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martini

GWAS Incorporating Networks


Bioconductor version: Release (3.18)

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 riken.jp>

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

Installation

To install this package, start R (version "4.3") and enter:


if (!require("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")
Running SConES HTML R Script
Simulating SConES-based phenotypes HTML R Script
Reference Manual PDF

Details

biocViews FeatureExtraction, GeneticVariability, Genetics, GenomeWideAssociation, GraphAndNetwork, Network, SNP, Software
Version 1.22.0
In Bioconductor since BioC 3.7 (R-3.5) (6 years)
License GPL-3
Depends R (>= 4.0)
Imports igraph (>= 1.0.1), Matrix, memoise (>= 2.0.0), methods (>= 3.3.2), Rcpp (>= 0.12.8), snpStats(>= 1.20.0), stats, utils
System Requirements
URL https://github.com/hclimente/martini
Bug Reports https://github.com/hclimente/martini/issues
See More
Suggests biomaRt(>= 2.34.1), circlize (>= 0.4.11), STRINGdb(>= 2.2.0), httr (>= 1.2.1), IRanges(>= 2.8.2), S4Vectors(>= 0.12.2), knitr, testthat, readr, rmarkdown
Linking To Rcpp, RcppEigen (>= 0.3.3.5.0)
Enhances
Depends On Me
Imports Me
Suggests Me
Links To Me
Build Report Build Report

Package Archives

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

Source Package martini_1.22.0.tar.gz
Windows Binary martini_1.22.0.zip
macOS Binary (x86_64) martini_1.22.0.tgz
macOS Binary (arm64) martini_1.22.0.tgz
Source Repository git clone https://git.bioconductor.org/packages/martini
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/martini
Bioc Package Browser https://code.bioconductor.org/browse/martini/
Package Short Url https://bioconductor.org/packages/martini/
Package Downloads Report Download Stats