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Erschienen in:
2013 | OriginalPaper | Buchkapitel
Outlier Gene Set Analysis Combined with Top Scoring Pair Provides Robust Biomarkers of Pathway Activity
verfasst von : Michael F. Ochs, Jason E. Farrar, Michael Considine, Yingying Wei, Soheil Meschinchi, Robert J. Arceci
Erschienen in: Pattern Recognition in Bioinformatics
Verlag: Springer Berlin Heidelberg
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Cancer is a disease driven by pathway activity, while useful biomarkers to predict outcome (prognostic markers) or determine treatment (treatment markers) rely on individual genes, proteins, or metabolites. We provide a novel approach that isolates pathways of interest by integrating outlier analysis and gene set analysis and couple it to the top-scoring pair algorithm to identify robust biomarkers. We demonstrate this methodology on pediatric acute myeloid leukemia (AML) data. We develop a biomarker in primary AML tumors, demonstrate robustness with an independent primary tumor data set, and show that the identified biomarkers also function well in relapsed AML tumors.