Adrian Altenhoff, Yannis Nevers, Vinh Tran, Dushyanth Jyothi, Maria Martin, Salvatore Cosentino, Sina Majidian, Marina Marcet-Houben, Diego Fuentes-Palacios, Emma Persson, Thomas Walsh, Odile Lecompte, Toni Gabaldón, Steven Kelly, Yanhui Hu, Wataru Iwasaki, Salvador Capella-Gutierrez, Christophe Dessimoz, Paul D Thomas, Ingo Ebersberger, Erik Sonnhammer
{"title":"New developments for the Quest for Orthologs benchmark service.","authors":"Adrian Altenhoff, Yannis Nevers, Vinh Tran, Dushyanth Jyothi, Maria Martin, Salvatore Cosentino, Sina Majidian, Marina Marcet-Houben, Diego Fuentes-Palacios, Emma Persson, Thomas Walsh, Odile Lecompte, Toni Gabaldón, Steven Kelly, Yanhui Hu, Wataru Iwasaki, Salvador Capella-Gutierrez, Christophe Dessimoz, Paul D Thomas, Ingo Ebersberger, Erik Sonnhammer","doi":"10.1093/nargab/lqae167","DOIUrl":null,"url":null,"abstract":"<p><p>The Quest for Orthologs (QfO) orthology benchmark service (https://orthology.benchmarkservice.org) hosts a wide range of standardized benchmarks for orthology inference evaluation. It is supported and maintained by the QfO consortium, and is used to gather ortholog predictions and to examine strengths and weaknesses of newly developed and existing orthology inference methods. The web server allows different inference methods to be compared in a standardized way using the same proteome data. The benchmark results are useful for developing new methods and can help researchers to guide their choice of orthology method for applications in comparative genomics and phylogenetic analysis. We here present a new release of the Orthology Benchmark Service with a new benchmark based on feature architecture similarity as well as updated reference proteomes. We further provide a meta-analysis of the public predictions from 18 different orthology assignment methods to reveal how they relate in terms of ortholog predictions and benchmark performance. These results can guide users of orthologs to the best suited method for their purpose.</p>","PeriodicalId":33994,"journal":{"name":"NAR Genomics and Bioinformatics","volume":"6 4","pages":"lqae167"},"PeriodicalIF":4.0000,"publicationDate":"2024-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11632614/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"NAR Genomics and Bioinformatics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1093/nargab/lqae167","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/12/1 0:00:00","PubModel":"eCollection","JCR":"Q1","JCRName":"GENETICS & HEREDITY","Score":null,"Total":0}
引用次数: 0
Abstract
The Quest for Orthologs (QfO) orthology benchmark service (https://orthology.benchmarkservice.org) hosts a wide range of standardized benchmarks for orthology inference evaluation. It is supported and maintained by the QfO consortium, and is used to gather ortholog predictions and to examine strengths and weaknesses of newly developed and existing orthology inference methods. The web server allows different inference methods to be compared in a standardized way using the same proteome data. The benchmark results are useful for developing new methods and can help researchers to guide their choice of orthology method for applications in comparative genomics and phylogenetic analysis. We here present a new release of the Orthology Benchmark Service with a new benchmark based on feature architecture similarity as well as updated reference proteomes. We further provide a meta-analysis of the public predictions from 18 different orthology assignment methods to reveal how they relate in terms of ortholog predictions and benchmark performance. These results can guide users of orthologs to the best suited method for their purpose.
Quest for Orthologs (QfO) orthology基准服务(https://orthology.benchmarkservice.org)为Orthologs推理评估提供了广泛的标准化基准测试。它由QfO联盟支持和维护,用于收集同源预测,并检查新开发的和现有的同源推断方法的优缺点。web服务器允许使用相同的蛋白质组数据以标准化的方式比较不同的推断方法。这些基准结果对新方法的开发有一定的指导作用,可以帮助研究人员在比较基因组学和系统发育分析中指导他们选择orthology方法。我们在此发布了一个新版本的Orthology基准服务,其中包含基于特征架构相似性的新基准以及更新的参考蛋白质组。我们进一步对来自18种不同的正交分配方法的公开预测进行了元分析,以揭示它们在正交预测和基准性能方面的关系。这些结果可以指导同源词的用户选择最适合他们目的的方法。