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Tests for finding complex patterns of differential expression in cancers: towards individualized medicine |
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| Authors: | |
| Institution: | (1) Department of Pathology, Center for Biomedical Informatics, and Interdisciplinary Biomedical Graduate Program, University of Pittsburgh, PA 15232 Pittsburgh, USA;(2) Clinical Genomics Facility, Center for Pathology Informatics, Benedum Center for Oncology Informatics, University of Pittsburgh Cancer Institute, Pittsburgh, PA 15232, USA;(3) Departments of Surgery and Human Genetics, University of Pittsburgh Medical School, Pittsburgh, PA 15232, USA;(4) Mount Sinai School of Medicine, One Gustave Levy Place, , Box 1668, East Building, Room 1070C, New York, NY 10029, USA |
| Abstract: | BackgroundMicroarray studies in cancer compare expression levels between two or more sample groups on thousands of genes. Data analysis follows a population-level approach (e.g., comparison of sample means) to identify differentially expressed genes. This leads to the discovery of 'population-level' markers, i.e., genes with the expression patterns A > B and B > A. We introduce the PPST test that identifies genes where a significantly large subset of cases exhibit expression values beyond upper and lower thresholds observed in the control samples. |
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