Package: GWASinlps 2.3

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_2.3.tar.gz
GWASinlps_2.3.tar.gz(r-4.5-noble)GWASinlps_2.3.tar.gz(r-4.4-noble)
GWASinlps_2.3.tgz(r-4.4-emscripten)GWASinlps_2.3.tgz(r-4.3-emscripten)
GWASinlps.pdf |GWASinlps.html
GWASinlps/json (API)
NEWS

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

Peer review:

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

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

1.70 score 3 scripts 375 downloads 3 exports 45 dependencies

Last updated 1 months agofrom:fb141e0681. Checks:OK: 2. Indexed: no.

TargetResultDate
Doc / VignettesOKNov 20 2024
R-4.5-linux-x86_64OKNov 20 2024

Exports:GWASinlpsnlpsGLMnlpsLM

Dependencies:BHbigmemorybigmemory.sriclicodetoolsdplyrfansifastglmforeachgenericsglassoglmnetgluehorseshoeintervalsiteratorslatticelifecyclemagrittrMatrixMatrixGenericsmatrixStatsmclustmgcvmombfmvtnormncvregnlmepillarpkgconfigpracmaR6RcppRcppArmadilloRcppEigenrlangshapesparseMatrixStatssurvivaltibbletidyselectutf8uuidvctrswithr