methylInheritance

Permutation-Based Analysis associating Conserved Differentially Methylated Elements Across Multiple Generations to a Treatment Effect

Bioconductor version: 3.23 · Package version: 1.36.0

Permutation analysis, based on Monte Carlo sampling, for testing the hypothesis that the number of conserved differentially methylated elements, between several generations, is associated to an effect inherited from a treatment and that stochastic effect can be dismissed.

Installation

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

BiocManager::install("methylInheritance")

Details

Maintainer	Astrid Deschênes <adeschen@hotmail.com>
Author	Astrid Deschênes [cre, aut] (ORCID: <https://orcid.org/0000-0001-7846-6749>), Pascal Belleau [aut] (ORCID: <https://orcid.org/0000-0002-0802-1071>), Arnaud Droit [aut]
License	Artistic-2.0
URL	https://github.com/adeschen/methylInheritance
Bug Reports	https://github.com/adeschen/methylInheritance/issues
Downloads rank	336
Source branch	RELEASE_3_23
biocViews	BiologicalQuestion, DNAMethylation, DifferentialMethylation, Epigenetics, ImmunoOncology, MethylSeq, Sequencing, Software, StatisticalMethod, WholeGenome

Documentation

Inferring inheritance of differentially methylated changes across multiple generations

Download

Source package

Dependencies

Depends: R (>= 3.5)

Imports: methylKit, BiocParallel, GenomicRanges, IRanges, S4Vectors, methods, parallel, ggplot2, gridExtra, rebus

Suggests: BiocStyle, BiocGenerics, knitr, rmarkdown, RUnit, methInheritSim, testthat (>= 3.0.0)

Reverse dependencies

Suggests Me (1): methInheritSim