DSpace Repository

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

Show simple item record

dc.contributor Universitat de Vic. Escola Politècnica Superior
dc.contributor Universitat de Vic. Grup de Recerca en Bioinformàtica i Estadística Mèdica
dc.contributor.author Cattaert, Tom
dc.contributor.author Urrea Gales, Víctor
dc.contributor.author Naj, Adam C.
dc.contributor.author De Lobel, Lizzy
dc.contributor.author De Wit, Vanessa
dc.contributor.author Fu, Mao
dc.contributor.author Mahachie John, Jestinah M.
dc.contributor.author Shen, Haiqing
dc.contributor.author Calle, M. Luz
dc.contributor.author Ritchie, Marylyn D.
dc.contributor.author Edwards, Todd L.
dc.contributor.author Van Steen, Kristel
dc.date.accessioned 2012-10-15T12:08:44Z
dc.date.available 2012-10-15T12:08:44Z
dc.date.created 2010-01
dc.date.issued 2010-04
dc.identifier.citation Cattaert T, Urrea V, Naj AC, De Lobel L, De Wit V, et al. (2010) FAM-MDR: A Flexible Family-Based Multifactor Dimensionality Reduction Technique to Detect Epistasis Using Related Individuals. PLoS ONE 5(4): e10304. doi:10.1371/journal.pone.0010304 ca_ES
dc.identifier.issn 1932-6203
dc.identifier.uri http://hdl.handle.net/10854/1898
dc.description.abstract 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. ca_ES
dc.format application/pdf
dc.format.extent 15 p. ca_ES
dc.language.iso eng ca_ES
dc.rights Aquest document està subjecte a aquesta llicència Creative Commons ca_ES
dc.rights.uri http://creativecommons.org/licenses/by-nc-nd/3.0/es/ ca_ES
dc.subject.other Epidemiologia genètica ca_ES
dc.subject.other Bioinformàtica ca_ES
dc.title FAM-MDR: a flexible family-based multifactor dimensionality reduction technique to detect epistasis using related individuals ca_ES
dc.type info:eu-repo/semantics/article ca_ES
dc.identifier.doi https://doi.org/10.1371/journal.pone.0010304
dc.rights.accesRights info:eu-repo/semantics/openAccess
dc.type.version info:eu-repo/semantics/publishedVersion
dc.indexacio Indexat a SCOPUS
dc.indexacio Indexat a WOS/JCR ca_ES

Files in this item

Show simple item record

Aquest document està subjecte a aquesta llicència Creative Commons Except where otherwise noted, this item's license is described as Aquest document està subjecte a aquesta llicència Creative Commons

Search RIUVic


Advanced Search

Browse

Statistics