Package: qgg 1.1.6

Peter Soerensen

qgg: Statistical Tools for Quantitative Genetic Analyses

Provides an infrastructure for efficient processing of large-scale genetic and phenotypic data including core functions for: 1) fitting linear mixed models, 2) constructing marker-based genomic relationship matrices, 3) estimating genetic parameters (heritability and correlation), 4) performing genomic prediction and genetic risk profiling, and 5) single or multi-marker association analyses. Rohde et al. (2019) <doi:10.1101/503631>.

Authors:Peter Soerensen [aut, cre], Palle Duun Rohde [aut], Izel Fourie Soerensen [aut]

qgg_1.1.6.tar.gz
qgg_1.1.6.tar.gz(r-4.7-arm64)qgg_1.1.6.tar.gz(r-4.7-x86_64)qgg_1.1.6.tar.gz(r-4.6-arm64)qgg_1.1.6.tar.gz(r-4.6-x86_64)
manual.pdf |manual.html✨
card.svg |card.png
qgg/json (API)
NEWS

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

Bug tracker:https://github.com/psoerensen/qgg/issues

Uses libs:
  • openblas– Optimized BLAS
  • fortran– Runtime library for GNU Fortran applications
  • c++– GNU Standard C++ Library v3

On CRAN:

Conda:

openblasfortrancpp

2.72 score 53 scripts 315 downloads 2 mentions 52 exports 15 dependencies

Last updated from:0f0aebc63c. Checks:5 OK, 1 FAIL. Indexed: no.

TargetResultTimeFilesSyslog
linux-devel-arm64OK178
linux-devel-x86_64OK190
source / vignettesOK240
linux-release-arm64OK177
linux-release-x86_64OK267
wasm-releaseFAIL124

Exports:accadjLDadjLDStatadjStatadjustBadjustMapLDcheckStatcomputeROCcreateLDsetsgbayesgblupgetGgetGRMgetLDgetLDscoresgetLDsetsgetMapgetMarkersgetPosgetSparseLDgfilterglmagmapgprepgremlgrmgscoregseagsimgsimCgsimRgsolveldscldscoremagmamapSetsmapStatmergeGRMmtadjplotBayesplotForestplotLDplotROCpopspredict_auc_mt_ccpredict_auc_mt_continuouspredict_auc_stpredict_r2_mtpredict_r2_stsplitWithOverlapvegaswriteBED

Dependencies:codacorpcordata.tablelatticeMASSMatrixMatrixModelsmcmcMCMCpackquantregRcppRcppArmadilloSparseMstatmodsurvival