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:
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')) |
Bug tracker:https://github.com/nilotpalsanyal/gwasinlps/issues
Last updated 3 days agofrom:fb141e0681. Checks:OK: 2. Indexed: no.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Oct 21 2024 |
| R-4.5-linux-x86_64 | OK | Oct 21 2024 |
Exports:GWASinlpsnlpsGLMnlpsLM
Dependencies:BHbigmemorybigmemory.sriclicodetoolsdplyrfansifastglmforeachgenericsglassoglmnetgluehorseshoeintervalsiteratorslatticelifecyclemagrittrMatrixMatrixGenericsmatrixStatsmclustmgcvmombfmvtnormncvregnlmepillarpkgconfigpracmaR6RcppRcppArmadilloRcppEigenrlangshapesparseMatrixStatssurvivaltibbletidyselectutf8uuidvctrswithr
