To install this package, start R and enter:

## try http:// if https:// URLs are not supported
source("https://bioconductor.org/biocLite.R")
biocLite("ramwas")

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ramwas

 

   

Fast Methylome-Wide Association Study Pipeline for Enrichment Platforms

Bioconductor version: Release (3.5)

RaMWAS provides 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.

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 <ashabalin at vcu.edu>

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

Installation

To install this package, start R and enter:

## try http:// if https:// URLs are not supported
source("https://bioconductor.org/biocLite.R")
biocLite("ramwas")

Documentation

HTML R Script 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. Analyzing data from other sources
HTML R Script 6. RaMWAS parameters
PDF   Reference Manual
Text   NEWS

Details

biocViews BatchEffect, Coverage, DNAMethylation, DifferentialMethylation, Normalization, Preprocessing, PrincipalComponent, QualityControl, Sequencing, Software, Visualization
Version 1.0.0
In Bioconductor since BioC 3.5 (R-3.4) (< 6 months)
License LGPL-3
Depends R (>= 3.3.0), methods, filematrix
Imports graphics, stats, utils, digest, glmnet, KernSmooth, grDevices, GenomicAlignments, Rsamtools, parallel, biomaRt, Biostrings, BiocGenerics
LinkingTo
Suggests knitr, rmarkdown, pander, BiocStyle, BSgenome.Hsapiens.UCSC.hg19, SNPlocs.Hsapiens.dbSNP144.GRCh37, BSgenome.Ecoli.NCBI.20080805
SystemRequirements
Enhances
URL https://bioconductor.org/packages/ramwas/
BugReports https://github.com/andreyshabalin/ramwas/issues
Depends On Me
Imports Me
Suggests Me
Build Report  

Package Archives

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

Package Source ramwas_1.0.0.tar.gz
Windows Binary ramwas_1.0.0.zip (32- & 64-bit)
Mac OS X 10.11 (El Capitan) ramwas_1.0.0.tgz
Subversion source (username/password: readonly)
Git source https://github.com/Bioconductor-mirror/ramwas/tree/release-3.5
Package Short Url http://bioconductor.org/packages/ramwas/
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