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Bioinformatics Advance Access published online on March 24, 2009
Bioinformatics, doi:10.1093/bioinformatics/btp171
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© The Author (2009). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

A web application to perform Linkage Disequilibrium and Linkage Analyses on a computational Grid

Jules Hernández-Sánchez 1,*, Jean-Alain Grunchec 1 and Sara Knott 1

1Institute of Evolutionary Biology, University of Edinburgh, King’s Buildings, Ashworth Laboratories, West Mains Road, EH9 3JT Edinburgh

*To whom correspondence should be addressed.Jules Hernández-Sánchez, E-mail: jules.hernandez{at}ed.ac.uk


  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 QTL when using historical information compared to 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.

Availability: The authors have implemented LDLA within the freely available GridQTL software (www.gridqtl.org.uk).

Contact: jules.hernandez{at}ed.ac.uk

Associate Editor: Prof. Martin Bishop

Received on October 31, 2008; revised on March 20, 2009; accepted on March 21, 2009

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