New approaches to identify cancer heterogeneity in DNA methylation studies using the lepage test and multinomial logistic regression

Seongkeon Lee, Youngjun Piao, Huidong Shi, Jeong-Hyeon Choi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations

Abstract

It is well known that cancer cells are diverse and heterogeneous among patients, and that this heterogeneity makes cancer diagnosis and cure difficult. Intra-tumoral heterogeneity has very recently become important because a small proportion of drug-resistant or tumor-initiating cells can ultimately determine a patient's outcome. In this study, we propose new approaches to use variance tests, including the Lepage test, to identify inter-patient cancer heterogeneity, as well as multinomial logistic regression to identify intra-patient cancer heterogeneity, i.e., different epiallele composition. We conduct experiments to show the performance of the proposed approaches.

Original languageEnglish (US)
Title of host publication2015 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781479969265
DOIs
StatePublished - Oct 16 2015
EventIEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB 2015 - Niagara Falls, Canada
Duration: Aug 12 2015Aug 15 2015

Publication series

Name2015 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB 2015

Other

OtherIEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB 2015
CountryCanada
CityNiagara Falls
Period8/12/158/15/15

ASJC Scopus subject areas

  • Computational Theory and Mathematics
  • Health Informatics
  • Artificial Intelligence
  • Biomedical Engineering

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    Lee, S., Piao, Y., Shi, H., & Choi, J-H. (2015). New approaches to identify cancer heterogeneity in DNA methylation studies using the lepage test and multinomial logistic regression. In 2015 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB 2015 [7300318] (2015 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB 2015). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CIBCB.2015.7300318