) == 0) {
# Without tss
new2 <- bed_File[!grepl("tss_id", bed_File$V10),]
results2 <- cSplit(new2, splitCols= "V10", sep = ";", drop = TRUE)
results2 <- as.data.frame(results2)
gene2_co <- which(apply(results2, 2, function(x) any(grepl("XLOC_*", x))))
TCONS2_co <- which(apply(results2, 2, function(x) any(grepl("TCONS*", x))))
exon2_co <- which(apply(results2, 2, function(x) any(grepl("exon_number", x))))
cc2_co <- which(apply(results2, 2, function(x) any(grepl("class_code", x))))
comb2 <- cbind(results2[gene2_co], results2[TCONS2_co], results2[exon2_co], results2[cc2_co])
comb2.m <- as.data.frame(cSplit(comb2, splitCols = c("V10_1", "V10_5", "V10_3"), sep = " ", drop = TRUE))
comb2.m <- comb2.m[,c(3,5,7,1)]
names(comb2.m) <- c("gene", "transcript", "exon_numb", "class_code")
t <- paste0(comb2.m$transcript, ".gene=", comb2.m$gene)
bind <- as.data.frame(cbind(t,comb2.m$exon_numb))
bind$t <- as.character(bind$t)
bind$V2 <- as.character(bind$V2)
bedfinal <- as.data.frame(bind %>% group_by(t) %>% summarise(V2 = max(V2)))
# non present columns
cols <- ncol(bedfinal)
cols <- cols + 1
bedfinal[,cols] <- NA
cols <- cols + 1
bedfinal[,cols] <- NA
} else {
# With tss
results <- as.data.frame(cSplit(new, splitCols= "V10", sep = ";", drop = TRUE))
gene_co <- which(apply(results, 2, function(x) any(grepl("XLOC_*", x))))
TCONS_co <- which(apply(results, 2, function(x) any(grepl("TCONS*", x))))
exon_co <- which(apply(results, 2, function(x) any(grepl("exon_number", x))))
cc_co <- which(apply(results, 2, function(x) any(grepl("class_code", x))))
comb <- cbind(results[gene_co], results[TCONS_co], results[exon_co], results[cc_co])
comb.m <- as.data.frame(cSplit(comb, splitCols = c(1, 2, 3), sep = " ", drop = TRUE))
comb.m <- comb.m[,c(3,5,7,1)]
names(comb.m) <- c("gene", "transcript", "exon_numb", "class_code")
# Without tss
new2 <- bed_File[!grepl("tss_id", bed_File$V10),]
if (nrow(new2) != 0) {
results2 <- cSplit(new2, splitCols= "V10", sep = ";", drop = TRUE)
results2 <- as.data.frame(results2)
gene2_co <- which(apply(results2, 2, function(x) any(grepl("XLOC_*", x))))
TCONS2_co <- which(apply(results2, 2, function(x) any(grepl("TCONS*", x))))
exon2_co <- which(apply(results2, 2, function(x) any(grepl("exon_number", x))))
cc2_co <- which(apply(results2, 2, function(x) any(grepl("class_code", x))))
comb2 <- cbind(results2[gene2_co], results2[TCONS2_co], results2[exon2_co], results2[cc2_co])
comb2.m <- as.data.frame(cSplit(comb2, splitCols = c(1, 2, 3), sep = " ", drop = TRUE))
comb2.m <- comb2.m[,c(3,5,7,1)]
names(comb2.m) <- c("gene", "transcript", "exon_numb", "class_code")
# Combine now
results_all <- rbind(comb.m, comb2.m)
head(results_all)
# Adding gene, transcript and exon number columns
t <- paste0(results_all$transcript, ".gene=", results_all$gene)
bind <- as.data.frame(cbind(t,results_all$exon_numb))
bind$t <- as.character(bind$t)
bind$V2 <- as.character(bind$V2)
bedfinal <- as.data.frame(bind %>% group_by(t) %>% summarise(V2 = max(V2)))
# non present columns
cols <- ncol(bedfinal)
cols <- cols + 1
bedfinal[,cols] <- NA
cols <- cols + 1
bedfinal[,cols] <- NA
} else {
t <- paste0(comb.m$transcript, ".gene=", comb.m$gene)
bind <- as.data.frame(cbind(t,comb.m$exon_numb))
bind$t <- as.character(bind$t)
bind$V2 <- as.character(bind$V2)
bedfinal <- as.data.frame(bind %>% group_by(t) %>% summarise(V2 = max(V2)))
