gage

gage performs gene-set enrichment analysis to detect differentially regulated gene sets and pathways from gene expression data across diverse experimental designs and sample sizes, including microarray studies.

Key Features:

• General applicability: Applicable to diverse datasets irrespective of sample size or experimental design.
• Superior performance: Demonstrates superior performance compared with GSEA and PAGE in consistency across studies, sensitivity and specificity, and inference of biologically relevant regulatory mechanisms.
• Novel mechanistic insights: Has identified novel regulatory mechanisms in contexts such as lung cancer progression and metastasis and, in an unpublished BMP6 study, implicated pathways in osteoblast differentiation including BMP-TGF beta, JAK-STAT, Wnt, and estrogen signaling.
• Comprehensive analysis capabilities: Provides functions for basic analysis, result processing and presentation, batch pipeline routines, comparisons between parallel studies, and integrated analysis of heterogeneous data from different sources.
• Implementation: Implemented as the "gage" package in the R programming environment.

Scientific Applications:

• Systems biology and genomics: Identification of pathway-level regulation and coordinated gene-set perturbations in genomic studies.
• Cancer research: Analysis of gene expression changes associated with cancer progression and metastasis, including lung cancer datasets.
• Developmental biology and differentiation: Investigation of regulatory pathways in developmental processes such as osteoblast differentiation (e.g., BMP6-related signaling).

Methodology:

Performs gene-set analysis with comparative evaluation against GSEA and PAGE, and provides routines for basic analysis, result processing and presentation, batch pipelines, cross-study comparisons, and integrated analysis of heterogeneous expression datasets; implemented as the "gage" R package.