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Fuzzy set-based generalized multifactor dimensionality reduction analysis of gene-gene interactions

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dc.contributor.authorJung, Hye-Young-
dc.contributor.authorLeem, Sangseob-
dc.contributor.authorPark, Taesung-
dc.date.accessioned2018-05-29T02:09:06Z-
dc.date.available2018-05-29T11:10:06Z-
dc.date.issued2018-04-20-
dc.identifier.citationBMC Medical Genomics, 11(Suppl 2):32ko_KR
dc.identifier.issn1755-8794-
dc.identifier.urihttps://hdl.handle.net/10371/141242-
dc.description.abstractBackground
Gene-gene interactions (GGIs) are a known cause of missing heritability. Multifactor dimensionality reduction (MDR) is one of most commonly used methods for GGI detection. The generalized multifactor dimensionality reduction (GMDR) method is an extension of MDR method that is applicable to various types of traits, and allows covariate adjustments. Our previous Fuzzy MDR (FMDR) is another extension for overcoming simple binary classification. FMDR uses continuous member-ship values instead of binary membership values 0 and 1, improving power for detecting causal SNPs and more intuitive interpretations in real data analysis. Here, we propose the fuzzy generalized multifactor dimensionality reduction (FGMDR) method, as a combined analysis of fuzzy set-based analysis and GMDR method, to detect GGIs associated with diseases using fuzzy set theory.

Results
Through simulation studies for different types of traits, the proposed FGMDR showed a higher detection ratio of causal SNPs, compared to GMDR. We then applied FGMDR to two real data: Crohns disease (CD) data from the Wellcome Trust Case Control Consortium (WTCCC) with a binary phenotype and the Homeostasis Model Assessment of Insulin Resistance (HOMA-IR) data from Korean population with a continuous phenotype. The interactions derived by our method include the pre-reported interactions associated with phenotypes.

Conclusions
The proposed FGMDR performs well for GGI detection with covariate adjustments. The program written in R for FGMDR is available at http://statgen.snu.ac.kr/software/FGMDR

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ko_KR
dc.description.sponsorshipThis work was supported by the Bio-Synergy Research Project (2013M3A9C4078158) of the Ministry of Science, ICT and Future Planning through the National Research Foundation and by a grant of the Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI), funded by the Ministry of Health & Welfare, Republic of Korea (grant number: HI16C2037). The publication cost of this article was funded by a grant from the Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI), funded by the Ministry of Health & Welfare, Republic of Korea (grant number: HI16C2037).ko_KR
dc.language.isoenko_KR
dc.publisherBioMed Centralko_KR
dc.subjectGene-gene interactionko_KR
dc.subjectFuzzy-set theoryko_KR
dc.subjectFGMDRko_KR
dc.subjectMultifactor dimensionality reductionko_KR
dc.titleFuzzy set-based generalized multifactor dimensionality reduction analysis of gene-gene interactionsko_KR
dc.typeArticleko_KR
dc.contributor.AlternativeAuthor정혜영-
dc.contributor.AlternativeAuthor임상섭-
dc.contributor.AlternativeAuthor박태성-
dc.identifier.doi10.1186/s12920-018-0343-0-
dc.language.rfc3066en-
dc.rights.holderThe Author(s).-
dc.date.updated2018-04-22T03:31:44Z-
Appears in Collections:
College of Natural Sciences (자연과학대학)Dept. of Statistics (통계학과)Journal Papers (저널논문_통계학과)
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