DOI: 10.18129/B9.bioc.dcGSA    

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

Bioconductor version: Release (3.6)

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 yale.edu>

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


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biocViews GeneExpression, GeneSetEnrichment, Microarray, RNASeq, Sequencing, Software, StatisticalMethod
Version 1.6.0
In Bioconductor since BioC 3.3 (R-3.3) (2 years)
License GPL-2
Depends R (>= 3.3), Matrix
Imports BiocParallel
Suggests knitr
Depends On Me
Imports Me
Suggests Me
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Source Package dcGSA_1.6.0.tar.gz
Windows Binary dcGSA_1.6.0.zip
Mac OS X 10.11 (El Capitan) dcGSA_1.6.0.tgz
Source Repository git clone https://git.bioconductor.org/packages/dcGSA
Package Short Url http://bioconductor.org/packages/dcGSA/
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