Analysing Illumina HumanMethylation BeadChip Data

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Documentation for package ‘missMethyl’ version 1.43.0

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missMethyl-package Introduction to the missMethyl package
contrasts.varFit Compute contrasts for a varFit object.
densityByProbeType Plot the beta value distributions of the Infinium I and II probe types relative to the overall beta value distribution.
getAdj Extract values adjusted for unwanted variation by RUVm
getINCs Extract intensity data for Illumina negative controls found on 450k or EPIC arrays.
getLeveneResiduals Obtain Levene residuals
getMappedEntrezIDs Get mapped Entrez Gene IDs from CpG probe names
gometh Gene ontology testing for Ilumina methylation array data
goregion Gene ontology testing of DMRs for Ilumina methylation array data
gsameth Generalised gene set testing for Illumina's methylation array data
gsaregion Generalised gene set testing for Illumina's methylation array data
gsaseq Generalised gene set testing for RNA-seq data
missMethyl Introduction to the missMethyl package
RUVadj RUV adjust
RUVfit Remove unwanted variation when testing for differential methylation
SWAN Subset-quantile Within Array Normalisation for Illumina Infinium HumanMethylation450 BeadChips
SWAN.default Subset-quantile Within Array Normalisation for Illumina Infinium HumanMethylation450 BeadChips
SWAN.MethyLumiSet Subset-quantile Within Array Normalisation for Illumina Infinium HumanMethylation450 BeadChips
SWAN.RGChannelSet Subset-quantile Within Array Normalisation for Illumina Infinium HumanMethylation450 BeadChips
topGSA Get table of top 20 enriched pathways
topRUV Table of top-ranked differentially methylated CpGs obatained from a differential methylation analysis using RUV
topVar Table of top-ranked differentially variable CpGs
varFit Testing for differential variability
varFit.default Testing for differential variability
varFit.DGEList Testing for differential variability
varFit.MethylSet Testing for differential variability