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count.reads.in.regions.Rmd
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count.reads.in.regions.Rmd
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---
title: "Count reads in regions"
output: pdf_document
---
```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE, cache = TRUE)
```
```{r package, results='hide', warning=FALSE, message=FALSE}
#source("https://bioconductor.org/biocLite.R")
#biocLite("Rsamtools")
library(Rsamtools)
```
Read in all input files
```{r input,results='hide', warning=FALSE, message=FALSE}
#GFF file information
gffFileInfo <- read.csv(file = "un_bowtie_gffFileInfo.csv",
stringsAsFactors = FALSE,
check.names = FALSE)
#Sample information
sampleInfo <- read.csv("un_bowtie_sampleInfo.csv",
stringsAsFactors = FALSE,
check.names = FALSE)
#Complete path to output folder
outFolderP <- "/Users/ls483/Documents/SRA.GEO/RProj_RNAseq/output_gene_cds"
#If bams file have a common extension,you can input it here.Eg.SRR1946637_un.bowtie2.sorted.
#So sample name = "SRR1946637" and samplExt = "_un.bowtie2.sorted""
sampleExt = "_un.bowtie2.sorted.bam"
```
This is the main function that is called:
```{R funcBatchProcess}
funcBatchProcess <- function(gff.folder.path, gff.file.names, ref,
sample.folder.paths, sample.names, sampleNameExt,
outFolderPath, map.q.threshold = 0){
#browser()
#org.path = system('getwd()', intern = TRUE)
org.path = getwd()
#counts.matrix.list only saves in.region column from function 'gene.level.counts'
counts.matrix.list = vector('list', length(gff.file.names)) #initialize empty vector
names(counts.matrix.list) = gsub('.gff', '', gff.file.names)
#counts.list only saves all 3 columns from function 'gene.level.counts'
counts.list = counts.matrix.list
#Loop for every GFF file
for(g in 1:length(gff.file.names)){
#browser()
print(g)
#setwd(gff.folder.path)
#Read GFF file
gg <- paste(gff.folder.path[g],"/",gff.file.names[g], sep="")
if(file.exists(gg)) {
gff = funcReadGffFile(gg)
# cat(g, ' ', gff.file.names[g], '\n')
region.pos = funcGetRegionPosFromGff(gff)
# last row is unannotated parts of genome
counts.matrix.list[[g]] = matrix(0, nrow(region.pos) + 1, length(sample.names))
rownames(counts.matrix.list[[g]]) = c(rownames(region.pos), 'unannotated parts of genome')
colnames(counts.matrix.list[[g]]) = paste('col', 1:length(sample.names), sep='_') # list of list
counts.list[[g]] = vector('list', length(sample.names))
names(counts.list[[g]]) = paste('list', 1:length(sample.names), sep='_')
#intended to store subset of sam/bam file for one specific virus
viral.sam.file = gsub('.gff', '.sam', gff.file.names[g])
#loop for every sample
for(s in 1:length(sample.folder.paths)){
print(s)
cat(g, gff.file.names[g], '\t', s, sample.names[s], '\n')
setwd(sample.folder.paths[s])
b = paste(sample.names[s],sampleNameExt,sep="") #name of bam file
if(file.exists(b)) {
#call function to get rows from bam file corres to one gff
# browser()
sam = funcSubsetBam(sample.names[s],sample.name.sampleExt = sampleNameExt, refName = ref[g]) #calling function to read sam file
counts = matrix(-1, nrow(region.pos), 3)
colnames(counts) = c('in.region','on.boundary','in.gaps')
rownames(counts) = rownames(region.pos)
if(is.null(sam)){
reads.pos = NULL
}else{
# Function to get Positions
reads.pos = funcGetReadPosFromSam(sam, map.q.threshold)
if(!is.null(reads.pos))
#Function to get Region Level Counts
counts = funcRegionLevelCounts(reads.pos, region.pos)
}
g1 <- gsub('.gff', '', gff.file.names[g])
fileName1 <- paste(outFolderPath,"/",g1,".RData" ,sep="")
save(region.pos, reads.pos, counts, file = fileName1)
counts.matrix.list[[g]][, s] = c(counts[,1], counts[1,3])
colnames(counts.matrix.list[[g]])[s] = sample.names[s]
counts.list[[g]][[s]] = counts
names(counts.list[[g]])[s] = sample.names[s]
#browser()
fileNameA <- paste(outFolderPath,"/",g1,"..",sample.names[s],"..counts.RData" ,sep="")
fileNameB <- paste(outFolderPath,"/",g1,"..",sample.names[s],"..counts.csv" ,sep="")
save(counts, file = fileNameA)
write.csv(counts, file = fileNameB)
} else {
print(paste(b, ": BAM file does not exist", sep=""))
}
} #end of sample for loop
} else {
print(paste(gg,"GFF file does not exist",sep=""))
}
} #End of For gff loop
setwd(org.path)
save(counts.matrix.list, file='counts.matrix.list.Rdata')
save(counts.list, file='counts.list.Rdata')
} #end of FuncBatchProcess
```
This is a sub-function (an internal function)
