BatchQC (version 1.0.17)

batchqc_pc_explained_variation: Returns explained variation for each principal components

Description

Returns explained variation for each principal components

Usage

batchqc_pc_explained_variation(pcs, vars, condition, batch)

Arguments

pcs

Principal components in the given data

vars

Variance of the Principal components in the given data

condition

Condition covariate of interest

batch

Batch covariate

Value

Explained variation table for each principal components

Examples

nbatch <- 3
ncond <- 2
npercond <- 10
data.matrix <- rnaseq_sim(ngenes=50, nbatch=nbatch, ncond=ncond, npercond=
    npercond, basemean=10000, ggstep=50, bbstep=2000, ccstep=800, 
    basedisp=100, bdispstep=-10, swvar=1000, seed=1234)
batch <- rep(1:nbatch, each=ncond*npercond)
condition <- rep(rep(1:ncond, each=npercond), nbatch)
pdata <- data.frame(batch, condition)
modmatrix = model.matrix(~as.factor(condition), data=pdata)
pca <- batchqc_pca(data.matrix, batch, mod=modmatrix)
pcs <- t(data.frame(pca$x))
batchqc_pc_explained_variation(pcs, pca$sdev^2, condition, batch)