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

Jules Hernandez-Sanchez, Jean-Alain Grunchec, Sara Knott

Research output: Contribution to journalArticlepeer-review

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.

Original languageEnglish
Pages (from-to)1377-1383
Number of pages7
JournalBioinformatics
Volume25
Issue number11
DOIs
Publication statusPublished - 1 Jun 2009

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