PeakSegFPOP_file {PeakSegDisk}

PeakSegFPOP using disk storage

Description

Run the PeakSeg Functional Pruning Optimal Partitioning algorithm, using a file on disk to store the O(N) function piece lists, each of size O(log N). This is a low-level function that just runs the algo and produces the result files (without reading them into R), so normal users are recommended to instead use PeakSegFPOP_dir, which calls this function then reads the result files into R.

Usage

PeakSegFPOP_file(bedGraph.file, 
    pen.str, db.file = NULL)

Arguments

bedGraph.file

character scalar: tab-delimited tabular text file with four columns: chrom, chromStart, chromEnd, coverage. The algorithm creates a large temporary file in the same directory, so make sure that there is disk space available on that device.

pen.str

character scalar that can be converted to a numeric scalar via as.numeric: non-negative penalty. More penalty means fewer peaks. "0" and "Inf" are OK. Character is required rather than numeric, so that the user can reliably find the results in the output files, which are in the same directory as bedGraph.file, and named using the penalty value, e.g. coverage.bedGraph_penalty=136500650856.439_loss.tsv

db.file

character scalar: file for writing temporary cost function database – there will be a lot of disk writing to this file. Default NULL means to write the same disk where the input bedGraph file is stored; another option is tempfile() which may result in speedups if the input bedGraph file is on a slow network disk and the temporary storage is a fast local disk.

Value

A named list of input parameters, and the temporary cost function database file size in megabytes.

Author(s)

Toby Dylan Hocking

Examples

r <- function(chrom, chromStart, chromEnd, coverage){
  data.frame(chrom, chromStart, chromEnd, coverage)
}
four <- rbind(
  r("chr1", 0, 10,  2),
  r("chr1", 10, 20, 10),
  r("chr1", 20, 30, 14),
  r("chr1", 30, 40, 13))
dir.create(prob.dir <- tempfile())
coverage.bedGraph <- file.path(prob.dir, "coverage.bedGraph")
write.table(
  four, coverage.bedGraph,
  sep="\t", row.names=FALSE, col.names=FALSE)
pstr <- "10.5"
result.list <- PeakSegDisk::PeakSegFPOP_file(coverage.bedGraph, pstr)
dir(prob.dir)

## segments file can be read to see optimal segment means.
outf <- function(suffix){
  paste0(coverage.bedGraph, "_penalty=", pstr, suffix)
}
segments.bed <- outf("_segments.bed")
seg.df <- read.table(segments.bed)
names(seg.df) <- col.name.list$segments
seg.df

## loss file can be read to see optimal Poisson loss, etc.
loss.tsv <- outf("_loss.tsv")
loss.df <- read.table(loss.tsv)
names(loss.df) <- col.name.list$loss
loss.df