getVars: Return the explained variation for each principal component...

In kevinblighe/PCAtools: PCAtools: Everything Principal Components Analysis

Return the explained variation for each principal component for an object of class 'pca'.

Description

Return the explained variation for each principal component for an object of class 'pca'.

Usage

getVars(pcaobj, components = NULL)

Arguments

pcaobj	Object of class 'pca' created by pca().
components	Indices of the principal components whose explained variances will be returned. If NULL, all values will be returned.

Details

Return the explained variation for each principal component for an object of class 'pca'.

Value

A numeric object.

Author(s)

Kevin Blighe <[e-mail]>

Examples

  options(scipen=10)
  options(digits=6)

  col <- 20
  row <- 20000
  mat1 <- matrix(
    rexp(col*row, rate = 0.1),
    ncol = col)
  rownames(mat1) <- paste0('gene', 1:nrow(mat1))
  colnames(mat1) <- paste0('sample', 1:ncol(mat1))

  mat2 <- matrix(
    rexp(col*row, rate = 0.1),
    ncol = col)
  rownames(mat2) <- paste0('gene', 1:nrow(mat2))
  colnames(mat2) <- paste0('sample', (ncol(mat1)+1):(ncol(mat1)+ncol(mat2)))

  mat <- cbind(mat1, mat2)

  metadata <- data.frame(row.names = colnames(mat))
  metadata$Group <- rep(NA, ncol(mat))
  metadata$Group[seq(1,40,2)] <- 'A'
  metadata$Group[seq(2,40,2)] <- 'B'
  metadata$CRP <- sample.int(100, size=ncol(mat), replace=TRUE)
  metadata$ESR <- sample.int(100, size=ncol(mat), replace=TRUE)

  p <- pca(mat, metadata = metadata, removeVar = 0.1)

  getVars(p)

kevinblighe/PCAtools documentation built on Oct. 22, 2023, 12:01 p.m.