Package: bWGR 2.2.13

Alencar Xavier

bWGR: Bayesian Whole-Genome Regression

Whole-genome regression methods on Bayesian framework fitted via EM or Gibbs sampling, single step (<doi:10.1534/g3.119.400728>), univariate and multivariate (<doi:10.1186/s12711-022-00730-w>, <doi:10.1093/genetics/iyae179>), with optional kernel term and sampling techniques (<doi:10.1186/s12859-017-1582-3>).

Authors:Alencar Xavier [aut, cre], William Muir [aut], David Habier [aut], Kyle Kocak [aut], Shizhong Xu [aut], Katy Rainey [aut]

bWGR_2.2.13.tar.gz
bWGR_2.2.13.tar.gz(r-4.5-noble)bWGR_2.2.13.tar.gz(r-4.4-noble)
bWGR_2.2.13.tgz(r-4.4-emscripten)bWGR_2.2.13.tgz(r-4.3-emscripten)
bWGR.pdf |bWGR.html✨
bWGR/json (API)

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

Peer review:

Uses libs:
  • c++– GNU Standard C++ Library v3
Datasets:
  • chr - Tetra-seed Pods
  • fam - Tetra-seed Pods
  • gen - Tetra-seed Pods
  • y - Tetra-seed Pods

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

cpp

2.17 score 1 stars 16 scripts 1.2k downloads 1 mentions 85 exports 4 dependencies

Last updated 21 days agofrom:ec402d2c31. Checks:OK: 2. Indexed: no.

TargetResultDate
Doc / VignettesOKDec 05 2024
R-4.5-linux-x86_64OKDec 05 2024

Exports:AccByCBayesABayesA2BayesBBayesB2BayesCBayesCpiBayesDpiBayesLBayesRRBayesRR2CNTEigenAccEigenARCEigenArcZEigenBDCSVDEigenCNTEigenEVDEigenGAUEigenGauZEigenGRMEigenJacobiSVDemBAemBBemBCemBCpiemBLemCVemDEemENemGWAemMLemML2emRRFUVBETAGAUGRMGS2EIGENGSEMGSFLMGSRRHmatIMPK2XKMUPKMUP2lassomarkovmcmcCVMEGAmixedmkrmkr2XMLMmmmrrmrr_floatmrr_svdmrr2XMRR3MRR3FmtgsrumtmixedMvSimYNNSNNSEARCHpredict_FLMSSSEMSibZSimGCSimYSimZsolver1xsolver1xFsolver2xsolver2xFSPCSPMUVBETAwgrXFUVBETAXSEMFYSEMFZFUVBETAZSEMF

Dependencies:latticeMatrixRcppRcppEigen

Readme and manuals

Help Manual

Help pageTopics
Bayesian Whole-Genome RegressionbWGR-package bWGR
Tetra-seed Podschr fam gen tpod y
MCMC Whole-genome RegressionBayesA BayesA2 BayesB BayesB2 BayesC BayesCpi BayesDpi BayesL BayesRR BayesRR2 GSEN KMUP KMUP2 mcmcCV wgr
Expectation-Maximization WGRemBA emBB emBC emBCpi emBL emCV emDE emEN emML emML2 emRR lasso
Multivariate RegressionFUVBETA GSEM MEGA mkr mkr2X MLM mrr mrr2X MRR3 MRR3F mrr_float mrr_svd SEM solver1x solver1xF solver2x solver2xF UVBETA XFUVBETA XSEMF YSEMF ZFUVBETA ZSEMF
Mixed model solverGS2EIGEN GSFLM GSRR mixed mm mtgsru mtmixed NNS NNSEARCH predict_FLMSS
Additional toolsAccByC CNT EigenAcc EigenARC EigenArcZ EigenBDCSVD EigenCNT EigenEVD EigenGAU EigenGauZ EigenGRM EigenJacobiSVD emGWA GAU GRM Hmat IMP K2X markov MvSimY SibZ SimGC SimY SimZ SPC SPM