Detecting SNP–SNP Interactions in Imbalanced Case-Control Study
SNP–SNP interactions are particularly informative biomarkers regarding the genetic components of disease risk. However, SNP–SNP interaction identifications are yet limited in imbalanced case–control study. In this study, we proposed a multiobjective multifactor dimen...
| 出版年: | IEEE Access |
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| 主要な著者: | , , |
| フォーマット: | 論文 |
| 言語: | 英語 |
| 出版事項: |
IEEE
2019-01-01
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| 主題: | |
| オンライン･アクセス: | https://ieeexplore.ieee.org/document/8848412/ |
| _version_ | 1852729405902684160 |
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| author | Cheng-Hong Yang Li-Yeh Chuang Yu-Da Lin |
| author_facet | Cheng-Hong Yang Li-Yeh Chuang Yu-Da Lin |
| author_sort | Cheng-Hong Yang |
| collection | DOAJ |
| container_title | IEEE Access |
| description | SNP–SNP interactions are particularly informative biomarkers regarding the genetic components of disease risk. However, SNP–SNP interaction identifications are yet limited in imbalanced case–control study. In this study, we proposed a multiobjective multifactor dimensionality reduction (MOMDR) based on three balancing approaches (BMOMDR), including (1) stratified <inline-formula> <tex-math notation="LaTeX">$K$ </tex-math></inline-formula>-fold cross-validation; (2) balanced estimation of ratio between cases and controls; (3) balanced measures of SNP–SNP interactions, to effectively identify SNP–SNP interaction in imbalanced case–control study. BMOMDR was evaluated by extensive experiments on both simulated imbalanced case–control datasets and real genome-wide data from Wellcome Trust Case Control Consortium (WTCCC). For the simulated datasets, the results indicated that three balancing approaches can enhance the detection success rate of SNP–SNP interaction by MOMDR in imbalanced datasets. For WTCCC datasets, the results of SNP–SNP interaction detection obtained from BMOMDR revealed statistically significant (<inline-formula> <tex-math notation="LaTeX">$p < 0.0001$ </tex-math></inline-formula>), revealing that BMOMDR can effectively identify SNP–SNP interaction in imbalanced case–control study. BMOMDR is freely available at <uri>http://shorturl.at/bluJS</uri>. |
| format | Article |
| id | doaj-art-1a112b13e8b54cef83b08bd07b3f894e |
| institution | Directory of Open Access Journals |
| issn | 2169-3536 |
| language | English |
| publishDate | 2019-01-01 |
| publisher | IEEE |
| record_format | Article |
| spelling | doaj-art-1a112b13e8b54cef83b08bd07b3f894e2025-08-19T21:09:15ZengIEEEIEEE Access2169-35362019-01-01714303614304510.1109/ACCESS.2019.29436148848412Detecting SNP–SNP Interactions in Imbalanced Case-Control StudyCheng-Hong Yang0https://orcid.org/0000-0002-8816-5250Li-Yeh Chuang1Yu-Da Lin2https://orcid.org/0000-0001-5100-6072Department of Electronic Engineering, National Kaohsiung University of Applied Sciences, Kaohsiung, TaiwanDepartment of Chemical Engineering, Institute of Biotechnology and Chemical Engineering, I-Shou University, Kaohsiung, TaiwanDepartment of Electronic Engineering, National Kaohsiung University of Applied Sciences, Kaohsiung, TaiwanSNP–SNP interactions are particularly informative biomarkers regarding the genetic components of disease risk. However, SNP–SNP interaction identifications are yet limited in imbalanced case–control study. In this study, we proposed a multiobjective multifactor dimensionality reduction (MOMDR) based on three balancing approaches (BMOMDR), including (1) stratified <inline-formula> <tex-math notation="LaTeX">$K$ </tex-math></inline-formula>-fold cross-validation; (2) balanced estimation of ratio between cases and controls; (3) balanced measures of SNP–SNP interactions, to effectively identify SNP–SNP interaction in imbalanced case–control study. BMOMDR was evaluated by extensive experiments on both simulated imbalanced case–control datasets and real genome-wide data from Wellcome Trust Case Control Consortium (WTCCC). For the simulated datasets, the results indicated that three balancing approaches can enhance the detection success rate of SNP–SNP interaction by MOMDR in imbalanced datasets. For WTCCC datasets, the results of SNP–SNP interaction detection obtained from BMOMDR revealed statistically significant (<inline-formula> <tex-math notation="LaTeX">$p < 0.0001$ </tex-math></inline-formula>), revealing that BMOMDR can effectively identify SNP–SNP interaction in imbalanced case–control study. BMOMDR is freely available at <uri>http://shorturl.at/bluJS</uri>.https://ieeexplore.ieee.org/document/8848412/SNP–SNP interactionsmultiobjective approach multifactor dimensionality reductionimbalanced case-control study |
| spellingShingle | Cheng-Hong Yang Li-Yeh Chuang Yu-Da Lin Detecting SNP–SNP Interactions in Imbalanced Case-Control Study SNP–SNP interactions multiobjective approach multifactor dimensionality reduction imbalanced case-control study |
| title | Detecting SNP–SNP Interactions in Imbalanced Case-Control Study |
| title_full | Detecting SNP–SNP Interactions in Imbalanced Case-Control Study |
| title_fullStr | Detecting SNP–SNP Interactions in Imbalanced Case-Control Study |
| title_full_unstemmed | Detecting SNP–SNP Interactions in Imbalanced Case-Control Study |
| title_short | Detecting SNP–SNP Interactions in Imbalanced Case-Control Study |
| title_sort | detecting snp x2013 snp interactions in imbalanced case control study |
| topic | SNP–SNP interactions multiobjective approach multifactor dimensionality reduction imbalanced case-control study |
| url | https://ieeexplore.ieee.org/document/8848412/ |
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