An effective approach to identify gene-gene interactions for complex quantitative traits using generalized fuzzy accuracy

Xiangdong Zhou; Chun Chung Chan

doi:10.1109/CIBCB.2016.7758094

An effective approach to identify gene-gene interactions for complex quantitative traits using generalized fuzzy accuracy

Xiangdong Zhou, Chun Chung Chan

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

1 Citation (Scopus)

Abstract

Multifactor dimensionality reduction (MDR) is originally proposed to identify gene-gene and gene-environment interactions associated with binary traits. Some efforts have been made to extend it to quantitative traits (QTs) and ordinal traits. However these methods are still not computationally efficient or effective. In this paper, we propose Fuzzy Quantitative trait based Ordinal MDR (QOMDR) to strengthen identification of gene-gene interactions associated with a quantitative trait by first transforming it to an ordinal trait and then using a fuzzy balance accuracy measure based on generalized member function of fuzzy sets to select best sets of SNPs as having strong association with the trait. Experimental results on two real datasets show that our algorithm has better consistency and classification accuracy in identifying gene-gene interactions associated with QTs.

Original language	English
Title of host publication	CIBCB 2016 - Annual IEEE International Conference on Computational Intelligence in Bioinformatics and Computational Biology
Publisher	IEEE
ISBN (Electronic)	9781467394727
DOIs	https://doi.org/10.1109/CIBCB.2016.7758094
Publication status	Published - 28 Nov 2016
Event	13th IEEE International Conference on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB 2016 - Chiang Mai, Thailand Duration: 5 Oct 2016 → 7 Oct 2016

Conference

Conference	13th IEEE International Conference on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB 2016
Country/Territory	Thailand
City	Chiang Mai
Period	5/10/16 → 7/10/16

Keywords

fuzzy accuracy
gene-gene interactions
multifactor dimensionality reduction
ordinal traits
quantitative traits

ASJC Scopus subject areas

Computational Mathematics
Health Informatics
Agricultural and Biological Sciences (miscellaneous)
Biotechnology
Genetics
Artificial Intelligence

More information

10.1109/CIBCB.2016.7758094

Cite this

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title = "An effective approach to identify gene-gene interactions for complex quantitative traits using generalized fuzzy accuracy",

abstract = "Multifactor dimensionality reduction (MDR) is originally proposed to identify gene-gene and gene-environment interactions associated with binary traits. Some efforts have been made to extend it to quantitative traits (QTs) and ordinal traits. However these methods are still not computationally efficient or effective. In this paper, we propose Fuzzy Quantitative trait based Ordinal MDR (QOMDR) to strengthen identification of gene-gene interactions associated with a quantitative trait by first transforming it to an ordinal trait and then using a fuzzy balance accuracy measure based on generalized member function of fuzzy sets to select best sets of SNPs as having strong association with the trait. Experimental results on two real datasets show that our algorithm has better consistency and classification accuracy in identifying gene-gene interactions associated with QTs.",

keywords = "fuzzy accuracy, gene-gene interactions, multifactor dimensionality reduction, ordinal traits, quantitative traits",

author = "Xiangdong Zhou and Chan, {Chun Chung}",

year = "2016",

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Zhou, X & Chan, CC 2016, An effective approach to identify gene-gene interactions for complex quantitative traits using generalized fuzzy accuracy. in CIBCB 2016 - Annual IEEE International Conference on Computational Intelligence in Bioinformatics and Computational Biology., 7758094, IEEE, 13th IEEE International Conference on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB 2016, Chiang Mai, Thailand, 5/10/16. https://doi.org/10.1109/CIBCB.2016.7758094

An effective approach to identify gene-gene interactions for complex quantitative traits using generalized fuzzy accuracy. / Zhou, Xiangdong; Chan, Chun Chung.
CIBCB 2016 - Annual IEEE International Conference on Computational Intelligence in Bioinformatics and Computational Biology. IEEE, 2016. 7758094.

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

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AU - Zhou, Xiangdong

AU - Chan, Chun Chung

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N2 - Multifactor dimensionality reduction (MDR) is originally proposed to identify gene-gene and gene-environment interactions associated with binary traits. Some efforts have been made to extend it to quantitative traits (QTs) and ordinal traits. However these methods are still not computationally efficient or effective. In this paper, we propose Fuzzy Quantitative trait based Ordinal MDR (QOMDR) to strengthen identification of gene-gene interactions associated with a quantitative trait by first transforming it to an ordinal trait and then using a fuzzy balance accuracy measure based on generalized member function of fuzzy sets to select best sets of SNPs as having strong association with the trait. Experimental results on two real datasets show that our algorithm has better consistency and classification accuracy in identifying gene-gene interactions associated with QTs.

AB - Multifactor dimensionality reduction (MDR) is originally proposed to identify gene-gene and gene-environment interactions associated with binary traits. Some efforts have been made to extend it to quantitative traits (QTs) and ordinal traits. However these methods are still not computationally efficient or effective. In this paper, we propose Fuzzy Quantitative trait based Ordinal MDR (QOMDR) to strengthen identification of gene-gene interactions associated with a quantitative trait by first transforming it to an ordinal trait and then using a fuzzy balance accuracy measure based on generalized member function of fuzzy sets to select best sets of SNPs as having strong association with the trait. Experimental results on two real datasets show that our algorithm has better consistency and classification accuracy in identifying gene-gene interactions associated with QTs.

KW - fuzzy accuracy

KW - gene-gene interactions

KW - multifactor dimensionality reduction

KW - ordinal traits

KW - quantitative traits

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PB - IEEE

T2 - 13th IEEE International Conference on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB 2016

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An effective approach to identify gene-gene interactions for complex quantitative traits using generalized fuzzy accuracy

Abstract

Conference

Keywords

ASJC Scopus subject areas

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