AOC：Analysis of Orthologous Collections（直向同源集合分析）——一款用于表征蛋白质编码序列中自然选择的应用程序
AOC: Analysis of Orthologous Collections -- an application for the characterization of natural selection in protein-coding sequences
AI总结：
本文介绍 AOC 软件，基于 Snakemake 自动化完成同源编码序列从比对到选择压力量化与可视化的完整流程，以降低进化分析门槛。
摘要：
动机：现代分子序列分析日益依赖自动化且稳健的软件工具来进行解释、注释和获取生物学洞见。Analysis of Orthologous Collections（AOC，直向同源集合分析）应用程序可在编码序列分析中自动识别受自然选择影响的基因组位点以及物种/谱系。AOC能量化不同类型的选择：负选择、多样化或定向正选择，以及分支组之间的差异选择。我们纳入了从未比对的同源序列到完整结果和交互式可视化所需的全部步骤，这些结果和可视化旨在辅助进行有用的解释和情境化分析。结果：我们的动机是希望让进化分析尽可能简单，并缩小文献中受到大量关注的基因与那些在很大程度上被忽视和探索不足的基因之间的差距。我们相信，这些未被充分重视和研究的遗传数据集可以包含丰富的生物学信息，并为进化的多样模式和过程提供实质性洞见，尤其是在领域专家能够亲自执行分析的情况下。可用性与实现：一个 Snakemake（Mölder 等人，2021）应用程序实现已在 GitHub 上公开发布，地址为 https://github.com/aglucaci/AnalysisOfOrthologousCollections，并附有软件文档和教程。
英文摘要：
Motivation Modern molecular sequence analysis increasingly relies on automated and robust software tools for interpretation, annotation, and biological insight. The Analysis of Orthologous Collections (AOC) application automates the identification of genomic sites and species/lineages influenced by natural selection in coding sequence analysis. AOC quantifies different types of selection: negative, diversifying or directional positive, or differential selection between groups of branches. We include all steps necessary to go from unaligned homologous sequences to complete results and interactive visualizations that are designed to aid in the useful interpretation and contextualization. Results We are motivated by a desire to make evolutionary analyses as simple as possible, and to close the disparity in the literature between genes which draw a significant amount of interest and those that are largely overlooked and underexplored. We believe that such underappreciated and understudied genetic datasets can hold rich biological information and offer substantial insights into the diverse patterns and processes of evolution, especially if domain experts are able to perform the analyses themselves. Availability and implementation A Snakemake [Mölder et al., 2021] application implementation is publicly available on GitHub at https://github.com/aglucaci/AnalysisOfOrthologousCollections and is accompanied by software documentation and a tutorial.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
