FAM-MDR: a flexible family-based multifactor dimensionality reduction technique to detect epistasis using related individuals.

We propose a novel multifactor dimensionality reduction method for epistasis detection in small or extended pedigrees, FAM-MDR. It combines features of the Genome-wide Rapid Association using Mixed Model And Regression approach (GRAMMAR) with Model-Based MDR (MB-MDR). We focus on continuous traits,...

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Autores principales:	Tom Cattaert, Víctor Urrea, Adam C Naj, Lizzy De Lobel, Vanessa De Wit, Mao Fu, Jestinah M Mahachie John, Haiqing Shen, M Luz Calle, Marylyn D Ritchie, Todd L Edwards, Kristel Van Steen
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2010
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/73364a32f96349eebd6e6cf8ab957a95
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spelling	oai:doaj.org-article:73364a32f96349eebd6e6cf8ab957a952021-11-25T06:24:20ZFAM-MDR: a flexible family-based multifactor dimensionality reduction technique to detect epistasis using related individuals.1932-620310.1371/journal.pone.0010304https://doaj.org/article/73364a32f96349eebd6e6cf8ab957a952010-04-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/20421984/pdf/?tool=EBIhttps://doaj.org/toc/1932-6203We propose a novel multifactor dimensionality reduction method for epistasis detection in small or extended pedigrees, FAM-MDR. It combines features of the Genome-wide Rapid Association using Mixed Model And Regression approach (GRAMMAR) with Model-Based MDR (MB-MDR). We focus on continuous traits, although the method is general and can be used for outcomes of any type, including binary and censored traits. When comparing FAM-MDR with Pedigree-based Generalized MDR (PGMDR), which is a generalization of Multifactor Dimensionality Reduction (MDR) to continuous traits and related individuals, FAM-MDR was found to outperform PGMDR in terms of power, in most of the considered simulated scenarios. Additional simulations revealed that PGMDR does not appropriately deal with multiple testing and consequently gives rise to overly optimistic results. FAM-MDR adequately deals with multiple testing in epistasis screens and is in contrast rather conservative, by construction. Furthermore, simulations show that correcting for lower order (main) effects is of utmost importance when claiming epistasis. As Type 2 Diabetes Mellitus (T2DM) is a complex phenotype likely influenced by gene-gene interactions, we applied FAM-MDR to examine data on glucose area-under-the-curve (GAUC), an endophenotype of T2DM for which multiple independent genetic associations have been observed, in the Amish Family Diabetes Study (AFDS). This application reveals that FAM-MDR makes more efficient use of the available data than PGMDR and can deal with multi-generational pedigrees more easily. In conclusion, we have validated FAM-MDR and compared it to PGMDR, the current state-of-the-art MDR method for family data, using both simulations and a practical dataset. FAM-MDR is found to outperform PGMDR in that it handles the multiple testing issue more correctly, has increased power, and efficiently uses all available information.Tom CattaertVíctor UrreaAdam C NajLizzy De LobelVanessa De WitMao FuJestinah M Mahachie JohnHaiqing ShenM Luz CalleMarylyn D RitchieTodd L EdwardsKristel Van SteenPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 5, Iss 4, p e10304 (2010)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Tom Cattaert Víctor Urrea Adam C Naj Lizzy De Lobel Vanessa De Wit Mao Fu Jestinah M Mahachie John Haiqing Shen M Luz Calle Marylyn D Ritchie Todd L Edwards Kristel Van Steen FAM-MDR: a flexible family-based multifactor dimensionality reduction technique to detect epistasis using related individuals.
description	We propose a novel multifactor dimensionality reduction method for epistasis detection in small or extended pedigrees, FAM-MDR. It combines features of the Genome-wide Rapid Association using Mixed Model And Regression approach (GRAMMAR) with Model-Based MDR (MB-MDR). We focus on continuous traits, although the method is general and can be used for outcomes of any type, including binary and censored traits. When comparing FAM-MDR with Pedigree-based Generalized MDR (PGMDR), which is a generalization of Multifactor Dimensionality Reduction (MDR) to continuous traits and related individuals, FAM-MDR was found to outperform PGMDR in terms of power, in most of the considered simulated scenarios. Additional simulations revealed that PGMDR does not appropriately deal with multiple testing and consequently gives rise to overly optimistic results. FAM-MDR adequately deals with multiple testing in epistasis screens and is in contrast rather conservative, by construction. Furthermore, simulations show that correcting for lower order (main) effects is of utmost importance when claiming epistasis. As Type 2 Diabetes Mellitus (T2DM) is a complex phenotype likely influenced by gene-gene interactions, we applied FAM-MDR to examine data on glucose area-under-the-curve (GAUC), an endophenotype of T2DM for which multiple independent genetic associations have been observed, in the Amish Family Diabetes Study (AFDS). This application reveals that FAM-MDR makes more efficient use of the available data than PGMDR and can deal with multi-generational pedigrees more easily. In conclusion, we have validated FAM-MDR and compared it to PGMDR, the current state-of-the-art MDR method for family data, using both simulations and a practical dataset. FAM-MDR is found to outperform PGMDR in that it handles the multiple testing issue more correctly, has increased power, and efficiently uses all available information.
format	article
author	Tom Cattaert Víctor Urrea Adam C Naj Lizzy De Lobel Vanessa De Wit Mao Fu Jestinah M Mahachie John Haiqing Shen M Luz Calle Marylyn D Ritchie Todd L Edwards Kristel Van Steen
author_facet	Tom Cattaert Víctor Urrea Adam C Naj Lizzy De Lobel Vanessa De Wit Mao Fu Jestinah M Mahachie John Haiqing Shen M Luz Calle Marylyn D Ritchie Todd L Edwards Kristel Van Steen
author_sort	Tom Cattaert
title	FAM-MDR: a flexible family-based multifactor dimensionality reduction technique to detect epistasis using related individuals.
title_short	FAM-MDR: a flexible family-based multifactor dimensionality reduction technique to detect epistasis using related individuals.
title_full	FAM-MDR: a flexible family-based multifactor dimensionality reduction technique to detect epistasis using related individuals.
title_fullStr	FAM-MDR: a flexible family-based multifactor dimensionality reduction technique to detect epistasis using related individuals.
title_full_unstemmed	FAM-MDR: a flexible family-based multifactor dimensionality reduction technique to detect epistasis using related individuals.
title_sort	fam-mdr: a flexible family-based multifactor dimensionality reduction technique to detect epistasis using related individuals.
publisher	Public Library of Science (PLoS)
publishDate	2010
url	https://doaj.org/article/73364a32f96349eebd6e6cf8ab957a95
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FAM-MDR: a flexible family-based multifactor dimensionality reduction technique to detect epistasis using related individuals.

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