detectLowQualityCells.totalCounts: detectLowQualityCells.totalCounts

In jasonserviss/sp.scRNAseqData: Data and processing functions for the CIMseq.data package

Description

It is often the case that some samples from sequencing experiments are of low quality, in many cases due to issues during the sample preperation stage. Due to the fact that these samples represent a high level of technical noise, it is often desirable to remove these before downstream analysis which is facilitated by this function. The function achieves this by detecting cells whose sum across all genes is > mincount.

Arguments

counts	data.frame; A data frame with counts data with gene names as rownames and sample names as colnames.
mincount	numeric; A minimum colSum for which columns with a higher colSum will be detected. Default = 4e5.

Value

A logical vector with length = ncol(counts) that is TRUE when the counts data.frame column contains a sample with colSums > mincount.

Author(s)

Jason Serviss

Examples

set.seed(8292)
x <- runif(2e4)
y <- runif(2e4, 1, 100)
names <- paste0(letters, 1:2e4)
counts <- data.frame(a = x, b = y, c = y, row.names = names)
detectLowQualityCells.totalCounts(counts)

jasonserviss/sp.scRNAseqData documentation built on Jan. 8, 2020, 11:46 a.m.