A web application to perform linkage disequilibrium and linkage analyses on a computational grid

Hernandez Sanchez, Julio, Grunchec, J-A, & Knott, S (2009) A web application to perform linkage disequilibrium and linkage analyses on a computational grid. Bioinformatics, 25(11), pp. 1377-1383.

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Abstract

Motivation: Unravelling the genetic architecture of complex traits requires large amounts of data, sophisticated models and large computational resources. The lack of user-friendly software incorporating all these requisites is delaying progress in the analysis of complex traits. Methods: Linkage disequilibrium and linkage analysis (LDLA) is a high-resolution gene mapping approach based on sophisticated mixed linear models, applicable to any population structure. LDLA can use population history information in addition to pedigree and molecular markers to decompose traits into genetic components. Analyses are distributed in parallel over a large public grid of computers in the UK. Results: We have proven the performance of LDLA with analyses of simulated data. There are real gains in statistical power to detect quantitative trait loci when using historical information compared with traditional linkage analysis. Moreover, the use of a grid of computers significantly increases computational speed, hence allowing analyses that would have been prohibitive on a single computer. © The Author 2009. Published by Oxford University Press. All rights reserved.

Impact and interest:

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ID Code: 58634
Item Type: Journal Article
Refereed: Yes
Additional Information: Articles free to read on journal website after 12 months
Keywords: molecular marker, bioinformatics; computer analysis; computer program; gene linkage disequilibrium; gene mapping; genetic analysis; genetic trait; linkage analysis; pedigree analysis; population structure; priority journal; quantitative trait locus; simulation; statistical, Computational Biology; Databases, Genetic; Linkage (Genetics); Linkage Disequilibrium; Quantitative Trait Loci; Software; User-Computer Interface
DOI: 10.1093/bioinformatics/btp171
ISSN: 13674803
Subjects: Australian and New Zealand Standard Research Classification > BIOLOGICAL SCIENCES (060000) > GENETICS (060400) > Quantitative Genetics (incl. Disease and Trait Mapping Genetics (060412)
Divisions: Current > Institutes > Institute of Health and Biomedical Innovation
Deposited On: 26 Mar 2013 05:31
Last Modified: 22 Jan 2015 06:15

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