Package: martini 1.33.0

Hector Climente-Gonzalez

martini: GWAS Incorporating Networks

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.

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

martini_1.33.0.tar.gz
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martini_1.33.0.tgz(r-4.6-x86_64)martini_1.33.0.tgz(r-4.6-arm64)martini_1.33.0.tgz(r-4.5-x86_64)martini_1.33.0.tgz(r-4.5-arm64)
martini_1.33.0.tar.gz(r-4.7-arm64)martini_1.33.0.tar.gz(r-4.7-x86_64)martini_1.33.0.tar.gz(r-4.6-arm64)martini_1.33.0.tar.gz(r-4.6-x86_64)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
martini/json (API)

# Install 'martini' in R:
install.packages('martini', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/hclimente/martini/issues

Uses libs:
  • c++– GNU Standard C++ Library v3
Datasets:

On BioConductor:martini-1.33.0(bioc 3.24)martini-1.32.0(bioc 3.23)

softwaregenomewideassociationsnpgeneticvariabilitygeneticsfeatureextractiongraphandnetworknetworkbioinformaticsgenomicsgwasnetwork-analysissnpssystems-biologycpp

6.04 score 4 stars 34 scripts 16 exports 20 dependencies

Last updated from:f8b9bd1355. Checks:1 WARNING, 11 ERROR, 1 OK, 1 FAIL. Indexed: yes.

TargetResultTimeFilesSyslog
bioc-checksWARNING183
linux-devel-arm64ERROR312
linux-devel-x86_64ERROR476
source / vignettesOK217
linux-release-arm64ERROR312
linux-release-x86_64ERROR314
macos-release-arm64ERROR299
macos-release-x86_64ERROR417
macos-oldrel-arm64ERROR321
macos-oldrel-x86_64ERROR405
windows-develERROR271
windows-releaseERROR307
windows-oldrelERROR284
wasm-releaseFAIL172

Exports:get_GI_networkget_GM_networkget_GS_networkldweight_edgesplot_ideogramsconesscones_scones.cvscones.cv_search_conessigmodsigmod_sigmod.cvsigmod.cv_simulate_causal_snpssimulate_phenotype

Dependencies:BiocGenericscachemclicpp11fastmapgenericsglueigraphlatticelifecyclemagrittrMatrixmemoisepkgconfigRcppRcppEigenrlangsnpStatssurvivalvctrs

Running SConES
Experimental data | The network | References
Rendered fromscones_usage.Rmdusingknitr::rmarkdown

Last update: 2021-03-02
Started: 2017-07-13

Simulating SConES-based phenotypes
References
Rendered fromsimulate_phenotype.Rmdusingknitr::rmarkdown

Last update: 2021-03-02
Started: 2017-07-13