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GSAR

GSAR

GSAR (Gene Set Analysis in R) is a tool for gene set analysis (GSA). The GSAR algorithm uses multivariate non-parametrical testing methods to test null hypothesis against alternative hypotheses. For example, mean, variance, and net correlations structure. GSAR also includes visualisation function.

Topic

Statistics and probability; RNA-Seq; Microarray experiment; Gene expression

Details

  • Operation: Differential gene expression analysis; Gene expression correlation
  • Software interface: Command-line user interface; Library
  • Language: R
  • Operating system: Linux; Mac OS X; Microsoft Windows
  • License: GNU General Public License v>=2
  • Cost: Free
  • Version name: 1.20.0
  • Maturity: Mature
  • Credit: The Arkansas Biosciences Institute, the Arkansas Translational Research Institute, the National Institutes of Health (NIH).
  • Contact: Yasir Rahmatallah yrahmatallah _at_ uams.ed | Galina Glazko gvglazko _at_ uams.edu
  • Collection: Bioconductor

Publications

Rahmatallah Y, Zybailov B, Emmert-Streib F, Glazko G "GSAR: Bioconductor package for Gene Set analysis in R." BMC Bioinformatics. 2017 Jan 24;18(1):61. https://doi.org/10.1186/s12859-017-1482-6
PMID: 28118818
PMCID: PMC5259853


Rahmatallah Y, Emmert-Streib F, Glazko G "Gene set analysis for self-contained tests: complex null and specific alternative hypotheses." Bioinformatics 2012; 28(23):3073-80 https://doi.org/10.1093/bioinformatics/bts579
PMID: 23044539
PMCID: PMC3509490


Huber W, Carey VJ, Gentleman R, Anders S, Carlson M, Carvalho BS, Bravo HC, Davis S, Gatto L, Girke T, Gottardo R, Hahne F, Hansen KD, Irizarry RA, Lawrence M, Love MI, MacDonald J1, Obenchain V, Oleś AK, Pagès H, Reyes A, Shannon P, Smyth GK, Tenenbaum D, Waldron L, Morgan M "Orchestrating high-throughput genomic analysis with Bioconductor." Nat Methods. 2015 Feb;12(2):115-21. https://doi.org/10.1038/nmeth.3252
PMID: 25633503
PMCID: PMC4509590


Gentleman RC, Carey VJ, Bates DM, Bolstad B, Dettling M, Dudoit S, Ellis B, Gautier L, Ge Y, Gentry J, Hornik K, Hothorn T, Huber W, Iacus S, Irizarry R, Leisch F, Li C, Maechler M, Rossini AJ, Sawitzki G, Smith C, Smyth G, Tierney L, Yang JY, Zhang J. "Bioconductor: open software development for computational biology and bioinformatics." Genome Biol. 2004;5(10):R80. Epub 2004 Sep 15. https://doi.org/10.1186/gb-2004-5-10-r80
PMID: 15461798
PMCID: PMC545600


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