Journal Article

Gene set enrichment analysis using linear models and diagnostics

Assaf P. Oron, Zhen Jiang and Robert Gentleman

in Bioinformatics

Volume 24, issue 22, pages 2586-2591
Published in print November 2008 | ISSN: 1367-4803
Published online September 2008 | e-ISSN: 1460-2059 | DOI: http://dx.doi.org/10.1093/bioinformatics/btn465
Gene set enrichment analysis using linear models and diagnostics

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Motivation: Gene-set enrichment analysis (GSEA) can be greatly enhanced by linear model (regression) diagnostic techniques. Diagnostics can be used to identify outlying or influential samples, and also to evaluate model fit and explore model expansion.

Results: We demonstrate this methodology on an adult acute lymphoblastic leukemia (ALL) dataset, using GSEA based on chromosome-band mapping of genes. Individual residuals, grouped or aggregated by chromosomal loci, indicate problematic samples and potential data-entry errors, and help identify hyperdiploidy as a factor playing a key role in expression for this dataset. Subsequent analysis pinpoints suspected DNA copy number abnormalities of specific samples and chromosomes (most prevalent are chromosomes X, 21 and 14), and also reveals significant expression differences between the hyperdiploid and diploid groups on other chromosomes (most prominently 19, 22, 3 and 13)—differences which are apparently not associated with copy number.

Availability: Software for the statistical tools demonstrated in this article is available as Bioconductor package GSEAlm.

Contact: assaf.oron@gmail.com

Supplementary information: Supplementary data are available at Bioinformatics online.

Journal Article.  4238 words.  Illustrated.

Subjects: Bioinformatics and Computational Biology

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