getComponents: Return the principal component labels for an object of class...

In kevinblighe/PCAtools: PCAtools: Everything Principal Components Analysis

Return the principal component labels for an object of class 'pca'.

Description

Return the principal component labels for an object of class 'pca'.

Usage

getComponents(pcaobj, components = NULL)

Arguments

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

Details

Return the principal component labels for an object of class 'pca'.

Value

A character 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)

  getComponents(p)

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