Package: GWASbyCluster 0.1.7

GWASbyCluster: Identifying Significant SNPs in Genome Wide Association Studies (GWAS) via Clustering

Identifying disease-associated significant SNPs using clustering approach. This package is implementation of method proposed in Xu et al (2019) <doi:10.1038/s41598-019-50229-6>.

Authors:Yan Xu, Li Xing, Jessica Su, Xuekui Zhang<[email protected]>, Weiliang Qiu <[email protected]>

GWASbyCluster_0.1.7.tar.gz
GWASbyCluster_0.1.7.zip(r-4.5)GWASbyCluster_0.1.7.zip(r-4.4)GWASbyCluster_0.1.7.zip(r-4.3)
GWASbyCluster_0.1.7.tgz(r-4.5-any)GWASbyCluster_0.1.7.tgz(r-4.4-any)GWASbyCluster_0.1.7.tgz(r-4.3-any)
GWASbyCluster_0.1.7.tar.gz(r-4.5-noble)GWASbyCluster_0.1.7.tar.gz(r-4.4-noble)
GWASbyCluster_0.1.7.tgz(r-4.4-emscripten)GWASbyCluster_0.1.7.tgz(r-4.3-emscripten)
GWASbyCluster.pdf |GWASbyCluster.html✨
GWASbyCluster/json (API)
NEWS

# Install 'GWASbyCluster' in R:
install.packages('GWASbyCluster', repos = c('https://ubclxing.r-universe.dev', 'https://cloud.r-project.org'))
Datasets:
  • esSim - An ExpressionSet Object Storing Simulated Genotype Data
  • esSimDiffPriors - An ExpressionSet Object Storing Simulated Genotype Data

On CRAN:

Conda:

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

1.00 score 141 downloads 4 exports 11 dependencies

Last updated 5 years agofrom:2ffc794c06. Checks:3 OK, 6 NOTE. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKMar 25 2025
R-4.5-winNOTEMar 25 2025
R-4.5-macNOTEMar 25 2025
R-4.5-linuxNOTEMar 25 2025
R-4.4-winNOTEMar 25 2025
R-4.4-macNOTEMar 25 2025
R-4.4-linuxNOTEMar 25 2025
R-4.3-winOKMar 25 2025
R-4.3-macOKMar 25 2025

Exports:estMemSNPsestMemSNPs.oneSetHyperParasimGenoFuncsimGenoFuncDiffPriors

Dependencies:BiobaseBiocGenericsgenericslatticelimmaMatrixrootSolvesnpStatsstatmodsurvivalzlibbioc