Principal components (cor)relation with experimental covariates

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)

Arguments

pcaobj

A prcomp object

coldata

A data.frame object containing the experimental covariates

pcs

A numeric vector, containing the corresponding PC number

Value

A data.frame object with computed p values for each covariate and for each principal component

Examples

library(DESeq2)
#> Loading required package: S4Vectors
#> Loading required package: stats4
#> 
#> Attaching package: ‘S4Vectors’
#> The following object is masked from ‘package:utils’:
#> 
#>     findMatches
#> The following objects are masked from ‘package:base’:
#> 
#>     I, expand.grid, unname
#> Loading required package: IRanges
#> Loading required package: GenomicRanges
#> Loading required package: GenomeInfoDb
#> Loading required package: SummarizedExperiment
#> Loading required package: MatrixGenerics
#> Loading required package: matrixStats
#> 
#> Attaching package: ‘matrixStats’
#> The following objects are masked from ‘package:Biobase’:
#> 
#>     anyMissing, rowMedians
#> 
#> Attaching package: ‘MatrixGenerics’
#> The following objects are masked from ‘package:matrixStats’:
#> 
#>     colAlls, colAnyNAs, colAnys, colAvgsPerRowSet, colCollapse,
#>     colCounts, colCummaxs, colCummins, colCumprods, colCumsums,
#>     colDiffs, colIQRDiffs, colIQRs, colLogSumExps, colMadDiffs,
#>     colMads, colMaxs, colMeans2, colMedians, colMins, colOrderStats,
#>     colProds, colQuantiles, colRanges, colRanks, colSdDiffs, colSds,
#>     colSums2, colTabulates, colVarDiffs, colVars, colWeightedMads,
#>     colWeightedMeans, colWeightedMedians, colWeightedSds,
#>     colWeightedVars, rowAlls, rowAnyNAs, rowAnys, rowAvgsPerColSet,
#>     rowCollapse, rowCounts, rowCummaxs, rowCummins, rowCumprods,
#>     rowCumsums, rowDiffs, rowIQRDiffs, rowIQRs, rowLogSumExps,
#>     rowMadDiffs, rowMads, rowMaxs, rowMeans2, rowMedians, rowMins,
#>     rowOrderStats, rowProds, rowQuantiles, rowRanges, rowRanks,
#>     rowSdDiffs, rowSds, rowSums2, rowTabulates, rowVarDiffs, rowVars,
#>     rowWeightedMads, rowWeightedMeans, rowWeightedMedians,
#>     rowWeightedSds, rowWeightedVars
#> The following object is masked from ‘package:Biobase’:
#> 
#>     rowMedians
dds <- makeExampleDESeqDataSet_multifac(betaSD_condition = 3, betaSD_tissue = 1)
rlt <- DESeq2::rlogTransformation(dds)
pcaobj <- prcomp(t(assay(rlt)))
correlatePCs(pcaobj, colData(dds))
#>        condition      tissue
#> PC_1 0.003947752 0.630954041
#> PC_2 0.748774042 0.003947752
#> PC_3 0.748774042 0.748774042
#> PC_4 0.748774042 0.748774042