getVars {PCAtools} | R Documentation

## getVars

### Description

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

### Usage

    getVars(
      pcaobj,
      components = NULL)

### Arguments

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

### Value

A `numeric` object.

### Author(s)

Kevin Blighe <kevin@clinicalbioinformatics.co.uk>, Myles Lewis <myles.lewis@qmul.ac.uk>

### 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)

[Package PCAtools version 1.0.0 Index]