adjustedDasen {wateRmelon} | R Documentation |
adjustedDasen utilizes dasen normliasation to normalise autosomal CpGs, and infers the sex chromosome linked CpGs by linear interpolation on corrected autosomal CpGs.
adjustedDasen( mns, uns, onetwo, chr, offset_fit = TRUE, cores = 1, ret2 = FALSE, fudge = 100, ... )
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). |
a matrix of normalised beta values.
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.
data(melon) normalised_betas <- adjustedDasen(mns = methylated(melon), uns = unmethylated(melon), onetwo = fData(melon)[,fot(melon)], chr = fData(melon)$CHR, cores=1)