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A large-scale benchmark of gene prioritization methods
Stockholm University, Faculty of Science, Department of Biochemistry and Biophysics. Stockholm University, Science for Life Laboratory (SciLifeLab).
Stockholm University, Faculty of Science, Department of Biochemistry and Biophysics. Stockholm University, Science for Life Laboratory (SciLifeLab).
Number of Authors: 2
2017 (English)In: Scientific Reports, ISSN 2045-2322, E-ISSN 2045-2322, Vol. 7, 46598Article in journal (Refereed) Published
Abstract [en]

In order to maximize the use of results from high-throughput experimental studies, e.g. GWAS, for identification and diagnostics of new disease-associated genes, it is important to have properly analyzed and benchmarked gene prioritization tools. While prospective benchmarks are underpowered to provide statistically significant results in their attempt to differentiate the performance of gene prioritization tools, a strategy for retrospective benchmarking has been missing, and new tools usually only provide internal validations. The Gene Ontology (GO) contains genes clustered around annotation terms. This intrinsic property of GO can be utilized in construction of robust benchmarks, objective to the problem domain. We demonstrate how this can be achieved for network-based gene prioritization tools, utilizing the FunCoup network. We use cross-validation and a set of appropriate performance measures to compare state-of-the-art gene prioritization algorithms: three based on network diffusion, NetRank and two implementations of Random Walk with Restart, and MaxLink that utilizes network neighborhood. Our benchmark suite provides a systematic and objective way to compare the multitude of available and future gene prioritization tools, enabling researchers to select the best gene prioritization tool for the task at hand, and helping to guide the development of more accurate methods.

Place, publisher, year, edition, pages
2017. Vol. 7, 46598
National Category
Bioinformatics and Systems Biology
Identifiers
URN: urn:nbn:se:su:diva-143570DOI: 10.1038/srep46598ISI: 000399996300001PubMedID: 28429739OAI: oai:DiVA.org:su-143570DiVA: diva2:1104487
Available from: 2017-06-01 Created: 2017-06-01 Last updated: 2017-06-01Bibliographically approved

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Guala, DimitriSonnhammer, Erik L. L.
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