Note to users. If you're seeing this message, it means that your browser cannot find this page's style/presentation instructions -- or possibly that you are using a browser that does not support current Web standards. Find out more about why this message is appearing, and what you can do to make your experience of our site the best it can be.

Sci. Signal., 13 September 2011
Vol. 4, Issue 190, p. tr4
[DOI: 10.1126/scisignal.2001966]

TEACHING RESOURCES

Introduction to Statistical Methods for Analyzing Large Data Sets: Gene-Set Enrichment Analysis

Neil R. Clark and Avi Ma’ayan*

Department of Pharmacology and Systems Therapeutics and Systems Biology Center New York, Mount Sinai School of Medicine, New York, NY 10029, USA.

Abstract: This Teaching Resource provides lecture notes, slides, and a problem set for a series of lectures introducing the mathematical concepts behind gene-set enrichment analysis (GSEA) and were part of a course entitled "Systems Biology: Biomedical Modeling." GSEA is a statistical functional enrichment analysis commonly applied to identify enrichment of biological functional categories in sets of ranked differentially expressed genes from genome-wide mRNA expression data sets.

* Corresponding author. E-mail, avi.maayan{at}mssm.edu

Citation: N. R. Clark, A. Ma’ayan, Introduction to Statistical Methods for Analyzing Large Data Sets: Gene-Set Enrichment Analysis. Sci. Signal. 4, tr4 (2011).

Read the Full Text

To Advertise     Find Products

Science Signaling. ISSN 1937-9145 (online), 1945-0877 (print). Pre-2008: Science's STKE. ISSN 1525-8882