resampleReferenceSamples: Pool and resample samples to create reference/background...

In dyohanne/RepAn: Differential abundance Analysis for deep sequenced immune repertoire (Repseq) datasets

Pool and resample samples to create reference/background repertoires, normalize samples to equal number of sequence reads

Description

Pool and resample samples to create reference/background repertoires, normalize samples to equal number of sequence reads

Usage

resampleReferenceSamples(repSeqObj, totalReads = 1e+05, resample = T,
  resampleSize = 1000, useProb = T)

Arguments

repSeqObj	is an object containing all repertoire sample data
totalReads	the total size of reads per sample to scale our data to. All repertoires are scaled to 100k reads by default.
resample	a boolean argument to decide whether to resample repertoires, needed when data is too big, default is True. If False, resamples as big as the original datasets are drawn from the pooled repertoire dataset
resampleSize	Maximum possible number of clonotype reads repertoires will be resampled to, default is 1000.
useProb	a boolean to indicate whether the resampling should be done probablistically or not.

Value

repSeq data object created by downsampling after pooling all datasets

dyohanne/RepAn documentation built on Feb. 3, 2023, 2:41 p.m.