Skip Navigation


Bioinformatics Advance Access originally published online on August 21, 2009
Bioinformatics 2009 25(20):2750-2752; doi:10.1093/bioinformatics/btp497
This Article
Right arrow Full Text Freely available
Right arrow FREE Full Text (Print PDF) Freely available
Right arrow Supplementary Data
Right arrowOA All Versions of this Article:
25/20/2750    most recent
btp497v2
btp497v1
Right arrow Comments: Submit a response
Right arrow Alert me when this article is cited
Right arrow Alert me when Comments are posted
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Add to My Personal Archive
Right arrow Download to citation manager
Google Scholar
Right arrow Articles by Estrada, K.
Right arrow Articles by Rivadeneira, F.
PubMed
Right arrow PubMed Citation
Right arrow Articles by Estrada, K.
Right arrow Articles by Rivadeneira, F.
Social Bookmarking
Add to CiteULike   Add to Connotea   Add to Del.icio.us  
What's this?

© The Author(s) 2009. Published by Oxford University Press.
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.5/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

GRIMP: a web- and grid-based tool for high-speed analysis of large-scale genome-wide association using imputed data

Karol Estrada 1,2,{dagger}, Anis Abuseiris 3,4,5,{dagger}, Frank G. Grosveld 4, André G. Uitterlinden 1,2, Tobias A. Knoch 3,4,5,* and Fernando Rivadeneira 1,2,*

1 Department of Internal Medicine, 2 Department of Epidemiology, 3 Biophysical Genomics & Erasmus Computing Grid, 4 Department of Cell Biology, Erasmus MC, Dr. Molewaterplein 50, 3015GE Rotterdam, The Netherlands and 5 Biophysical Genomics, Genome Organization & Function, BioQuant/German Cancer Research Center, Im Neuenheimer Feld 267, 69120 Heidelberg, Germany

* To whom correspondence should be addressed.


  Abstract

Summary: The current fast growth of genome-wide association studies (GWAS) combined with now common computationally expensive imputation requires the online access of large user groups to high-performance computing resources capable of analyzing rapidly and efficiently millions of genetic markers for ten thousands of individuals. Here, we present a web-based interface—called GRIMP—to run publicly available genetic software for extremely large GWAS on scalable super-computing grid infrastructures. This is of major importance for the enlargement of GWAS with the availability of whole-genome sequence data from the 1000 Genomes Project and for future whole-population efforts.

Contact: ta.knoch{at}taknoch.org; f.rivadeneira{at}erasmusmc.nl

{dagger} The authors wish it to be known that, in their opinion, the first two authors should be regarded as joint First Authors.

Associate Editor: Jeffrey Barrett

Received on June 23, 2009; revised on August 13, 2009; accepted on August 13, 2009

Add to CiteULike CiteULike   Add to Connotea Connotea   Add to Del.icio.us Del.icio.us    What's this?




Disclaimer: Please note that abstracts for content published before 1996 were created through digital scanning and may therefore not exactly replicate the text of the original print issues. All efforts have been made to ensure accuracy, but the Publisher will not be held responsible for any remaining inaccuracies. If you require any further clarification, please contact our Customer Services Department.