Package: geneSLOPE 0.38.1

geneSLOPE: Genome-Wide Association Study with SLOPE

Genome-wide association study (GWAS) performed with SLOPE, short for Sorted L-One Penalized Estimation, a method for estimating the vector of coefficients in linear model. In the first step of GWAS, SNPs are clumped according to their correlations and distances. Then, SLOPE is performed on data where each clump has one representative.

Authors:Damian Brzyski [aut], Christine Peterson [aut], Emmanuel J. Candes [aut], Malgorzata Bogdan [aut], Chiara Sabatti [aut], Piotr Sobczyk [cre, aut]

geneSLOPE_0.38.1.tar.gz
geneSLOPE_0.38.1.zip(r-4.5)geneSLOPE_0.38.1.zip(r-4.4)geneSLOPE_0.38.1.zip(r-4.3)
geneSLOPE_0.38.1.tgz(r-4.5-any)geneSLOPE_0.38.1.tgz(r-4.4-any)geneSLOPE_0.38.1.tgz(r-4.3-any)
geneSLOPE_0.38.1.tar.gz(r-4.5-noble)geneSLOPE_0.38.1.tar.gz(r-4.4-noble)
geneSLOPE_0.38.1.tgz(r-4.4-emscripten)geneSLOPE_0.38.1.tgz(r-4.3-emscripten)
geneSLOPE.pdf |geneSLOPE.html
geneSLOPE/json (API)

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

Bug tracker:https://github.com/psobczyk/geneslope/issues

On CRAN:

4.18 score 3 stars 7 scripts 195 downloads 6 exports 38 dependencies

Last updated 3 years agofrom:1c323d5abe. Checks:1 OK, 7 NOTE. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKFeb 07 2025
R-4.5-winNOTEFeb 07 2025
R-4.5-macNOTEFeb 07 2025
R-4.5-linuxNOTEFeb 07 2025
R-4.4-winNOTEFeb 07 2025
R-4.4-macNOTEFeb 07 2025
R-4.3-winNOTEFeb 07 2025
R-4.3-macNOTEFeb 07 2025

Exports:clump_snpsgui_geneSLOPEidentify_clumpread_phenotypescreen_snpsselect_snps

Dependencies:BHbigmemorybigmemory.sriclicodetoolscolorspacefansifarverforeachggplot2gluegtableisobanditeratorslabelinglatticelifecyclemagrittrMASSMatrixmgcvmunsellnlmepillarpkgconfigR6RColorBrewerRcppRcppArmadillorlangscalesSLOPEtibbleutf8uuidvctrsviridisLitewithr

Tutorial for GWAS with SLOPE

Rendered fromGWASwithSLOPE.Rmdusingknitr::rmarkdownon Feb 07 2025.

Last update: 2021-11-10
Started: 2015-10-28