Journal Article

Cancer outlier detection based on likelihood ratio test

Jianhua Hu

in Bioinformatics

Volume 24, issue 19, pages 2193-2199
Published in print October 2008 | ISSN: 1367-4803
Published online August 2008 | e-ISSN: 1460-2059 | DOI: http://dx.doi.org/10.1093/bioinformatics/btn372
Cancer outlier detection based on likelihood ratio test

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Motivation: Microarray experiments can be used to help study the role of chromosomal translocation in cancer development through cancer outlier detection. The aim is to identify genes that are up- or down-regulated in a subset of cancer samples in comparison to normal samples.

Results: We propose a likelihood-based approach which targets detecting the change of point in mean expression intensity in the group of cancer samples. A desirable property of the proposed approach is the availability of theoretical significance-level results. Simulation studies showed that the performance of the proposed approach is appealing in terms of both detection power and false discovery rate. And the real data example also favored the likelihood-based approach in terms of the biological relevance of the results.

Availability: R code to implement the proposed method in the statistical package R is available at: http://odin.mdacc.tmc.edu/~jhhu/cod-analysis/.

Contact: jhu@mdanderson.org

Supplementary information: Supplementary data are available at Bioinformatics online.

Journal Article.  2632 words.  Illustrated.

Subjects: Bioinformatics and Computational Biology

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