English
 
Help Privacy Policy Disclaimer
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT
 
 
DownloadE-Mail
  EPIBLASTER - fast exhaustive two-locus epistasis detection strategy using graphical processing units

Kam-Thong, T., Czamara, D., Tsuda, K., Borgwardt, K., Lewis, C. M., Erhardt-Lehmann, A., et al. (2011). EPIBLASTER - fast exhaustive two-locus epistasis detection strategy using graphical processing units. European Journal of Human Genetics, 19(4), 465-471. doi:10.1038/ejhg.2010.196.

Item is

Files

show Files

Locators

show

Creators

show
hide
 Creators:
Kam-Thong, T., Author
Czamara, D., Author
Tsuda, K.1, Author
Borgwardt, K.2, 3, Author           
Lewis, C. M., Author
Erhardt-Lehmann, A., Author
Hemmer, B., Author
Rieckmann, P., Author
Daake, M., Author
Weber, F., Author
Wolf, C., Author
Ziegler, A., Author
Pütz, B., Author
Holsboer, F., Author
Schölkopf, B.3, Author           
Müller-Myhsok, B., Author
Affiliations:
1Max Planck Society, ou_persistent13              
2Research Group Machine Learning and Computational Biology, Max Planck Institute for Intelligent Systems, Max Planck Society, ou_1497664              
3Dept. Empirical Inference, Max Planck Institute for Intelligent Systems, Max Planck Society, ou_1497647              

Content

show
hide
Free keywords: MPI für Intelligente Systeme; Abt. Schölkopf;
 Abstract: Detection of epistatic interaction between loci has been postulated to provide a more in-depth understanding of the complex biological and biochemical pathways underlying human diseases. Studying the interaction between two loci is the natural progression following traditional and well-established single locus analysis. However, the added costs and time duration required for the computation involved have thus far deterred researchers from pursuing a genome-wide analysis of epistasis. In this paper, we propose a method allowing such analysis to be conducted very rapidly. The method, dubbed EPIBLASTER, is applicable to case–control studies and consists of a two-step process in which the difference in Pearson‘s correlation coefficients is computed between controls and cases across all possible SNP pairs as an indication of significant interaction warranting further analysis. For the subset of interactions deemed potentially significant, a second-stage analysis is performed using the likelihood ratio test from the logistic regression to obtain the P-value for the estimated coefficients of the individual effects and the interaction term. The algorithm is implemented using the parallel computational capability of commercially available graphical processing units to greatly reduce the computation time involved. In the current setup and example data sets (211 cases, 222 controls, 299468 SNPs; and 601 cases, 825 controls, 291095 SNPs), this coefficient evaluation stage can be completed in roughly 1 day. Our method allows for exhaustive and rapid detection of significant SNP pair interactions without imposing significant marginal effects of the single loci involved in the pair.

Details

show
hide
Language(s):
 Dates: 2011-04-01
 Publication Status: Issued
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Degree: -

Event

show

Legal Case

show

Project information

show

Source 1

show
hide
Title: European Journal of Human Genetics
Source Genre: Journal
 Creator(s):
Affiliations:
Publ. Info: -
Pages: 6 Volume / Issue: 19 (4) Sequence Number: - Start / End Page: 465 - 471 Identifier: -