meffil.plot.pc.fit: Number of control matrix principal components

In perishky/meffil: Efficient algorithms for DNA methylation

Number of control matrix principal components

Description

Fits probe intensities to principal components of the microarray control matrix and calculates the resulting mean squared residuals for different numbers of principal components.

Usage

meffil.plot.pc.fit(
  qc.objects,
  fixed.effects = NULL,
  random.effects = NULL,
  n.cross = 10,
  name = "autosomal.ii"
)

Arguments

qc.objects	A list of outputs from meffil.create.qc.object().
fixed.effects	Names of columns in samplesheet that should be included as fixed effects along with control matrix principal components (Default: NULL).
random.effects	Names of columns in samplesheet that should be included as random effects (Default: NULL).
number.pcs	Number of principal components to include in the design matrix (Default: all).

Value

A list containing a data frame with the mean squared residuals for different numbers of principal components and a plot of these residuals.

perishky/meffil documentation built on June 9, 2024, 5:59 p.m.