methrix_pca: Principal Component Analysis

In CompEpigen/methrix: Fast and efficient summarization of generic bedGraph files from Bisufite sequencing

Principal Component Analysis

Description

Principal Component Analysis

Usage

methrix_pca(
  m,
  var = "top",
  top_var = 1000,
  ranges = NULL,
  pheno = NULL,
  do_plot = TRUE,
  n_pc = 2
)

Arguments

m	Input methrix object
var	Choose between random CpG sites ('rand') or most variable CpGs ('top').
top_var	Number of variable CpGs to use. Default 1000 Set it to NULL to use all CpGs (which is not recommended due to memory requirements). This option is mutually exclusive with ranges.
ranges	genomic regions to be summarized. Could be a data.table with 3 columns (chr, start, end) or a GenomicRanges object
pheno	Column name of colData(m). Default NULL. Will be used as a factor to color different groups
do_plot	Should a plot be generated?
n_pc	Default 2.

Value

PCA results

Examples

data('methrix_data')
methrix_pca(methrix_data, do_plot = FALSE)

CompEpigen/methrix documentation built on Sept. 23, 2023, 7:14 p.m.