batchqc_pca_svd: Performs PCA svd variance decomposition and produces plot of...

In BatchQC: Batch Effects Quality Control Software

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)

BatchQC documentation built on Nov. 8, 2020, 8:30 p.m.