Bioconductor version: Release (3.16)
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")
):
To install this package, start R (version "4.2") and enter:
if (!require("BiocManager", quietly = TRUE)) install.packages("BiocManager") BiocManager::install("dcGSA")
For older versions of R, please refer to the appropriate Bioconductor release.
Reference Manual | ||
Text | NEWS |
biocViews | GeneExpression, GeneSetEnrichment, ImmunoOncology, Microarray, RNASeq, Sequencing, Software, StatisticalMethod |
Version | 1.26.0 |
In Bioconductor since | BioC 3.3 (R-3.3) (7 years) |
License | GPL-2 |
Depends | R (>= 3.3), Matrix |
Imports | BiocParallel |
LinkingTo | |
Suggests | knitr |
SystemRequirements | |
Enhances | |
URL | |
Depends On Me | |
Imports Me | |
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Build Report |
Follow Installation instructions to use this package in your R session.
Source Package | dcGSA_1.26.0.tar.gz |
Windows Binary | dcGSA_1.26.0.zip |
macOS Binary (x86_64) | dcGSA_1.26.0.tgz |
macOS Binary (arm64) | dcGSA_1.26.0.tgz |
Source Repository | git clone https://git.bioconductor.org/packages/dcGSA |
Source Repository (Developer Access) | git clone git@git.bioconductor.org:packages/dcGSA |
Bioc Package Browser | https://code.bioconductor.org/browse/dcGSA/ |
Package Short Url | https://bioconductor.org/packages/dcGSA/ |
Package Downloads Report | Download Stats |
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