_            _    _        _         _
      /\ \         /\ \ /\ \     /\_\      / /\
      \_\ \       /  \ \\ \ \   / / /     / /  \
      /\__ \     / /\ \ \\ \ \_/ / /     / / /\ \__
     / /_ \ \   / / /\ \ \\ \___/ /     / / /\ \___\
    / / /\ \ \ / / /  \ \_\\ \ \_/      \ \ \ \/___/
   / / /  \/_// / /   / / / \ \ \        \ \ \
  / / /      / / /   / / /   \ \ \   _    \ \ \
 / / /      / / /___/ / /     \ \ \ /_/\__/ / /
/_/ /      / / /____\/ /       \ \_\\ \/___/ /
\_\/       \/_________/         \/_/ \_____\/
r-missmethyl 1.40.0
Propagated dependencies: r-annotationdbi@1.68.0 r-biasedurn@2.0.12 r-biobase@2.66.0 r-biocgenerics@0.52.0 r-genomicranges@1.58.0 r-go-db@3.20.0 r-illuminahumanmethylation450kanno-ilmn12-hg19@0.6.1 r-illuminahumanmethylation450kmanifest@0.4.0 r-illuminahumanmethylationepicanno-ilm10b4-hg19@0.6.0 r-illuminahumanmethylationepicmanifest@0.3.0 r-illuminahumanmethylationepicv2anno-20a1-hg38@1.0.0 r-illuminahumanmethylationepicv2manifest@1.0.0 r-iranges@2.40.0 r-limma@3.62.1 r-methylumi@2.52.0 r-minfi@1.52.0 r-org-hs-eg-db@3.20.0 r-ruv@0.9.7.1 r-s4vectors@0.44.0 r-statmod@1.5.0 r-stringr@1.5.1 r-summarizedexperiment@1.36.0
Channel: guix
Location: gnu/packages/bioconductor.scm (gnu packages bioconductor)
Home page: https://bioconductor.org/packages/missMethyl
Licenses: GPL 2
Synopsis: Analyzing Illumina HumanMethylation BeadChip data
Description:

This is a package for normalization, testing for differential variability and differential methylation and gene set testing for data from Illumina's Infinium HumanMethylation arrays. The normalization procedure is subset-quantile within-array normalization (SWAN), which allows Infinium I and II type probes on a single array to be normalized 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.

Total results: 1