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Detecting non-orthology in the COGs database and other approaches grouping orthologs using genome-specific best hits

机译:检测COGs数据库中的非矫形术以及其他使用基因组特异性最佳命中直系同源物的方法

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摘要

Correct orthology assignment is a critical prerequisite of numerous comparative genomics procedures, such as function prediction, construction of phylogenetic species trees and genome rearrangement analysis. We present an algorithm for the detection of non-orthologs that arise by mistake in current orthology classification methods based on genome-specific best hits, such as the COGs database. The algorithm works with pairwise distance estimates, rather than computationally expensive and error-prone tree-building methods. The accuracy of the algorithm is evaluated through verification of the distribution of predicted cases, case-by-case phylogenetic analysis and comparisons with predictions from other projects using independent methods. Our results show that a very significant fraction of the COG groups include non-orthologs: using conservative parameters, the algorithm detects non-orthology in a third of all COG groups. Consequently, sequence analysis sensitive to correct orthology assignments will greatly benefit from these findings.
机译:正确的拼字分配是众多比较基因组学程序的关键先决条件,例如功能预测,系统发育树种构建和基因组重排分析。我们提出了一种算法,用于检测基于基因组特定的最佳匹配(例如COGs数据库)的当前正交分类方法中由于错误而产生的非直系同源物。该算法适用于成对距离估计,而不是计算量大且易于出错的树构建方法。通过验证预测病例的分布,逐例系统发育分析以及使用独立方法与其他项目的预测进行比较,来评估算法的准确性。我们的结果表明,COG组中非常重要的部分包括非直系同源物:使用保守参数,该算法在所有COG组的三分之一中检测到非正交性。因此,对正确的拼字法分配敏感的序列分析将大大受益于这些发现。

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