SAM-GS statistics

To access cutting-edge analytics on consensus tools, life science contexts and associated fields, you will need to subscribe to our premium service.


Citations per year

Citations chart

Popular tool citations

chevron_left Gene set enrichment analysis chevron_right
Popular tools chart

Tool usage distribution map

Tool usage distribution map

Associated diseases

Associated diseases

SAM-GS specifications


Unique identifier OMICS_09853
Alternative name Significance Analysis of Microarray for Gene Sets
Software type Package/Module
Interface Command line interface
Restrictions to use None
Operating system Unix/Linux
Programming languages Python, R
Computer skills Advanced
Stability Stable
Maintained Yes


Add your version


  • person_outline Yutaka Yasui <>

Publications for Significance Analysis of Microarray for Gene Sets

SAM-GS in publications

PMCID: 5598806
PMID: 28932104
DOI: 10.1177/1176935117730016

[…] on gene sampling, whereas self-contained methods use permutations based on subject sampling. we prefer the latter because it preserves correlations across genes in a set., in this article, we use significance analysis of microarray for gene sets (sam-gs), a method previously found to perform very well compared with 6 other self-contained methods. the performance was assessed in simulation […]

PMCID: 5112852
PMID: 27846233
DOI: 10.1371/journal.pone.0165543

[…] genes were fed into downstream analysis. raw data of the second set were downloaded from the sbv challenge website, and were separately pre-processed in the same way., sam-gsr is an extension of the sam-gs algorithm [], with an objective of identifying the core gene subset within each selected pathway. it consists of two steps: sam-gs to select relevant pathways and the reduction step to obtain […]

PMCID: 5053608
PMID: 27711232
DOI: 10.1371/journal.pone.0163918

[…] et al. [] use the l2 norm of a t-like statistic vector ∑i=1kdi2 and a permutation method to assess the significance of a gene set in their significance analysis of microarray to gene-set analyses (sam-gs) method. others include tomfohr et al. [] who use a singular value decomposition of expression levels to identify a metagene which is the eigenvector associated with the largest eigenvalue. […]

PMCID: 4418815
PMID: 25938587
DOI: 10.1371/journal.pone.0125442

[…] [–]. these tools can roughly be divided into two categories: (1) microarray data based methods, which in general access the full data matrices. representative examples include gsea [], safe [], sam-gs [];(2) significant gene list based methods, which utilize lists of significantly differentially expressed genes as input. representative examples include david [], funcassociate [], webgestalt […]

PMCID: 4453458
PMID: 25461803
DOI: 10.1038/bjc.2014.604

[…] gene set enrichment analysis was performed with 21 gene sets covering the significant biological processes from the go analysis, using the significance analysis of microarrays for gene sets (sam-gs) software, which is based on the moderated t-statistics in sam (). all gene sets were collected from the molecular signatures database except a prostate cancer-specific hypoxia gene set […]

To access a full list of publications, you will need to upgrade to our premium service.

SAM-GS institution(s)
Department of Public Health Sciences, School of Public Health, University of Alberta, Edmonton, AB, Canada

SAM-GS reviews

star_border star_border star_border star_border star_border
star star star star star

Be the first to review SAM-GS