Imperial College London
Alternate

ProfessorMichaelSternberg

Faculty of Natural Sciences, Department of Life Sciences

Director, Systems Biology and Bioinformatics Centre
 
 
 
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Contact

 

+44 (0)20 7594 5212m.sternberg Website

 
 
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Location

 

306Sir Ernst Chain BuildingSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@article{Cornish:2018:bioinformatics/bty028,
author = {Cornish, AJ and David, A and Sternberg, MJE},
doi = {bioinformatics/bty028},
journal = {Bioinformatics},
pages = {2087--2095},
title = {PhenoRank: reducing study bias in gene prioritisation through simulation},
url = {http://dx.doi.org/10.1093/bioinformatics/bty028},
volume = {34},
year = {2018}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - Motivation: Genome-wide association studies have identified thousands of loci associated with human disease, but identifying the causal genes at these loci is often difficult. Several methods prioritise genes most likely to be disease causing through the integration of biological data, including protein-protein interaction and phenotypic data. Data availability is not the same for all genes however, potentially influencing the performance of these methods. Results: We demonstrate that whilst disease genes tend to be associated with greater numbers of data, this may be at least partially a result of them being better studied. With this observation we develop PhenoRank, which prioritises disease genes whilst avoiding being biased towards genes with more available data. Bias is avoided by comparing gene scores generated for the query disease against gene scores generated using simulated sets of phenotype terms, which ensures that differences in data availability do not affect the ranking of genes. We demonstrate that whilst existing prioritisation methods are biased by data availability, PhenoRank is not similarly biased. Avoiding this bias allows PhenoRank to effectively prioritise genes with fewer available data and improves its overall performance. PhenoRank outperforms three available prioritisation methods in cross-validation (PhenoRank area under receiver operating characteristic curve [AUC]=0.89, DADA AUC=0.87, EXOMISER AUC=0.71, PRINCE AUC=0.83, P < 2.2 × 10-16). Availability: PhenoRank is freely available for download at https://github.com/alexjcornish/PhenoRank. Contact: m.sternberg@imperial.ac.uk. Supplementary information: Supplementary data are available at Bioinformatics online.
AU  - Cornish,AJ
AU  - David,A
AU  - Sternberg,MJE
DO  - bioinformatics/bty028
EP  - 2095
PY  - 2018///
SN  - 1367-4803
SP  - 2087
TI  - PhenoRank: reducing study bias in gene prioritisation through simulation
T2  - Bioinformatics
UR  - http://dx.doi.org/10.1093/bioinformatics/bty028
UR  - http://hdl.handle.net/10044/1/56722
VL  - 34
ER  -
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