martini

DOI: 10.18129/B9.bioc.martini    

This package is for version 3.8 of Bioconductor; for the stable, up-to-date release version, see martini.

GWAS Incorporating Networks

Bioconductor version: 3.8

martini deals with the low power inherent to GWAS studies by using prior knowledge represented as a network. SNPs are the vertices of the network, and the edges represent biological relationships between them (genomic adjacency, belonging to the same gene, physical interaction between protein products). The network is scanned using SConES, which looks for groups of SNPs maximally associated with the phenotype, that form a close subnetwork.

Author: Hector Climente-Gonzalez [aut, cre], Chloe-Agathe Azencott [aut]

Maintainer: Hector Climente-Gonzalez <hector.climente at curie.fr>

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

Installation

To install this package, start R (version "3.5") and enter:

if (!requireNamespace("BiocManager", quietly = TRUE))
    install.packages("BiocManager")
BiocManager::install("martini")

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("martini")

 

HTML R Script Running SConES
HTML R Script Simulating SConES-based phenotypes
PDF   Reference Manual
Text   LICENSE

Details

biocViews FeatureExtraction, GeneticVariability, Genetics, GenomeWideAssociation, GraphAndNetwork, Network, SNP, Software
Version 1.2.0
In Bioconductor since BioC 3.7 (R-3.5) (1 year)
License MIT + file LICENSE
Depends R (>= 3.5)
Imports igraph (>= 1.0.1), Matrix, methods (>= 3.3.2), Rcpp (>= 0.12.8), snpStats(>= 1.20.0), S4Vectors(>= 0.12.2), stats, utils
LinkingTo Rgin, Rcpp, RcppEigen (>= 0.3.3.3.0)
Suggests biomaRt(>= 2.34.1), httr (>= 1.2.1), IRanges(>= 2.8.2), knitr, testthat, tidyverse, rmarkdown
SystemRequirements
Enhances
URL
Depends On Me
Imports Me
Suggests Me
Links To Me
Build Report  

Package Archives

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

Source Package martini_1.2.0.tar.gz
Windows Binary martini_1.2.0.zip (32- & 64-bit)
Mac OS X 10.11 (El Capitan) martini_1.2.0.tgz
Source Repository git clone https://git.bioconductor.org/packages/martini
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/martini
Package Short Url http://bioconductor.org/packages/martini/
Package Downloads Report Download Stats

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