# non present columns
cols <- ncol(bedfinal)
cols <- cols + 1
bedfinal[,cols] <- NA
cols <- cols + 1
bedfinal[,cols] <- NA
}
}
# Merging All three files
merge1 <- merge(x = df, y = cage, by = 1, all = TRUE)
merge2 <- merge(x = merge1, y = bedfinal, by = 1, all = TRUE)
merge2$V1_2 <- as.character(merge2$V1_2)
merge2$V1_2[is.na(merge2$V1_2)] <- "No"
merge2$V1_2 <- sub("CAGE_PLUS", "Yes", merge2$V1_2)
merge2$V1_2 <- as.factor(merge2$V1_2)
colnames(merge2)[2] <- "Size(bp)"
colnames(merge2)[3] <- "Has_TSS_data"
colnames(merge2)[4] <- "Number_of_exons"
colnames(merge2)[5] <- "Overlapping_known_lincRNA"
colnames(merge2)[6] <- "gene_id"
# merge2[,order(colnames(merge2))]
merge2 <- merge2[,c(1:2,5:6,3:4)]
# Writing data
write.table(merge2, file = "final_Summary_table.tsv", row.names = F, col.names = T, quote = F, sep = "\t")
########################################################################################################################
# All present
########################################################################################################################
} else {
# All lincRNA's
fastaFile <- readDNAStringSet(ret.opts$lincRNA)
lincRNA_ID = names(fastaFile)
sequence = paste(fastaFile)
size = width(fastaFile)
df <- data.frame(lincRNA_ID, size)
# Overlapping lincRNA's
fastaFile_over <- readDNAStringSet(ret.opts$overlap)
lincRNA_ID_over <- names(fastaFile_over)
len <- length(lincRNA_ID_over)
newmat <- matrix(lincRNA_ID_over, ncol =1 , nrow = len, byrow = T)
overlap <- cSplit(as.data.table(newmat), "V1", "_o")
# CAGE supported lincRNA's
fastaFile_Cage <- readDNAStringSet(ret.opts$tss)
lincRNA_ID_Cage <- names(fastaFile_Cage)
len1 <- length(lincRNA_ID_Cage)
newmat1 <- matrix(lincRNA_ID_Cage, ncol =1 , nrow = len1, byrow = T)
cage <- cSplit(as.data.table(newmat1), "V1", "_C")
# Finding out the lincRNA gene id:
info = file.info("./intersect_output2.txt")
if (info$size == 0) {
data4 <- data.frame(gene_id = rep("NA",nrow(df)))
} else {
data1 <- read.table("./intersect_output2.txt", sep="\t")
names(data1) <- c("ID","gene")
data1$gene <- as.character(data1$gene)
gene2 <- unlist(strsplit(data1$gene, "_"))
data2 <- matrix(gene2, ncol = 4, byrow = T)
data3 <- as.data.frame(cbind(data1[1], data2[,2]))
names(data3) <- c("id", "gene")
data4 <- as.data.frame(data3 %>% group_by(id) %>% summarise(gene[1]))
names(data4)[2] <- "gene_id"
}
# Bed file
# split concatenated column by `;`
bed_File <- read.csv(ret.opts$lincRNAbed, sep = "\t", header = F)
# Search the tss column
new <- bed_File[grep("tss_id", bed_File$V10),]
if (nrow(new) == 0) {
# Without tss
new2 <- bed_File[!grepl("tss_id", bed_File$V10),]
results2 <- cSplit(new2, splitCols= "V10", sep = ";", drop = TRUE)
results2 <- as.data.frame(results2)
gene2_co <- which(apply(results2, 2, function(x) any(grepl("XLOC_*", x))))
TCONS2_co <- which(apply(results2, 2, function(x) any(grepl("TCONS*", x))))
exon2_co <- which(apply(results2, 2, function(x) any(grepl("exon_number", x))))
cc2_co <- which(apply(results2, 2, function(x) any(grepl("class_code", x))))
comb2 <- cbind(results2[gene2_co], results2[TCONS2_co], results2[exon2_co], results2[cc2_co])
comb2.m <- as.data.frame(cSplit(comb2, splitCols = c("V10_1", "V10_5", "V10_3"), sep = " ", drop = TRUE))
comb2.m <- comb2.m[,c(3,5,7,1)]
names(comb2.m) <- c("gene", "transcript", "exon_numb", "class_code")
