Package: GWAS.BAYES 1.15.0
GWAS.BAYES: Bayesian analysis of Gaussian GWAS data
This package is built to perform GWAS analysis using Bayesian techniques. Currently, GWAS.BAYES has functionality for the implementation of BICOSS (Williams, J., Ferreira, M. A., and Ji, T. (2022). BICOSS: Bayesian iterative conditional stochastic search for GWAS. BMC Bioinformatics), BGWAS (Williams, J., Xu, S., Ferreira, M. A.. (2023) "BGWAS: Bayesian variable selection in linear mixed models with nonlocal priors for genome-wide association studies." BMC Bioinformatics), and IEB. All methods currently are for the analysis of Gaussian phenotypes The research related to this package was supported in part by National Science Foundation awards DMS 1853549, DMS 1853556, and DMS 2054173.
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GWAS.BAYES_1.15.0.tar.gz
GWAS.BAYES_1.15.0.zip(r-4.5)GWAS.BAYES_1.15.0.zip(r-4.4)GWAS.BAYES_1.15.0.zip(r-4.3)
GWAS.BAYES_1.15.0.tgz(r-4.4-any)GWAS.BAYES_1.15.0.tgz(r-4.3-any)
GWAS.BAYES_1.15.0.tar.gz(r-4.5-noble)GWAS.BAYES_1.15.0.tar.gz(r-4.4-noble)
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GWAS.BAYES.pdf |GWAS.BAYES.html✨
GWAS.BAYES/json (API)
# Install 'GWAS.BAYES' in R: |
install.packages('GWAS.BAYES', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org')) |
On BioConductor:GWAS.BAYES-1.15.0(bioc 3.20)GWAS.BAYES-1.14.0(bioc 3.19)
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 2 months agofrom:963cbb5de4
Dependencies:cachemcaretclasscliclockcodetoolscolorspacecpp11crayondata.tablediagramdigestdplyre1071ellipsisfansifarverfastmapforeachfuturefuture.applyGAgenericsggplot2globalsgluegowergtablehardhatipredisobanditeratorsKernSmoothlabelinglatticelavalifecyclelimmalistenvlubridatemagrittrMASSMatrixmemoisemgcvModelMetricsmunsellnlmennetnumDerivparallellypillarpkgconfigplyrpROCprodlimprogressrproxypurrrR6RColorBrewerRcppRcppArmadillorecipesreshape2rlangrpartscalesshapeSQUAREMstatmodstringistringrsurvivaltibbletidyrtidyselecttimechangetimeDatetzdbutf8vctrsviridisLitewithr