RaceID (version 0.1.3)

clustdiffgenes: Inference of differentially expressed genes in a cluster

Description

This functions computes differentially expressed genes in a cluster by comparing to all remaining cells outside of the cluster based on a negative binomial model of gene expression

Usage

clustdiffgenes(object, cl, pvalue = 0.01)

Arguments

object

SCseq class object.

cl

A valid cluster number from the final cluster partition stored in the cpart slot of the SCseq object.

pvalue

Positive real number smaller than one. This is the p-value cutoff for the inference of differential gene expression. Default is 0.01.

Value

A data.frame of differentially expressed genes ordered by p-value in increasing order, with four columns:

mean.ncl

mean expression across cells outside of cluster cl.

mean.cl

mean expression across cells within cluster cl.

fc

fold-change of mean expression in cluster cl versus the remaining cells.

pv

inferred p-value for differential expression.

padj

Benjamini-Hochberg corrected FDR.

Examples

# NOT RUN {
sc <- SCseq(intestinalDataSmall)
sc <- filterdata(sc)
sc <- compdist(sc)
sc <- clustexp(sc)
sc <- findoutliers(sc)
x <- clustdiffgenes(sc,1)
head(x[x$fc>1,])
# }