Package: dcGSA 1.35.0

Jiehuan sun

dcGSA: Distance-correlation based Gene Set Analysis for longitudinal gene expression profiles

Distance-correlation based Gene Set Analysis for longitudinal gene expression profiles. In longitudinal studies, the gene expression profiles were collected at each visit from each subject and hence there are multiple measurements of the gene expression profiles for each subject. The dcGSA package could be used to assess the associations between gene sets and clinical outcomes of interest by fully taking advantage of the longitudinal nature of both the gene expression profiles and clinical outcomes.

Authors:Jiehuan Sun [aut, cre], Jose Herazo-Maya [aut], Xiu Huang [aut], Naftali Kaminski [aut], and Hongyu Zhao [aut]

dcGSA_1.35.0.tar.gz
dcGSA_1.35.0.zip(r-4.5)dcGSA_1.35.0.zip(r-4.4)dcGSA_1.35.0.zip(r-4.3)
dcGSA_1.35.0.tgz(r-4.4-any)dcGSA_1.35.0.tgz(r-4.3-any)
dcGSA_1.35.0.tar.gz(r-4.5-noble)dcGSA_1.35.0.tar.gz(r-4.4-noble)
dcGSA_1.35.0.tgz(r-4.4-emscripten)dcGSA_1.35.0.tgz(r-4.3-emscripten)
dcGSA.pdf |dcGSA.html
dcGSA/json (API)
NEWS

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

Peer review:

Datasets:

On BioConductor:dcGSA-1.33.0(bioc 3.20)dcGSA-1.32.0(bioc 3.19)

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

immunooncologygenesetenrichmentmicroarraystatisticalmethodsequencingrnaseqgeneexpression

2.30 score 1 scripts 185 downloads 3 exports 11 dependencies

Last updated 23 days agofrom:a50f9059a8. Checks:OK: 1 WARNING: 6. Indexed: yes.

TargetResultDate
Doc / VignettesOKOct 30 2024
R-4.5-winWARNINGOct 30 2024
R-4.5-linuxWARNINGOct 30 2024
R-4.4-winWARNINGOct 30 2024
R-4.4-macWARNINGOct 30 2024
R-4.3-winWARNINGOct 30 2024
R-4.3-macWARNINGOct 30 2024

Exports:dcGSALDcovreadGMT

Dependencies:BHBiocParallelcodetoolscpp11formatRfutile.loggerfutile.optionslambda.rlatticeMatrixsnow