Given the rapid increase of species with a sequenced genome, the need to identify orthologous genes between them has emerged as a central bioinformatics task. Many different methods exist for orthology detection, which makes it difficult to decide which one to choose for a particular application. Here, we review the latest developments and issues in the orthology field, and summarize the most recent results reported at the third 'Quest for Orthologs' meeting. We focus on community efforts such as the adoption of reference proteomes, standard file formats and benchmarking. Progress in these areas is good, and they are already beneficial to both orthology consumers and providers. However, a major current issue is that the massive increase in complete proteomes poses computational challenges to many of the ortholog database providers, as most orthology inference algorithms scale at least quadratically with the number of proteomes. The Quest for Orthologs consortium is an open community with a number of working groups that join efforts to enhance various aspects of orthology analysis, such as defining standard formats and datasets, documenting community resources and benchmarking.
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机译：考虑到具有测序基因组的物种的迅速增加，识别它们之间直系同源基因的需求已成为一项重要的生物信息学任务。存在许多不同的方法来进行正畸检测，这使得难以确定为特定应用选择哪种方法。在这里，我们回顾了矫正学领域的最新发展和问题，并总结了第三届“直系同源物探索”会议上报告的最新结果。我们专注于社区工作，例如采用参考蛋白质组，标准文件格式和基准测试。这些领域的进展是好的，它们已经对矫正术的消费者和提供者都有利。然而，当前的一个主要问题是，完整蛋白质组的大量增加给许多直系同源数据库提供者带来了计算挑战，因为大多数正字学推断算法至少随着蛋白质组数量的增加而平方成比例。 Quest for Orthologs财团是一个开放的社区，拥有许多工作组，这些工作组共同努力以增强拼字分析的各个方面，例如定义标准格式和数据集，记录社区资源和进行基准测试。
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