DOI: 10.18129/B9.bioc.martini  

GWAS Incorporating Networks

Bioconductor version: Release (3.17)

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>

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


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


biocViews FeatureExtraction, GeneticVariability, Genetics, GenomeWideAssociation, GraphAndNetwork, Network, SNP, Software
Version 1.20.0
In Bioconductor since BioC 3.7 (R-3.5) (5.5 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
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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
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