correlatePCs {pcaExplorer} | R Documentation |
Computes the significance of (cor)relations between PCA scores and the sample
experimental covariates, using Kruskal-Wallis test for categorial variables
and the cor.test
based on Spearman's correlation for continuous
variables
correlatePCs(pcaobj, coldata, pcs = 1:4)
pcaobj |
A |
coldata |
A |
pcs |
A numeric vector, containing the corresponding PC number |
A data.frame
object with computed p values for each covariate
and for each principal component
library(DESeq2) dds <- makeExampleDESeqDataSet_multifac(betaSD_condition = 3,betaSD_tissue = 1) rlt <- rlogTransformation(dds) pcaobj <- prcomp(t(assay(rlt))) correlatePCs(pcaobj,colData(dds))