This is the development version of missMethyl; for the stable release version, see missMethyl.
Analysing Illumina HumanMethylation BeadChip DataBioconductor version: Development (3.22)
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>, Calandra Grima <calandra.grima at petermac.org>
Citation (from within R, entercitation("missMethyl")): Installation
To install this package, start R (version "4.5") and enter:
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
# The following initializes usage of Bioc devel
BiocManager::install(version='devel')
BiocManager::install("missMethyl")
For older versions of R, please refer to the appropriate Bioconductor release.
DocumentationTo view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("missMethyl")Follow Installation instructions to use this package in your R session.
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