getSNparams: Estimate parameters for finite mixture of Skew-Normal...

In skewr: Visualize Intensities Produced by Illumina's Human Methylation 450k BeadChip

Description

Utilizes smsn.mix from the mixsmsn package to find the parameters for a finite mixture of skew normal distributions to model the overall distribution of signal intensities for a subset of probes on the Illumina Infinium HumanMethylation450. The probes may be subset by type and methylated or unmethylated. It can also be specified whether the SNP(rs), imprinted(idmr), or ch probes should be included or filtered out prior to parameter estimation.

Usage

getSNparams(MethyLumiSet, allele = c('M', 'U'),
            type = c('I-red', 'I-green', 'II'),
            snps = TRUE, idmr = TRUE, ch = FALSE)

Arguments

MethyLumiSet	A MethyLumiSet object
allele	Should parameter estimation be done on the methylated or unmethylated signal intensities
type	Use the signal intensities for which probe type
snps	logical; should the rs probes be included in the dataset. The default is TRUE
idmr	logical; should the probes of imprinted gene loci be included in the dataset. The default is TRUE
ch	logical; should the ch probes be included in the dataset. The default is FALSE

Value

A Skew.normal object as returned by smsn.mix from the mixsmsn package with the means and modes of the components added.

Author(s)

Ryan Putney [e-mail]

References

Pidsley R, Wong CCY, Volta M, Lunnon K, Mill J, Schalwyk LC(2013). A data-driven approach to preprocessing Illumina 450k methylation array data. BMC Genomics, 14:293.

Prates MO, Cabral CRB, Lachos VH (2013).mixsmsn: Fitting Finite Mixture of Scale Mixture of Skew-Normal Distributions. Journal of Statistical Software, 54(12), 1-20. http://www.jstatsoft.org/v54/i12/

See Also

subsetProbes

Examples

if(require('wateRmelon')) {
  data(melon)
  mixes.raw.meth.II <- getSNparams(melon[,1], 'M', 'II')
}

skewr documentation built on Nov. 8, 2020, 8:08 p.m.