quick.count: Counts reads across samples in a small number of bins

In jmonlong/PopSV: Population-based detection of structural variants from Read-Depth signal

Description

This function retrieves bin count for all samples in the input file information data.frame. It was designed to count reads in a small amount of bins (a subset of what will be used for the full analysis). This counts can be used later to compare a potentially large number samples and guide the selection of samples to consider in the analysis.

Usage

quick.count(files.df, bins.df, nb.cores = 1, col.files = NULL,
  nb.rand.bins = NULL, ...)

Arguments

files.df	a data.frame with the information about the files to use. Columns 'sample' and 'bam' are required.
bins.df	a data.frame with the information about the bins. Columns 'chr', 'start' and 'end' are required.
nb.cores	number of cores to use. If higher than 1, parallel package is used to parallelized the counting.
col.files	if non-NULL, the name of the column in 'files.df' with the filenames where the information should be retrieved from.
nb.rand.bins	if non-NULL, the number of bins to randomly choose. Default is NULL.
...	extra paramaters for 'bin.bam' function

Details

If ‘col.files="bc.gc.gz"', for example, the bin counts will be merged from the pre-computed files (the ones created by functions ’bin.bam' and 'correct.GC').

Value

a data.frame with the bin location and read counts for all samples.

Author(s)

Jean Monlong

jmonlong/PopSV documentation built on Sept. 15, 2019, 9:29 p.m.