qc.sample: QC samples

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

Description

Compute QC metrics for each sample informing how much it fits the reference samples. It can compute: the average distance between a sample and the 10

Usage

qc.sample(bins.df, files.df = NULL, cnv.df = NULL, ref.samples = NULL,
  n.subset = 1000, nb.cores = 1)

Arguments

bins.df	a data.frame with information about the bins. Columns 'chr', 'start', 'end' are required.
files.df	a data.frame with information about the files, usually created by 'init.filenames'.
cnv.df	a data.frame with PopSV calls, created by 'call.abnormal.cov'.
ref.samples	a vector with the names of the samples used as reference. If NULL (default), all samples in 'files.df' are used.
n.subset	the number of bins to use to compute the metrics. Default is 1000.
nb.cores	number of cores to use. If higher than 1, parallel package is used to parallelized the counting.

Value

a data.frame with qc metrics for each sample of the input 'files.df'.

Author(s)

Jean Monlong

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