Imperial College London
Alternate

DrMarinaEvangelou

Faculty of Natural Sciences, Department of Mathematics

Senior Lecturer in Statistics
 
 
 
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Contact

 

+44 (0)20 7594 7184m.evangelou

 
 
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Location

 

546Huxley BuildingSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@article{Evangelou:2014:bioinformatics/btt583,
author = {Evangelou, M and Dudbridge, F and Wernisch, L},
doi = {bioinformatics/btt583},
journal = {Bioinformatics},
pages = {690--697},
title = {Two novel pathway analysis methods based on a hierarchical model},
url = {http://dx.doi.org/10.1093/bioinformatics/btt583},
volume = {30},
year = {2014}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - Motivation: Over the past few years several pathway analysis methods have been proposed for exploring and enhancing the analysis of genome-wide association data. Hierarchical models have been advocated as a way to integrate SNP and pathway effects in the same model, but their computational complexity has prevented them being applied on a genome-wide scale to date.Methods: We present two novel methods for identifying associated pathways. In the proposed hierarchical model, the SNP effects are analytically integrated out of the analysis, allowing computationally tractable model fitting to genome-wide data. The first method uses Bayes factors for calculating the effect of the pathways, whereas the second method uses a machine learning algorithm and adaptive lasso for finding a sparse solution of associated pathways.Results: The performance of the proposed methods was explored on both simulated and real data. The results of the simulation study showed that the methods outperformed some well-established association methods: the commonly used Fisher’s method for combining P-values and also the recently published BGSA. The methods were applied to two genome-wide association study datasets that aimed to find the genetic structure of platelet function and body mass index, respectively. The results of the analyses replicated the results of previously published pathway analysis of these phenotypes but also identified novel pathways that are potentially involved.Availability: An R package is under preparation. In the meantime, the scripts of the methods are available on request from the authors.
AU  - Evangelou,M
AU  - Dudbridge,F
AU  - Wernisch,L
DO  - bioinformatics/btt583
EP  - 697
PY  - 2014///
SN  - 1367-4803
SP  - 690
TI  - Two novel pathway analysis methods based on a hierarchical model
T2  - Bioinformatics
UR  - http://dx.doi.org/10.1093/bioinformatics/btt583
UR  - http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000332259300014&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202
UR  - https://academic.oup.com/bioinformatics/article/30/5/690/245758
VL  - 30
ER  -
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