t <- paste0(comb2.m$transcript, ".gene=", comb2.m$gene)
bind <- as.data.frame(cbind(t,comb2.m$exon_numb))
bind$t <- as.character(bind$t)
bind$V2 <- as.character(bind$V2)
bedfinal <- as.data.frame(bind %>% group_by(t) %>% summarise(V2 = max(V2)))
} else {
# With tss
results <- as.data.frame(cSplit(new, splitCols= "V10", sep = ";", drop = TRUE))
gene_co <- which(apply(results, 2, function(x) any(grepl("XLOC_*", x))))
TCONS_co <- which(apply(results, 2, function(x) any(grepl("TCONS*", x))))
exon_co <- which(apply(results, 2, function(x) any(grepl("exon_number", x))))
cc_co <- which(apply(results, 2, function(x) any(grepl("class_code", x))))
comb <- cbind(results[gene_co], results[TCONS_co], results[exon_co], results[cc_co])
comb.m <- as.data.frame(cSplit(comb, splitCols = c(1, 2, 3), sep = " ", drop = TRUE))
comb.m <- comb.m[,c(3,5,7,1)]
names(comb.m) <- c("gene", "transcript", "exon_numb", "class_code")
# Without tss
new2 <- bed_File[!grepl("tss_id", bed_File$V10),]
if (nrow(new2) != 0) {
results2 <- cSplit(new2, splitCols= "V10", sep = ";", drop = TRUE)
results2 <- as.data.frame(results2)
gene2_co <- which(apply(results2, 2, function(x) any(grepl("XLOC_*", x))))
TCONS2_co <- which(apply(results2, 2, function(x) any(grepl("TCONS*", x))))
exon2_co <- which(apply(results2, 2, function(x) any(grepl("exon_number", x))))
cc2_co <- which(apply(results2, 2, function(x) any(grepl("class_code", x))))
comb2 <- cbind(results2[gene2_co], results2[TCONS2_co], results2[exon2_co], results2[cc2_co])
comb2.m <- as.data.frame(cSplit(comb2, splitCols = c(1, 2, 3), sep = " ", drop = TRUE))
comb2.m <- comb2.m[,c(3,5,7,1)]
names(comb2.m) <- c("gene", "transcript", "exon_numb", "class_code")
# Combine now
results_all <- rbind(comb.m, comb2.m)
head(results_all)
# Adding gene, transcript and exon number columns
t <- paste0(results_all$transcript, ".gene=", results_all$gene)
bind <- as.data.frame(cbind(t,results_all$exon_numb))
bind$t <- as.character(bind$t)
bind$V2 <- as.character(bind$V2)
bedfinal <- as.data.frame(bind %>% group_by(t) %>% summarise(V2 = max(V2)))
} else {
t <- paste0(comb.m$transcript, ".gene=", comb.m$gene)
bind <- as.data.frame(cbind(t,comb.m$exon_numb))
bind$t <- as.character(bind$t)
bind$V2 <- as.character(bind$V2)
bedfinal <- as.data.frame(bind %>% group_by(t) %>% summarise(V2 = max(V2)))
}
}
# Merging All three files
merge1 <- merge(x = df, y = overlap, by = 1, all = TRUE)
if (info$size == 0) {
merge2 <- cbind(merge1, data4)}
else {
merge2 <- merge(x = merge1, y = data4, by = 1, all = TRUE)
}
merge3 <- merge(merge2, cage, by=1, all = TRUE)
merge4 <- merge(merge3, bedfinal, by=1, all = TRUE)
names(merge4) <- c("lincRNA_ID", "Size(bp)", "Overlapping_known_lincRNA", "gene_ID", "Has_TSS_data", "Number_of_exons")
merge4$gene_ID <- as.character(merge4$gene_ID)
merge4$gene_ID[is.na(merge4$gene_ID)] <- "NA"
merge4$Overlapping_known_lincRNA <- as.character(merge4$Overlapping_known_lincRNA)
merge4$Has_TSS_data <- as.character(merge4$Has_TSS_data)
merge4$Overlapping_known_lincRNA[!is.na(merge4$Overlapping_known_lincRNA)] <- "Yes"
merge4$Has_TSS_data[!is.na(merge4$Has_TSS_data)] <- "Yes"
merge4$Overlapping_known_lincRNA[is.na(merge4$Overlapping_known_lincRNA)] <- "No"
merge4$Has_TSS_data[is.na(merge4$Has_TSS_data)] <- "No"
# Writing data
write.table(merge4, file = "final_Summary_table.tsv", row.names = F, col.names = T, quote = F, sep = "\t")
}