missMethyl
Analysing Illumina HumanMethylation BeadChip Data
Bioconductor version: Release (3.19)
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 <phipson.b at wehi.edu.au>, Jovana Maksimovic <jovana.maksimovic at petermac.org>, Andrew Lonsdale <andrew.lonsdale at petermac.org>
citation("missMethyl")
):
Installation
To install this package, start R (version "4.4") 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")
missMethyl: Analysing Illumina HumanMethylation BeadChip Data | HTML | R Script |
Reference Manual | ||
NEWS | Text |
Details
biocViews | DNAMethylation, DifferentialMethylation, GeneSetEnrichment, GeneticVariability, GenomicVariation, MethylationArray, Normalization, Software |
Version | 1.38.0 |
In Bioconductor since | BioC 3.0 (R-3.1) (10 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 |
System Requirements | |
URL |
See More
Suggests | BiocStyle, edgeR, knitr, minfiData, rmarkdown, tweeDEseqCountData, DMRcate, ExperimentHub |
Linking To | |
Enhances | |
Depends On Me | methylationArrayAnalysis |
Imports Me | DMRcate, MEAL, methylGSA |
Suggests Me | RnBeads |
Links To Me | |
Build Report | Build Report |
Package Archives
Follow Installation instructions to use this package in your R session.
Source Package | missMethyl_1.38.0.tar.gz |
Windows Binary (x86_64) | missMethyl_1.38.0.zip |
macOS Binary (x86_64) | missMethyl_1.38.0.tgz |
macOS Binary (arm64) | missMethyl_1.38.0.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 3.19 | Source Archive |