adjustedDasen: adjustedDasen

In schalkwyk/wateRmelon: Illumina 450 and EPIC methylation array normalization and metrics

adjustedDasen

Description

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

Usage

adjustedDasen(
  mns,
  uns,
  onetwo,
  chr,
  offset_fit = TRUE,
  cores = 1,
  ret2 = FALSE,
  fudge = 100,
  ...
)

Arguments

mns	matrix of methylated signal intensities, samples in column and probes in row.
uns	matrix of unmethylated signal intensities, samples in column and probes in row.
onetwo	character vector or factor of length nrow(mns) indicating assay type 'I' or 'II'.
chr	character vector stores the mapped chromosomes for all probes, e.g. chr <- c('1', 'X', '21', ..., 'Y').
offset_fit	logical (default is TRUE). To use dasen, set it TRUE; to use nasen, set it FALSE.
cores	an integer(e.g. 8) defines the number of cores to parallel processing. Default value is 1, set to -1 to use all available cores.
ret2	logical (default is FALSE), if TRUE, returns a list of intensities and betas instead of a naked matrix of betas.
fudge	default 100, a value added to total intensity to prevent denominators close to zero when calculating betas, e.g. betas <- mns / (mns + uns + fudge).
...	additional argument roco for dfsfit giving Sentrix rows and columns. This allows a background gradient model to be fit. This is split from data column names by default. roco=NULL disables model fitting (and speeds up processing), otherwise roco can be supplied as a character vector of strings like 'R01C01' (only 3rd and 6th characters used).

Value

a matrix of normalised beta values.

References

A data-driven approach to preprocessing Illumina 450K methylation array data, Pidsley et al, BMC Genomics.
interpolatedXY: a two-step strategy to normalise DNA methylation microarray data avoiding sex bias, Wang et al., 2021.

Examples

data(melon)
normalised_betas <- adjustedDasen(mns = methylated(melon), uns = unmethylated(melon), onetwo = fData(melon)[,fot(melon)], chr = fData(melon)$CHR, cores=1)
## if input is an object of methylumiset or methylset
normalised_betas <- adjustedDasen(melon)

schalkwyk/wateRmelon documentation built on April 15, 2024, 12:06 p.m.