RaceID (version 0.3.9)

diffgenes: Compute Expression Differences between Clusters

Description

This functions computes expression differences between clusters and ranks genes by z-score differences.

Usage

diffgenes(object, cl1, cl2, mincount = 1)

Value

A list with four components:

z

a vector of z-scores in decreasing order with genes up-regulated in cl1 appearing at the top of the list.

cl1

a data.frame with expression values for cells in cl1.

cl2

a data.frame with expression values for cells in cl2.

cl1n

a vector of cluster numbers for cells in cl1.

cl2n

a vector of cluster numbers for cells in cl2.

Arguments

object

SCseq class object.

cl1

A vector of valid cluster numbers (contained in the cpart slot of the SCseq object). Represents the first group of the comparison.

cl2

A vector of valid cluster numbers (contained in the cpart slot of the SCseq object). Represents the second group of the comparison.

mincount

Minimal normalized expression level of a gene to be included into the analysis. A gene needs to be expressed at this level in at least a single cell.

Examples

sc <- SCseq(intestinalDataSmall)
sc <- filterdata(sc)
sc <- compdist(sc)
sc <- clustexp(sc)
sc <- findoutliers(sc)
x <- diffgenes(sc,1,2)
head(x$z)
plotdiffgenes(x,names(x$z)[1])