ramwas

This is the development version of ramwas; for the stable release version, see ramwas.

Fast Methylome-Wide Association Study Pipeline for Enrichment Platforms

Bioconductor version: Development (3.19)

A complete toolset for methylome-wide association studies (MWAS). It is specifically designed for data from enrichment based methylation assays, but can be applied to other data as well. The analysis pipeline includes seven steps: (1) scanning aligned reads from BAM files, (2) calculation of quality control measures, (3) creation of methylation score (coverage) matrix, (4) principal component analysis for capturing batch effects and detection of outliers, (5) association analysis with respect to phenotypes of interest while correcting for top PCs and known covariates, (6) annotation of significant findings, and (7) multi-marker analysis (methylation risk score) using elastic net. Additionally, RaMWAS include tools for joint analysis of methlyation and genotype data. This work is published in Bioinformatics, Shabalin et al. (2018) .

Author: Andrey A Shabalin [aut, cre] , Shaunna L Clark [aut], Mohammad W Hattab [aut], Karolina A Aberg [aut], Edwin J C G van den Oord [aut]

Maintainer: Andrey A Shabalin <andrey.shabalin at gmail.com>

Citation (from within R, enter citation("ramwas")):

Installation

To install this package, start R (version "4.4") and enter:


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

# The following initializes usage of Bioc devel
BiocManager::install(version='devel')

BiocManager::install("ramwas")

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

Documentation


Reference Manual	PDF

Need some help? Ask on the Bioconductor Support site!

Details

biocViews	BatchEffect, Coverage, DNAMethylation, DifferentialMethylation, Normalization, Preprocessing, PrincipalComponent, QualityControl, Sequencing, Software, Visualization
Version	1.27.0
In Bioconductor since	BioC 3.5 (R-3.4) (7 years)
License	LGPL-3
Depends	R (>= 3.3.0), methods, filematrix
Imports	graphics, stats, utils, digest, glmnet, KernSmooth, grDevices, GenomicAlignments, Rsamtools, parallel, biomaRt, Biostrings, BiocGenerics
System Requirements
URL	https://bioconductor.org/packages/ramwas/
Bug Reports	https://github.com/andreyshabalin/ramwas/issues

Suggests	knitr, rmarkdown, pander, BiocStyle, BSgenome.Ecoli.NCBI.20080805
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Build Report	Build Report

Package Archives

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

Source Package
Windows Binary
macOS Binary (x86_64)
macOS Binary (arm64)
Source Repository	git clone https://git.bioconductor.org/packages/ramwas
Source Repository (Developer Access)	git clone git@git.bioconductor.org:packages/ramwas
Package Short Url	https://bioconductor.org/packages/ramwas/
Package Downloads Report	Download Stats