pc_assoc: Association tests for meta variables and principal components

In jdreyf/jdcbioinfo: Joslin Diabetes Center bioinformatics utilities

Association tests for meta variables and principal components

Description

Association tests for meta variables and principal components.

Usage

pc_assoc(
  object,
  pheno.df,
  metavars,
  num.pc = 10,
  seed = 100,
  plot = TRUE,
  name = "assoc_with_pc_pvals",
  width = 8,
  height = 7,
  xrot = 0,
  yrot = 0
)

Arguments

object	Matrix-like object with features (e.g. genes) as rows and samples as columns.
pheno.df	Data frame with rows as samples and columns as phenotypes.
metavars	A vector of column names in pheno.df.
num.pc	Number of principal components
seed	Random seed.
plot	Logical for plotting the p-values.
name	Name of the plot file.
width	Width of the plot.
height	Height of the plot.
xrot	rot angle (in degrees) by which the x- axis labels are to be rotated
yrot	rot angle (in degrees) by which the y- axis labels are to be rotated

Value

matrix of p-values.

jdreyf/jdcbioinfo documentation built on April 15, 2024, 6:37 p.m.