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EpiReSIM: A Resampling Method of Epistatic Model without Marginal Effects Using Under-Determined System of Equations

Simulation experiments are essential to evaluate epistasis detection methods, which is the main way to prove their effectiveness and move toward practical applications. However, due to the lack of effective simulators, especially for simulating models without marginal effects (eNME models), epistasi...

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Detalles Bibliográficos
Autores principales: Shang, Junliang, Cai, Xinrui, Zhang, Tongdui, Sun, Yan, Zhang, Yuanyuan, Liu, Jinxing, Guan, Boxin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9777644/
https://www.ncbi.nlm.nih.gov/pubmed/36553553
http://dx.doi.org/10.3390/genes13122286
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author Shang, Junliang
Cai, Xinrui
Zhang, Tongdui
Sun, Yan
Zhang, Yuanyuan
Liu, Jinxing
Guan, Boxin
author_facet Shang, Junliang
Cai, Xinrui
Zhang, Tongdui
Sun, Yan
Zhang, Yuanyuan
Liu, Jinxing
Guan, Boxin
author_sort Shang, Junliang
collection PubMed
description Simulation experiments are essential to evaluate epistasis detection methods, which is the main way to prove their effectiveness and move toward practical applications. However, due to the lack of effective simulators, especially for simulating models without marginal effects (eNME models), epistasis detection methods can hardly verify their effectiveness through simulation experiments. In this study, we propose a resampling simulation method (EpiReSIM) for generating the eNME model. First, EpiReSIM provides two strategies for solving eNME models. One is to calculate eNME models using prevalence constraints, and another is by joint constraints of prevalence and heritability. We transform the computation of the model into the problem of solving the under-determined system of equations. Introducing the complete orthogonal decomposition method and Newton’s method, EpiReSIM calculates the solution of the underdetermined system of equations to obtain the eNME model, especially the solution of the high-order model, which is the highlight of EpiReSIM. Second, based on the computed eNME model, EpiReSIM generates simulation data by a resampling method. Experimental results show that EpiReSIM has advantages in preserving the biological properties of minor allele frequencies and calculating high-order models, and it is a convenient and effective alternative method for current simulation software.
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spelling pubmed-97776442022-12-23 EpiReSIM: A Resampling Method of Epistatic Model without Marginal Effects Using Under-Determined System of Equations Shang, Junliang Cai, Xinrui Zhang, Tongdui Sun, Yan Zhang, Yuanyuan Liu, Jinxing Guan, Boxin Genes (Basel) Article Simulation experiments are essential to evaluate epistasis detection methods, which is the main way to prove their effectiveness and move toward practical applications. However, due to the lack of effective simulators, especially for simulating models without marginal effects (eNME models), epistasis detection methods can hardly verify their effectiveness through simulation experiments. In this study, we propose a resampling simulation method (EpiReSIM) for generating the eNME model. First, EpiReSIM provides two strategies for solving eNME models. One is to calculate eNME models using prevalence constraints, and another is by joint constraints of prevalence and heritability. We transform the computation of the model into the problem of solving the under-determined system of equations. Introducing the complete orthogonal decomposition method and Newton’s method, EpiReSIM calculates the solution of the underdetermined system of equations to obtain the eNME model, especially the solution of the high-order model, which is the highlight of EpiReSIM. Second, based on the computed eNME model, EpiReSIM generates simulation data by a resampling method. Experimental results show that EpiReSIM has advantages in preserving the biological properties of minor allele frequencies and calculating high-order models, and it is a convenient and effective alternative method for current simulation software. MDPI 2022-12-04 /pmc/articles/PMC9777644/ /pubmed/36553553 http://dx.doi.org/10.3390/genes13122286 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Shang, Junliang
Cai, Xinrui
Zhang, Tongdui
Sun, Yan
Zhang, Yuanyuan
Liu, Jinxing
Guan, Boxin
EpiReSIM: A Resampling Method of Epistatic Model without Marginal Effects Using Under-Determined System of Equations
title EpiReSIM: A Resampling Method of Epistatic Model without Marginal Effects Using Under-Determined System of Equations
title_full EpiReSIM: A Resampling Method of Epistatic Model without Marginal Effects Using Under-Determined System of Equations
title_fullStr EpiReSIM: A Resampling Method of Epistatic Model without Marginal Effects Using Under-Determined System of Equations
title_full_unstemmed EpiReSIM: A Resampling Method of Epistatic Model without Marginal Effects Using Under-Determined System of Equations
title_short EpiReSIM: A Resampling Method of Epistatic Model without Marginal Effects Using Under-Determined System of Equations
title_sort epiresim: a resampling method of epistatic model without marginal effects using under-determined system of equations
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9777644/
https://www.ncbi.nlm.nih.gov/pubmed/36553553
http://dx.doi.org/10.3390/genes13122286
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