```{R funcSubsetBam}
## sam.file: NC_022518.sam
## sample.name: sample.name without .bwa.bam/sam
funcSubsetBam <- function(sample.name, sample.name.sampleExt = ".bam", refName){
#browser()
bam.file = paste(sample.name,sample.name.sampleExt,sep="")
#source("https://bioconductor.org/biocLite.R")
#biocLite("Rsamtools")
#library("Rsamtools")
bfl = Rsamtools::BamFile(bam.file)
which1 <- as(seqinfo(bfl)[refName], "GRanges")
which1
params <- ScanBamParam(which = which1, what = c("qname", "flag","rname","pos","mapq","cigar"))
temp <- Rsamtools::scanBam(file =bam.file , param = params)
temp1 <- as.data.frame(temp)
colnames(temp1) <- c("qname", "flag","rname","pos","mapq","cigar")
#subset for specific virus
#temp2 <- dplyr::filter(temp1, rname == refName)
temp2 <- temp1
return(temp2)
}
```
This is a sub-function (an internal function)
```{R funcMatcher}
###################
## cigar parsing functions
## usage: sapply(cigars = c('26S2I5D36M', '28S22M', '39M10S'), funcCigarSums)
funcMatcher <- function(pattern, x) {
ind = gregexpr(pattern, x)[[1]]
start = as.numeric(ind)
end = start + attr(ind, "match.length")- 2
apply(cbind(start,end), 1, function(y) substr(x, start=y[1], stop=y[2]));
}
```
This is a sub-function (an internal function)
```{R funcDoOne}
funcDoOne <- function(c, cigar) {
pat <- paste("\\d+", c , sep="")
sum(as.numeric(funcMatcher(pat, cigar)), na.rm=T)
}
```
This is a sub-function (an internal function)
```{R funcCigarSums}
## function
funcCigarSums <- function(cigar, chars=c("M","N","D","I","S","H", "P", "X", "=")) {
sapply (X = chars, funcDoOne, cigar)
}
```
This is a sub-function (an internal function)
```{R funcGetReadPosFromSam}
###################
funcGetReadPosFromSam <- function(sam, map.q.threshold = 40){
#browser()
map.q.flag = sam[, 5] >= map.q.threshold
star.cigar.flag = sam[, 6] != '*'
idx = map.q.flag & star.cigar.flag
if(length(which(idx)) < 1)
return(NULL)
cigars = as.character(sam[which(idx), 6])
cigar.summary = sapply(cigars, funcCigarSums)
reads.length = cigar.summary[1,] + cigar.summary[3,] - cigar.summary[4,]
reads.pos = cbind(as.numeric(sam[which(idx), 4]), as.numeric(sam[which(idx), 4]) + reads.length - 1)
colnames(reads.pos) = c('start', 'end')
rownames(reads.pos) = NULL
return(reads.pos)
}
```
This is a sub-function (an internal function)
```{R funcReadGffFile}
### read gff from gff file, skip first 5 and the last comment line
funcReadGffFile <- function(gff.file, head.skip = 5, tail.ignored = 1){
#browser()
print(gff.file)
gff = read.delim(gff.file, header=F, skip = head.skip)
gff = gff[1:(nrow(gff)-tail.ignored), ]
return(gff)
}
```
This is a sub-function (an internal function)
```{R funcGetRegionPosFromGff}
### get region position, n * 2, start, end
funcGetRegionPosFromGff <- function(gff){
#browser()
region.pos = as.matrix(gff[,c(4,5)])
colnames(region.pos) = c('start', 'end')
rownames(region.pos) = paste(as.character(gff[,1]), #NC_022518.1
as.character(gff[,3]), #long_terminal_repeat/region/gene/CDS
as.numeric(gff[,4]), #start 1112
as.numeric(gff[,5]), #end 6746
sep='_')
return(region.pos)
}
```
This is a sub-function (an internal function)
```{R funcRegionLevelCounts}
# reads.pos and genes.pos are same format, N * 2 matrix, with column 'start' and 'end'
funcRegionLevelCounts <- function(reads.pos, region.pos){
#browser()
n.counts = matrix(0,nrow(region.pos),3)
colnames(n.counts) = c('in.region','on.boundary','in.gaps')
rownames(n.counts) = rownames(region.pos)
low = region.pos[, 1]
high = region.pos[, 2]
for(i in 1:nrow(reads.pos)){
start = reads.pos[i, 1]
end = reads.pos[i, 2]
idx.w = ((start >= low) & (end <= high))
if(sum(idx.w) > 0)
n.counts[idx.w, 1] = n.counts[idx.w, 1] + 1
idx.r = ((start >= low) & (start < high) & (end > high)) # on right boundary
idx.l = ((start < low) & (end > low) & (end <= high)) # on left boundary
idx.c = ((start < low) & (end > high)) # cover region
idx.b = idx.r | idx.l | idx.c
if(sum(idx.b) > 0)
n.counts[idx.b, 2] = n.counts[idx.b, 2] + 1
if(sum(idx.w | idx.b) == 1)
n.counts[1, 3] = n.counts[1, 3] + 1
}
return(n.counts)
}
```
Calling main function ```funcBatchProcess```
```{r CallingFunc, results='hide', message=FALSE, warning=FALSE}
#calling func
funcBatchProcess(gffFileInfo$gff.folder.path,
gffFileInfo$gff.file.names,
gffFileInfo$ref,
sampleInfo$sample.folder.paths,
sampleInfo$sample.names,
sampleNameExt = sampleExt,
outFolderPath = outFolderP)
```