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

doi:10.1109/CIBCB.2015.7300318

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

Biochemistry and Molecular Biology

Research output: Chapter in Book/Report/Conference proceeding › Conference 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 language	English (US)
Title of host publication	2015 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB 2015
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781479969265
DOIs	https://doi.org/10.1109/CIBCB.2015.7300318
State	Published - Oct 16 2015
Event	IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB 2015 - Niagara Falls, Canada Duration: Aug 12 2015 → Aug 15 2015

Publication series

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

Other

Other	IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB 2015
Country/Territory	Canada
City	Niagara Falls
Period	8/12/15 → 8/15/15

ASJC Scopus subject areas

Computational Theory and Mathematics
Health Informatics
Artificial Intelligence
Biomedical Engineering

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1109/CIBCB.2015.7300318

Cite this

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 Article 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

New approaches to identify cancer heterogeneity in DNA methylation studies using the lepage test and multinomial logistic regression. / Lee, Seongkeon; Piao, Youngjun; Shi, Huidong et al.
2015 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB 2015. Institute of Electrical and Electronics Engineers Inc., 2015. 7300318 (2015 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB 2015).

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

Lee, S, Piao, Y, Shi, H & Choi, JH 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., IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB 2015, Niagara Falls, Canada, 8/12/15. https://doi.org/10.1109/CIBCB.2015.7300318

Lee S, Piao Y, Shi H, Choi JH. 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. Institute of Electrical and Electronics Engineers Inc. 2015. 7300318. (2015 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB 2015). doi: 10.1109/CIBCB.2015.7300318

Lee, Seongkeon ; Piao, Youngjun ; Shi, Huidong et al. / New approaches to identify cancer heterogeneity in DNA methylation studies using the lepage test and multinomial logistic regression. 2015 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB 2015. Institute of Electrical and Electronics Engineers Inc., 2015. (2015 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB 2015).

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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.",

author = "Seongkeon Lee and Youngjun Piao and Huidong Shi and Choi, {Jeong Hyeon}",

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AB - 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.

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

Abstract

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ASJC Scopus subject areas

UN SDGs

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