BatchQC (version 1.0.17)

batchqc_pca_svd: Performs PCA svd variance decomposition and produces plot of the first two principal components

Description

Performs PCA svd variance decomposition and produces plot of the first two principal components

Usage

batchqc_pca_svd(data.matrix, batch, mod = NULL)

Arguments

data.matrix

Given data or simulated data from rnaseq_sim()

batch

Batch covariate

mod

Model matrix for outcome of interest and other covariates besides batch

Value

res PCA list with two components v and d.

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)
batchqc_pca_svd(data.matrix, batch, mod=modmatrix)