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An improved fuzzy set-based multifactor dimensionality reduction for detecting epistasis.
Yang, Cheng-Hong; Chuang, Li-Yeh; Lin, Yu-Da.
Afiliación
  • Yang CH; Department of Electronic Engineering, National Kaohsiung University of Science and Technology, No. 415, Jiangong Rd., Sanmin Dist., Kaohsiung City, 80778, Taiwan; Ph. D. Program in Biomedical Engineering, Kaohsiung Medical University, No. 100, Shih-Chuan 1st Rd., Kaohsiung, 80708, Taiwan. Electronic address: chyang@cc.kuas.edu.tw.
  • Chuang LY; Department of Chemical Engineering & Institute of Biotechnology and Chemical Engineering, I-Shou University, No.1, Sec. 1, Syuecheng Rd., Dashu District, Kaohsiung, 84001, Taiwan. Electronic address: chuang@isu.edu.tw.
  • Lin YD; Department of Electronic Engineering, National Kaohsiung University of Science and Technology, No. 415, Jiangong Rd., Sanmin Dist., Kaohsiung City, 80778, Taiwan. Electronic address: yudalinemail@gmail.com.
Artif Intell Med ; 102: 101768, 2020 01.
Article en En | MEDLINE | ID: mdl-31980105
OBJECTIVE: Epistasis identification is critical for determining susceptibility to human genetic diseases. The rapid development of technology has enabled scalability to make multifactor dimensionality reduction (MDR) measurements an effective calculation tool that achieves superior detection. However, the classification of high-risk (H) or low-risk (L) groups in multidrug resistance operations calls for extensive research. METHODS AND MATERIAL: In this study, an improved fuzzy sigmoid (FS) method using the membership degree in MDR (FSMDR) was proposed for solving the limitations of binary classification. The FS method combined with MDR measurements yielded an improved ability to distinguish similar frequencies of potential multifactor genotypes. RESULTS: We compared our results with other MDR-based methods and FSMDR achieved superior detection rates on simulated data sets. The results indicated that the fuzzy classifications can provide insight into the uncertainty of H/L classification in MDR operation. CONCLUSION: FSMDR successfully detected significant epistasis of coronary artery disease in the Wellcome Trust Case Control Consortium data set.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Lógica Difusa / Epistasis Genética / Reducción de Dimensionalidad Multifactorial Tipo de estudio: Observational_studies / Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Revista: Artif Intell Med Asunto de la revista: INFORMATICA MEDICA Año: 2020 Tipo del documento: Article Pais de publicación: Países Bajos
Texto completo
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Lógica Difusa / Epistasis Genética / Reducción de Dimensionalidad Multifactorial Tipo de estudio: Observational_studies / Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Revista: Artif Intell Med Asunto de la revista: INFORMATICA MEDICA Año: 2020 Tipo del documento: Article Pais de publicación: Países Bajos