Huayu, Z;
Amy, F;
Grant, R;
Muchen, J;
Teng, Z;
Cathie, S;
Keith, S;
... Wu, H; + view all
(2021)
Benchmarking network-based gene prioritization methods for cerebral small vessel disease.
Briefings in Bioinformatics
10.1093/bib/bbab006.
(In press).
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Abstract
Network-based gene prioritization algorithms are designed to prioritize disease-associated genes based on known ones using biological networks of protein interactions, gene disease associations and other relationships between biological entities. Various algorithms have been developed based on different mechanisms, but it is not obvious which algorithm is optimal for a specific disease. To address this issue, we benchmarked multiple algorithms for their application in cerebral small vessel disease (cSVD). We curated protein-gene interactions (PGI) and gene-disease associations (GDA) from databases and assembled PGI networks and disease-gene heterogenous networks. A screening of algorithms resulted in seven representative algorithms to be benchmarked. Performance of algorithms was assessed using both leave-one-out cross-validation (LOOCV) and external validation with MEGASTROKE genome-wide association study (GWAS). We found that random walk with restart on the heterogeneous network (RWRH) showed best LOOCV performance, with median LOOCV rediscovery rank of 185.5 (out of 19,463 genes). The GenePanda algorithm had most GWAS-confirmable genes in top 200 predictions, while RWRH had best ranks for small vessel stroke associated genes confirmed in GWAS. In conclusion, RWRH has overall better performance for application in cSVD despite its susceptibility to bias caused by degree centrality. Choice of algorithms should be determined before applying to specific disease. Current pure network-based gene prioritization algorithms are unlikely to find novel disease-associated genes that are not associated with known ones. The tools for implementing and benchmarking algorithms have been made available and can be generalized for other diseases.
| Type: | Article |
|---|---|
| Title: | Benchmarking network-based gene prioritization methods for cerebral small vessel disease |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1093/bib/bbab006 |
| Publisher version: | https://doi.org/10.1093/bib/bbab006 |
| Language: | English |
| Additional information: | © The Author(s) 2021. Published by Oxford University Press. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute of Health Informatics |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10118392 |
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