Imperial College London
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DrDeanBodenham

Faculty of Natural Sciences, Department of Mathematics

Lecturer in Statistics
 
 
 
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Contact

 

dean.bodenham

 
 
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Location

 

531Huxley BuildingSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@article{Llinares-López:2017:bioinformatics/btx071,
author = {Llinares-López, F and Papaxanthos, L and Bodenham, D and Roqueiro, D and Borgwardt, K},
doi = {bioinformatics/btx071},
journal = {Bioinformatics},
pages = {1820--1828},
title = {Genome-wide genetic heterogeneity discovery with categorical covariates},
url = {http://dx.doi.org/10.1093/bioinformatics/btx071},
volume = {33},
year = {2017}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - MotivationGenetic heterogeneity is the phenomenon that distinct genetic variants may give rise to the same phenotype. The recently introduced algorithm Fast Automatic Interval Search (FAIS) enables the genome-wide search of candidate regions for genetic heterogeneity in the form of any contiguous sequence of variants, and achieves high computational efficiency and statistical power. Although FAIS can test all possible genomic regions for association with a phenotype, a key limitation is its inability to correct for confounders such as gender or population structure, which may lead to numerous false-positive associations.ResultsWe propose FastCMH, a method that overcomes this problem by properly accounting for categorical confounders, while still retaining statistical power and computational efficiency. Experiments comparing FastCMH with FAIS and multiple kinds of burden tests on simulated data, as well as on human and Arabidopsis samples, demonstrate that FastCMH can drastically reduce genomic inflation and discover associations that are missed by standard burden tests.Availability and ImplementationAn R package fastcmh is available on CRAN and the source code can be found at: https://www.bsse.ethz.ch/mlcb/research/bioinformatics-and-computational-biology/fastcmh.html
AU  - Llinares-López,F
AU  - Papaxanthos,L
AU  - Bodenham,D
AU  - Roqueiro,D
AU  - Borgwardt,K
DO  - bioinformatics/btx071
EP  - 1828
PY  - 2017///
SN  - 1367-4803
SP  - 1820
TI  - Genome-wide genetic heterogeneity discovery with categorical covariates
T2  - Bioinformatics
UR  - http://dx.doi.org/10.1093/bioinformatics/btx071
UR  - https://academic.oup.com/bioinformatics/article/33/12/1820/2995817/
UR  - http://hdl.handle.net/10044/1/73743
VL  - 33
ER  -
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