gaga

(R) Gaga: a parsimonious and flexible model for differential expression analysis Bioconductor version: Release (2.10) Implements the GaGa model for high-throughput data analysis, including differential expression analysis, supervised gene clustering and classification. Additionally, it performs sequential sample size calculations using the GaGa and LNNGV models (the latter from EBarrays package).

Keywords for this software

Anything in here will be replaced on browsers that support the canvas element

References in zbMATH (referenced in 4 articles , 1 standard article )

Showing results 1 to 4 of 4.
Sorted by year (citations)

  1. Hong, Zhaoping; Lian, Heng: BOPA: A Bayesian hierarchical model for outlier expression detection (2012)
  2. Lund, Steven P.; Nettleton, Dan: The importance of distinct modeling strategies for gene and gene-specific treatment effects in hierarchical models for microarray data (2012)
  3. Newton, Michael A.; Chung, Lisa M.: Gamma-based clustering via ordered means with application to gene-expression analysis (2010)
  4. Rossell, David: Gaga: a parsimonious and flexible model for differential expression analysis (2009)