missMethyl

DOI: 10.18129/B9.bioc.missMethyl  

Analysing Illumina HumanMethylation BeadChip Data

Bioconductor version: Release (3.16)

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.

Author: Belinda Phipson and Jovana Maksimovic

Maintainer: Belinda Phipson <belinda.phipson at petermac.org>, Jovana Maksimovic <jovana.maksimovic at petermac.org>, Andrew Lonsdale <andrew.lonsdale at petermac.org>

Installation

To install this package, start R (version "4.2") and enter:

if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

BiocManager::install("missMethyl")

For older versions of R, please refer to the appropriate Bioconductor release.

Documentation

To view documentation for the version of this package installed in your system, start R and enter:

browseVignettes("missMethyl")

 

HTML	R Script	missMethyl: Analysing Illumina HumanMethylation BeadChip Data
PDF		Reference Manual
Text		NEWS

Details

biocViews	DNAMethylation, DifferentialMethylation, GeneSetEnrichment, GeneticVariability, GenomicVariation, MethylationArray, Normalization, Software
Version	1.32.1
In Bioconductor since	BioC 3.0 (R-3.1) (8.5 years)
License	GPL-2
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
LinkingTo
Suggests	BiocStyle, edgeR, knitr, minfiData, rmarkdown, tweeDEseqCountData, DMRcate, ExperimentHub
SystemRequirements
Enhances
URL
Depends On Me	methylationArrayAnalysis
Imports Me	ChAMP, DMRcate, MEAL, methylGSA
Suggests Me	RnBeads
Links To Me
Build Report

Package Archives

Follow Installation instructions to use this package in your R session.

Source Package	missMethyl_1.32.1.tar.gz
Windows Binary	missMethyl_1.32.1.zip
macOS Binary (x86_64)	missMethyl_1.32.1.tgz
macOS Binary (arm64)	missMethyl_1.32.1.tgz
Source Repository	git clone https://git.bioconductor.org/packages/missMethyl
Source Repository (Developer Access)	git clone git@git.bioconductor.org:packages/missMethyl
Bioc Package Browser	https://code.bioconductor.org/browse/missMethyl/
Package Short Url	https://bioconductor.org/packages/missMethyl/
Package Downloads Report	Download Stats
Old Source Packages for BioC 3.16	Source Archive