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

Bioconductor version: Release (3.19)

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.

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

Maintainer: Jiehuan sun <jiehuan.sun at>

Citation (from within R, enter citation("dcGSA")):


To install this package, start R (version "4.4") and enter:

if (!require("BiocManager", quietly = TRUE))


For older versions of R, please refer to the appropriate Bioconductor release.


Reference Manual PDF


biocViews GeneExpression, GeneSetEnrichment, ImmunoOncology, Microarray, RNASeq, Sequencing, Software, StatisticalMethod
Version 1.32.0
In Bioconductor since BioC 3.3 (R-3.3) (8 years)
License GPL-2
Depends R (>= 3.3), Matrix
Imports BiocParallel
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Follow Installation instructions to use this package in your R session.

Source Package dcGSA_1.32.0.tar.gz
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macOS Binary (x86_64) dcGSA_1.32.0.tgz
macOS Binary (arm64) dcGSA_1.32.0.tgz
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