Outlier gene set analysis combined with top scoring pair provides robust biomarkers of pathway activity

Michael F. Ochs; Jason E. Farrar; Michael Considine; Yingying Wei; Soheil Meschinchi; Robert J. Arceci

doi:10.1007/978-3-642-39159-0-5

Outlier gene set analysis combined with top scoring pair provides robust biomarkers of pathway activity

Michael F. Ochs, Jason E. Farrar, Michael Considine, Yingying Wei, Soheil Meschinchi, Robert J. Arceci

School of Medicine

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

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.

Original language	English (US)
Title of host publication	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages	47-58
Number of pages	12
Volume	7986 LNBI
DOIs	https://doi.org/10.1007/978-3-642-39159-0-5
State	Published - 2013
Event	8th IAPR International Conference on Pattern Recognition in Bioinformatics, PRIB 2013 - Nice, France Duration: Jun 17 2013 → Jun 20 2013

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	7986 LNBI
ISSN (Print)	03029743
ISSN (Electronic)	16113349

Other

Other	8th IAPR International Conference on Pattern Recognition in Bioinformatics, PRIB 2013
Country	France
City	Nice
Period	6/17/13 → 6/20/13

ASJC Scopus subject areas

Computer Science(all)
Theoretical Computer Science

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10.1007/978-3-642-39159-0-5

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Ochs, M. F., Farrar, J. E., Considine, M., Wei, Y., Meschinchi, S., & Arceci, R. J. (2013). Outlier gene set analysis combined with top scoring pair provides robust biomarkers of pathway activity. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7986 LNBI, pp. 47-58). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7986 LNBI). https://doi.org/10.1007/978-3-642-39159-0-5

Outlier gene set analysis combined with top scoring pair provides robust biomarkers of pathway activity. / Ochs, Michael F.; Farrar, Jason E.; Considine, Michael; Wei, Yingying; Meschinchi, Soheil; Arceci, Robert J.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 7986 LNBI 2013. p. 47-58 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7986 LNBI).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Ochs, MF, Farrar, JE, Considine, M, Wei, Y, Meschinchi, S & Arceci, RJ 2013, Outlier gene set analysis combined with top scoring pair provides robust biomarkers of pathway activity. in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). vol. 7986 LNBI, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 7986 LNBI, pp. 47-58, 8th IAPR International Conference on Pattern Recognition in Bioinformatics, PRIB 2013, Nice, France, 6/17/13. https://doi.org/10.1007/978-3-642-39159-0-5

Ochs MF, Farrar JE, Considine M, Wei Y, Meschinchi S, Arceci RJ. Outlier gene set analysis combined with top scoring pair provides robust biomarkers of pathway activity. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 7986 LNBI. 2013. p. 47-58. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-642-39159-0-5

Ochs, Michael F. ; Farrar, Jason E. ; Considine, Michael ; Wei, Yingying ; Meschinchi, Soheil ; Arceci, Robert J. / Outlier gene set analysis combined with top scoring pair provides robust biomarkers of pathway activity. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 7986 LNBI 2013. pp. 47-58 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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Outlier gene set analysis combined with top scoring pair provides robust biomarkers of pathway activity

Abstract

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