Proteinortho6: pseudo-reciprocal best alignment heuristic for graph-based detection of (co-)orthologs

IF 2.8 Q2 MATHEMATICAL & COMPUTATIONAL BIOLOGY Frontiers in bioinformatics Pub Date : 2023-12-13 DOI:10.3389/fbinf.2023.1322477
Paul Klemm, Peter F. Stadler, Marcus Lechner
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Abstract

Proteinortho is a widely used tool to predict (co)-orthologous groups of genes for any set of species. It finds application in comparative and functional genomics, phylogenomics, and evolutionary reconstructions. With a rapidly increasing number of available genomes, the demand for large-scale predictions is also growing. In this contribution, we evaluate and implement major algorithmic improvements that significantly enhance the speed of the analysis without reducing precision. Graph-based detection of (co-)orthologs is typically based on a reciprocal best alignment heuristic that requires an all vs. all comparison of proteins from all species under study. The initial identification of similar proteins is accelerated by introducing an alternative search tool along with a revised search strategy—the pseudo-reciprocal best alignment heuristic—that reduces the number of required sequence comparisons by one-half. The clustering algorithm was reworked to efficiently decompose very large clusters and accelerate processing. Proteinortho6 reduces the overall processing time by an order of magnitude compared to its predecessor while maintaining its small memory footprint and good predictive quality.
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Proteinortho6:基于图谱检测(同)同源物的伪互易最佳配准启发式
Proteinortho 是一种广泛使用的工具,用于预测任何物种的(同)同源基因组。它适用于比较和功能基因组学、系统发生组学和进化重建。随着可用基因组数量的迅速增加,对大规模预测的需求也在不断增长。在这篇论文中,我们评估并实施了重大的算法改进,在不降低精度的情况下显著提高了分析速度。基于图谱的(共)同源物检测通常基于互易最佳配对启发式,需要对所有研究物种的蛋白质进行全对全比较。通过引入另一种搜索工具和修订后的搜索策略--伪互易最佳配对启发式--可将所需的序列比较次数减少一半,从而加快了相似蛋白质的初步识别。聚类算法经过重新设计,可有效分解超大聚类并加快处理速度。与前者相比,Proteinortho6 的整体处理时间缩短了一个数量级,同时保持了较小的内存占用和良好的预测质量。
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