Nothing
gsnapChromosomes <- function(genome, genome_dir) {
read.table(pipe(paste("get-genome -L -d", genome, "-D", genome_dir)))[,1]
}
tally2GR<- function(bamfiles,
genome = "hg19_ucsc",
genome_dir = "/gnet/is2/data/bioinfo/gmap/data/genomes",
chr_ids = gsnapChromosomes(genome, genome_dir),
regions,
variant_strand=1,
min_cov =1,
breaks=NULL,
bqual_thresh=56,
map_qual=13)
{
chr_ids <- as.list(as.character(chr_ids))
has_regions <- !missing(regions)
list_of_gr <- mclapply(chr_ids, function(chr_name){
tally <- pipe(paste("bam_tally -B 0 -C -Q -q", map_qual, " -X ", variant_strand, " -n ",
min_cov, " -T -d", genome, "-D", genome_dir, bamfiles,
paste("'", chr_name, ":' 2> /dev/null", sep = "")))
tab <- read.table(tally, colClasses = c("character", "integer", "integer",
"character"), sep = "\t",
col.names = c("chrom", "position", "count", "cycles"))
if(dim(tab)[1] <1){
gr <- GRanges()
} else {
counts <- strsplit(tab[[4]], " ", fixed=TRUE)
counts_part <- PartitioningByWidth(elementNROWS(counts))
chr <- rep(tab[[1]], width(counts_part))
pos <- rep(tab[[2]], width(counts_part))
count.total <- rep(tab[[3]], width(counts_part))
## we only get duplicated locations if there is overlap across strands
## thus, we force the duplicated locations onto different strands
location <- paste(tab[[1]], tab[[2]], sep = ":")
location_dup <- duplicated(location)
strand <- rep("*", length(location))
strand[match(location[location_dup], location)] <- "+"
strand[location_dup] <- "-"
strand <- rep(strand, width(counts_part))
location <- rep(location, width(counts_part))
counts_flat <- unlist(counts, use.names=FALSE)
bases <- sub("(\\D).*", "\\1", counts_flat)
ref_rows <- start(counts_part)
ref <- rep(bases[ref_rows], width(counts_part))
zero_count <- !grepl("(", counts_flat, fixed=TRUE)
### FIXME: obscene hack to simplify code
counts_flat[zero_count] <- paste(counts_flat[zero_count], "(0@NA)", sep="")
cycles <- strsplit(sub(".*\\((.*?)\\).*", "\\1", counts_flat), ",",
fixed=TRUE)
ncycles <- elementNROWS(cycles)
cycles_flat <- unlist(cycles, use.names=FALSE)
cycles_counts <- unlist(strsplit(cycles_flat, "@", fixed=TRUE),
use.names=FALSE)
cycles_mat <- matrix(suppressWarnings(as.integer(cycles_counts)), nrow=2)
## insane code for counting up reads by strand
neg_cycle <- cycles_mat[2,] < 0
coord_ind <- rep(seq_along(cycles), ncycles)
strand_key <- paste(coord_ind, neg_cycle)
strand_key_uniq <- !duplicated(strand_key)
strand_key <- factor(strand_key, strand_key[strand_key_uniq])
neg_cycle_uniq <- neg_cycle[strand_key_uniq]
coord_ind_uniq <- coord_ind[strand_key_uniq]
strand_count <- rowsum(cycles_mat[1,], strand_key)
count.pos <- count.neg <- rep(0L, length(cycles))
## have to use which() here to drop the NA values
count.pos[coord_ind_uniq[which(!neg_cycle_uniq)]] <-
strand_count[which(!neg_cycle_uniq)]
count.neg[coord_ind_uniq[which(neg_cycle_uniq)]] <-
strand_count[which(neg_cycle_uniq)]
message("working on breaks")
if (!is.null(breaks)) {
### NOTE: overuse of rep() here might lead to over-long vectors
cycle_bins <- cut(rep(abs(cycles_mat[2,]), cycles_mat[1,]), breaks)
cycle_i <- factor(rep(rep(seq(length(cycles)), ncycles), cycles_mat[1,]),
seq(length(cycles)))
cycle_tab <- table(cycle_i, cycle_bins)
colnames(cycle_tab) <- paste(head(breaks, -1), tail(breaks, -1),
sep = ".")
ref_cycle_tab <- cycle_tab[rep(ref_rows, width(counts_part)),]
colnames(ref_cycle_tab) <- paste(colnames(cycle_tab), "ref", sep = ".")
cycle_tab <- cbind(cycle_tab, ref_cycle_tab)
} else cycle_tab <- matrix(nrow = length(pos), ncol = 0)
message("completed breaks")
base_counts <- as.integer(sub("\\D(\\d+).*", "\\1", counts_flat))
ncycles[zero_count] <- 0L # otherwise 1 due to our obscene hack above
ncycles.ref <- rep(ncycles[ref_rows], width(counts_part))
count.ref <- rep(base_counts[ref_rows], width(counts_part))
count.pos[zero_count] <- 0L
count.pos.ref <- rep(count.pos[ref_rows], width(counts_part))
count.neg[zero_count] <- 0L
count.neg.ref <- rep(count.neg[ref_rows], width(counts_part))
quals <- strsplit(sub(".*\\)\\((.*?)\\).*", "\\1", counts_flat), ",",
fixed=TRUE)
nquals <- elementNROWS(quals)
count_above_thresh <- lapply(quals, function(x){
mat <-matrix(unlist(strsplit(x, "Q", fixed=TRUE),
use.names=FALSE), nrow=2)
logical <- (as.numeric(mat[2,]))>bqual_thresh
sum(as.numeric(mat[1,logical]), na.rm=T)
})
high_qual <- unlist(count_above_thresh)
gr <- GRanges(chr, IRanges(pos, width=1L), strand, location,
ref = DNAStringSet(ref), read = DNAStringSet(bases),
ncycles, ncycles.ref,
count = base_counts, count.ref, count.total, high.quality = high_qual,
count.pos, count.pos.ref, count.neg, count.neg.ref,
cycleCount = unclass(cycle_tab))
##adding ref counts back in as counts per break segment
##there seems to be a bug somewhere above that is causing the ref positions to be listed twice some times. Removing these for now
gr <- gr[as.character(values(gr)$ref) != as.character(values(gr)$read)]
if (has_regions) {
region_ol <- findOverlaps(gr, regions)
region_strand <- as.vector(strand(regions))[subjectHits(region_ol)]
strand(gr) <- region_strand
rc <- region_strand == "-"
values(gr)$ref[rc] <- reverseComplement(values(gr)$ref[rc])
values(gr)$read[rc] <- reverseComplement(values(gr)$read[rc])
}
values(gr)$location <- paste(values(gr)$location, strand(gr), sep = ":")
}
message(paste("finished chr ", chr_name))
seqlevels(gr) <- unlist(chr_ids)
gr
})
GR_full <- do.call(c, list_of_gr)
return(GR_full)
}
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