adjustedFunnorm: adjustedFunnorm

In schalkwyk/wateRmelon: Illumina DNA methylation array normalization and metrics

adjustedFunnorm

Description

adjustedFunnorm utilizes functional normliasation to normalise autosomal CpGs, and infers the sex chromosome linked CpGs by linear interpolation on corrected autosomal CpGs.

Usage

adjustedFunnorm(
  rgSet,
  nPCs = 2,
  sex = NULL,
  bgCorr = TRUE,
  dyeCorr = TRUE,
  keepCN = TRUE,
  ratioConvert = TRUE,
  verbose = TRUE
)

Arguments

rgSet	An object of class "RGChannelSet".
nPCs	Number of principal components from the control probes PCA.
sex	An optional numeric vector containing the sex of the samples.
bgCorr	Should the NOOB background correction be done, prior to functional normalization (see "preprocessNoob")
dyeCorr	Should dye normalization be done as part of the NOOB background correction (see "preprocessNoob")?
keepCN	Should copy number estimates be kept around? Setting to 'FALSE' will decrease the size of the output object significantly.
ratioConvert	Should we run "ratioConvert", ie. should the output be a "GenomicRatioSet" or should it be kept as a "GenomicMethylSet"; the latter is for experts.
verbose	Should the function be verbose?

Value

an object of class "GenomicRatioSet", unless "ratioConvert=FALSE" in which case an object of class "GenomicMethylSet".

References

Functional normalization of 450k methylation array data improves replication in large cancer studies, Fortin et al., 2014, Genome biology.
interpolatedXY: a two-step strategy to normalise DNA methylation microarray data avoiding sex bias, Wang et al., 2021.

Examples

## Not run: 
GRset <- adjustedFunnorm(RGSet)

## End(Not run)

schalkwyk/wateRmelon documentation built on Aug. 13, 2024, 9:52 a.m.