DESCRIPTION

Package: missMethyl
Type: Package
Title: Analysing Illumina HumanMethylation BeadChip Data
Version: 1.33.1
Date: 2020-09-16
Author: Belinda Phipson and Jovana Maksimovic 
Maintainer: Belinda Phipson <phipson.b@wehi.edu.au>, Jovana
        Maksimovic <jovana.maksimovic@petermac.org>,
        Andrew Lonsdale <andrew.lonsdale@petermac.org>
Depends: 
    R (>= 3.6.0),
    IlluminaHumanMethylation450kanno.ilmn12.hg19,
    IlluminaHumanMethylationEPICanno.ilm10b4.hg19
Imports:
    AnnotationDbi, 
    BiasedUrn,
    Biobase,
    BiocGenerics,
    GenomicRanges,
    GO.db,
    IlluminaHumanMethylation450kmanifest,
    IlluminaHumanMethylationEPICmanifest,
    IRanges,
    limma,
    methods,
    methylumi,
    minfi,
    org.Hs.eg.db,
    ruv,
    S4Vectors,
    statmod, 
    stringr,
    SummarizedExperiment
VignetteBuilder: knitr
Suggests: 
    BiocStyle, 
    edgeR,
    knitr,
    minfiData, 
    rmarkdown, 
    tweeDEseqCountData,
    DMRcate,
    ExperimentHub
Description: Normalisation, testing for differential variability and
	differential methylation and gene set testing for data from Illumina's 
	Infinium HumanMethylation arrays. The normalisation procedure is 
	subset-quantile within-array normalisation (SWAN), which allows 
	Infinium I and II type probes on a single array to be normalised 
	together. The test for differential variability is based on an 
	empirical Bayes version of Levene's test. Differential
	methylation testing is performed using RUV, which can adjust for
	systematic errors of unknown origin in high-dimensional data by
 	using negative control probes. Gene ontology analysis is performed
 	by taking into account the number of probes per gene on the
 	array, as well as taking into account multi-gene associated probes.
License: GPL-2
biocViews: Normalization, DNAMethylation, MethylationArray,
        GenomicVariation, GeneticVariability, DifferentialMethylation,
        GeneSetEnrichment
RoxygenNote: 7.1.1
Encoding: UTF-8