编码区分析：分析 SNP 水平的微观多样性，以区分病毒基因组中的编码区和非编码区。
CodingDiv: analyzing SNP-level microdiversity to discriminate between coding and noncoding regions in viral genomes.
机构信息
Université Clermont Auvergne, CNRS, LMGE, F-63000 Clermont-Ferrand, France.
出版信息
Bioinformatics. 2023 Jul 1;39(7). doi: 10.1093/bioinformatics/btad408.
SUMMARY
Viral genes, that are frequently small genes and/or with large overlaps, are still difficult to predict accurately. To help predict all genes in viral genomes, we provide CodingDiv that detects SNP-level microdiversity of all potential coding regions, using metagenomic reads and/or similar sequences from external databases. Protein coding regions can then be identified as the ones containing more synonymous SNPs than unfavorable nonsynonymous substitutions SNPs.
AVAILABILITY AND IMPLEMENTATION
CodingDiv is released under the GPL license. Source code is available at https://github.com/ericolo/codingDiv. The software can be installed and used through a docker container.
摘要
病毒基因通常是小型基因且/或具有较大重叠，因此仍然难以准确预测。为了帮助预测病毒基因组中的所有基因，我们提供了 CodingDiv，该程序使用宏基因组读取和/或来自外部数据库的类似序列，检测所有潜在编码区域的 SNP 级微观多样性。然后，可以将包含更多同义 SNP 而不是不利非同义取代 SNP 的蛋白编码区域鉴定为编码区域。
可用性和实施
CodingDiv 是在 GPL 许可证下发布的。源代码可在 https://github.com/ericolo/codingDiv 上获得。可以通过 docker 容器安装和使用该软件。
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