dcGSA

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>

Installation

To install this package, start R and enter:

## try http:// if https:// URLs are not supported
source("https://bioconductor.org/biocLite.R")
biocLite("dcGSA")

Documentation

PDF		Reference Manual
Text		NEWS

Details

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
LinkingTo
Suggests	knitr
SystemRequirements
Enhances
URL
Depends On Me
Imports Me
Suggests Me
Build Report

Package Archives

Follow Installation instructions to use this package in your R session.

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/
Package Downloads Report	Download Stats