PhenoGeneRanker: A Tool for Gene Prioritization Using Complete Multiplex Heterogeneous Networks
Association for Computing Machinery
Proceedings of the 10th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics
Uncovering genotype-phenotype relationships is a fundamental challenge in genomics. Gene prioritization is an important step for this endeavor to make a short manageable list from a list of thousands of genes coming from high-throughput studies. Network propagation methods are promising and state of the art methods for gene prioritization based on the premise that functionally-related genes tend to be close to each other in the biological networks.
In this study, we present PhenoGeneRanker, an improved version of a recently developed network propagation method called Random Walk with Restart on Multiplex Heterogeneous Networks (RWR-MH). PhenoGeneRanker allows multi-layer gene and disease networks. It also calculates empirical p-values of gene ranking using random stratified sampling of genes based on their connectivity degree in the network.
We ran PhenoGeneRanker using multi-omics datasets of rice to effectively prioritize the cold tolerance-related genes. We observed that top genes selected by PhenoGeneRanker were enriched in cold tolerance-related Gene Ontology (GO) terms whereas bottom ranked genes were enriched in general GO terms only. We also observed that top-ranked genes exhibited significant p-values suggesting that their rankings were independent of their degree in the network.
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This work is licensed under a Creative Commons Attribution 4.0 International License.
Dursun, Cagatay; Shimoyama, Naoki; Shimoyama, Mary; Schläppi, Michael; and Bozdag, Serdar, "PhenoGeneRanker: A Tool for Gene Prioritization Using Complete Multiplex Heterogeneous Networks" (2019). Computer Science Faculty Research and Publications. 22.
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Published in Proceedings of the 10th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics, 2019: 279-288. DOI. The copyright holder for this preprint is the author/funder. It is made available under a CC-BY 4.0 International license. Used with permission.