High Performance QTL Analysis

An Integrative Biology Project

BBSRC

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GridQTL Project

Project Overview

The mapping of Quantitative Trait Loci (QTL) is the first step towards the identification of genes and other areas of the genome that affect important traits in human medicine and agriculture. Fast, efficient and robust methods to map QTL have been developed by groups at The Institute of Evolutionary Biology (IEB), Edinburgh University and The Roslin Institute, Edinburgh and were deployed in QTLExpress, the first publicly available Web-based application that could perform QTL mapping on a variety of population types.

GridQTL was released in the summer of 2006 and extended the functionality of QTLExpress by adding a Linkage-Disequilibruim-Linkage-Analysis (LDLA) tool in tandem with a Haplotyping analysis to enable higher resolution detection of QTL; an Epistasis option for 2-QTL determination in F2 populations was also implemented. This functionality was offered via a web portal which offered data persistence for management of users' output and distributed execution of analyses via a computational Grid system.

Project Goals

GridQTL's existing functionality will be maintained and new developments will be included in the future:

Towards a More Predictive Biology.

Workflow technolgies will be studied in order to adopt GridQTL as a core component of a future integrated biological system incorporating genetic, phenotypic, transcription and comparative information with the goal being to allow prediction from gene sequence to consequence.

Accessing the Cloud

Moving on from Grid computing technologies, Cloud computing models will be investigated with a view to managing the remote execution of analyses and computing costs.

At the Cutting Edge of QTL Methods

New innovations in QTL mapping will be followed for possible inclusion in future releases of GridQTL.

Citations

Users may publish any text or graphics output from GridQTL in original or adapted form. It is expected only that such material be presented or attributed in such a way that it is reasonably apparent that GridQTL was the original source. The proper citations are:

GridQTL

Seaton G., Hernandez J., Grunchec J.A., White I., Allen J., De Koning D.J., Wei W., Berry D., Haley C., Knott S. (2006) GridQTL: A Grid Portal for QTL Mapping of Compute Intensive Datasets. Proceedings of the 8th World Congress on Genetics Applied to Livestock Production, August 13-18, 2006. Belo Horizonte, Brazil.

GridQTL: A Grid Portal for QTL Mapping of Compute Intensive Datasets ISBN: 85-60088-01-6

CloudQTL

John Allen, David Scott, Malcolm Illingworth, Bartek Dobrzelecki, Davy Virdee, Steve Thorn, Sara Knott (2012) CloudQTL: Evolving a Bioinformatics Application to the Cloud. Digital Research 2012, September 10-12, 2012. Oxford, UK.

CloudQTL: Evolving a Bioinformatics Application to the Cloud

This paper was also presented at the EGI Community Forum, Manchester, 8th-12th April 2013.

EGI Community Forum Book of Abstracts 2013

See also: GridQTL Case Study

F2 and F2 from outbred lines

Haley CS & Knott SA. (1992) Heredity 69:315-324;doi:10.1038/hdy.1992.131

A simple regression method for mapping quantitative trait loci in line crosses using flanking markers.

Haley CS, Knott SA & Elsen JM. (1994) Genetics 136:1195-1207

Mapping quantitative trait loci in crosses between outbred lines using least squares.

LDLA

Hernández-Sánchez J., Grunchec J.-A. and Knott S. Bioinformatics 2009, 25(11):1377-1383; doi:10.1093/bioinformatics/btp171.

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

which uses a novel job scheduler for managing the distributed computation of the LDLA analyses:

SWARM: A meta-scheduler to Minimize Job Queuing Times on Computational Grids.

Haplotyping

Hernandez J. & Knott S. (2009) BMC Proceedings/2009, 3(Suppl 1):S7

Haplotyping via minimum recombinant paradigm.

Epistasis

Epistasis User Manual.

Disclaimer

Although every effort is made to ensure the correct functioning of the software at this site users use it at their own risk. GridQTL members and their respective institutions can not be held responsible for any problems resulting or consequential losses arising from the use of this software.

Funding

GridQTL has received the following funding:

United Kingdom Biotechnology and Biological Sciences Research Council (BEP2, BBS/B/1695X) 2006-2010.

European Community (Project SABRE, FOOD-CT-2006-01625); Research Councils United Kingdom (GR/T27983/01).

United Kingdom Bioinformatics and Biological Resources (BB/G022658/1 (GridQTL+ - High Performance Web-Based Genetic Analyses for the Biosciences - 2010-2013).

Publications and GridQTL Use

General

Project Flyer

Project Poster

International Science Grid This Week

Demo

GridQTL Use

GridQTL was released to the QTL community in the summer of 2006. To date we have had over 500 individual users performing over 100000 analyses in their QTL studies and using 2 cpu years of computation time each year on our Grid and local servers; we now consume over 2000 cpu hours on the Grid each month. GridQTL is used in every continent of the world (though not quite Antarctica for its penguins yet!) by around 50 users a month. A map detailing the location of our users and their output of work is shown below.


View GridQTL Use in a larger map