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ramwas

Fast Methylome-Wide Association Study Pipeline for Enrichment Platforms


Bioconductor version: Release (3.18)

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 "4.3") and enter:


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

BiocManager::install("ramwas")

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("ramwas")
1. Overview HTML R Script
2. CpG sets HTML R Script
3. BAM Quality Control Measures HTML R Script
4. Joint Analysis of Methylation and Genotype Data HTML R Script
5.a. Analyzing Illumina Methylation Array Data HTML R Script
5.c. Analyzing data from other sources HTML R Script
6. RaMWAS parameters HTML R Script
Reference Manual PDF
NEWS Text

Details

biocViews BatchEffect, Coverage, DNAMethylation, DifferentialMethylation, Normalization, Preprocessing, PrincipalComponent, QualityControl, Sequencing, Software, Visualization
Version 1.26.0
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
See More
Suggests knitr, rmarkdown, pander, BiocStyle, BSgenome.Ecoli.NCBI.20080805
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Package Archives

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

Source Package ramwas_1.26.0.tar.gz
Windows Binary ramwas_1.26.0.zip
macOS Binary (x86_64) ramwas_1.26.0.tgz
macOS Binary (arm64) ramwas_1.26.0.tgz
Source Repository git clone https://git.bioconductor.org/packages/ramwas
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/ramwas
Bioc Package Browser https://code.bioconductor.org/browse/ramwas/
Package Short Url https://bioconductor.org/packages/ramwas/
Package Downloads Report Download Stats