Package: GWASinlps 2.4

Nilotpal Sanyal

GWASinlps: Non-Local Prior Based Iterative Variable Selection Tool for Genome-Wide Association Studies

Performs variable selection with data from Genome-wide association studies (GWAS), or other high-dimensional data with continuous, binary or survival outcomes, combining in an iterative framework the computational efficiency of the structured screen-and-select variable selection strategy based on some association learning and the parsimonious uncertainty quantification provided by the use of non-local priors (see Sanyal et al., 2019 <doi:10.1093/bioinformatics/bty472>).

Authors:Nilotpal Sanyal [aut, cre]

GWASinlps_2.4.tar.gz
GWASinlps_2.4.tar.gz(r-4.7-arm64)GWASinlps_2.4.tar.gz(r-4.7-x86_64)GWASinlps_2.4.tar.gz(r-4.6-arm64)GWASinlps_2.4.tar.gz(r-4.6-x86_64)
GWASinlps_2.4.tgz(r-4.6-emscripten)
manual.pdf |manual.html
card.svg |card.png
GWASinlps/json (API)
NEWS

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

Bug tracker:https://github.com/nilotpalsanyal/gwasinlps/issues

Pkgdown/docs site:https://nilotpalsanyal.github.io

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3

On CRAN:

Conda:

openblascpp

1.70 score 3 scripts 192 downloads 3 exports 44 dependencies

Last updated from:1dbe81e131. Checks:6 OK. Indexed: no.

TargetResultTimeFilesSyslog
linux-devel-arm64OK208
linux-devel-x86_64OK173
source / vignettesOK217
linux-release-arm64OK232
linux-release-x86_64OK174
wasm-releaseOK161

Exports:GWASinlpsnlpsGLMnlpsLM

Dependencies:BHbigmemorybigmemory.sriclicodetoolsdplyrfastglmforeachFormulagenericsglassoglmnetglueintervalsiteratorslatticelifecyclemagrittrMatrixMatrixGenericsmatrixStatsmclustmgcvmombfmvtnormncvregnlmepillarpkgconfigpracmaR6RcppRcppArmadilloRcppEigenrlangshapesparseMatrixStatssurvivaltibbletidyselectutf8uuidvctrswithr