Journal Article

Evaluating test statistics to select interesting genes in microarray experiments

Charles Kooperberg, Simonetta Sipione, Michael LeBlanc, Andrew D. Strand, Elena Cattaneo and James M. Olson

in Human Molecular Genetics

Volume 11, issue 19, pages 2223-2232
Published in print September 2002 | ISSN: 0964-6906
Published online September 2002 | e-ISSN: 1460-2083 | DOI: http://dx.doi.org/10.1093/hmg/11.19.2223
Evaluating test statistics to select interesting genes in microarray experiments

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A randomization procedure to evaluate the significance level and the false-discovery rate in complex microarray experiments is proposed. A related graph can be used to compare different test statistics that can be used to analyze the same experiment. This graph is closely related to receiver operator characteristic (ROC) curves. The proposed method is applied to a subset of the data from a cell-line experiment related to Huntington's disease. A small simulation study compares the effectiveness of the proposed procedure with the significance analysis of microarrays (SAM) procedure.

Journal Article.  6674 words.  Illustrated.

Subjects: Genetics and Genomics

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