PSAURON:一种用于评估多种物种蛋白质注释的工具。

IF 4 Q1 GENETICS & HEREDITY
NAR Genomics and Bioinformatics Pub Date : 2025-01-07 eCollection Date: 2025-03-01 DOI:10.1093/nargab/lqae189
Markus J Sommer, Aleksey V Zimin, Steven L Salzberg
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引用次数: 0

摘要

评估基因组注释中蛋白质编码序列的准确性是一个具有挑战性的问题,目前还没有广泛适用的解决方案。在这篇文章中,我们介绍了PSAURON(蛋白质序列评估使用参考ORF网络),这是一种新的软件工具,用于帮助评估蛋白质编码基因注释的质量。PSAURON利用在来自1000多个植物和动物基因组的不同数据集上训练的机器学习模型,为编码DNA或蛋白质序列分配分数,反映该序列是真正的蛋白质编码区域的可能性。PSAURON评分可用于全基因组蛋白质注释评估以及潜在的虚假注释蛋白质的快速鉴定。对既定基准的验证表明PSAURON的有效性和与公认的蛋白质质量测量的相关性,突出了其作为评估基因注释精度的广泛适用方法的潜在用途。PSAURON是开源的,可以在https://github.com/salzberg-lab/PSAURON免费获得。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
PSAURON: a tool for assessing protein annotation across a broad range of species.

Evaluating the accuracy of protein-coding sequences in genome annotations is a challenging problem for which there is no broadly applicable solution. In this manuscript, we introduce PSAURON (Protein Sequence Assessment Using a Reference ORF Network), a novel software tool developed to help assess the quality of protein-coding gene annotations. Utilizing a machine learning model trained on a diverse dataset from over 1000 plant and animal genomes, PSAURON assigns a score to coding DNA or protein sequence that reflects the likelihood that the sequence is a genuine protein-coding region. PSAURON scores can be used for genome-wide protein annotation assessment as well as the rapid identification of potentially spurious annotated proteins. Validation against established benchmarks demonstrates PSAURON's effectiveness and correlation with recognized measures of protein quality, highlighting its potential use as a widely applicable method to evaluate precision in gene annotation. PSAURON is open source and freely available at https://github.com/salzberg-lab/PSAURON.

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来源期刊
CiteScore
8.00
自引率
2.20%
发文量
95
审稿时长
15 weeks
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