Abstract：
DNA shuffling is a powerful technique for generating synthetic DNA via recombination of homologous parental sequences. Resulting chimeras are often incorporated into complex libraries for functionality screenings that identify novel variants with improved characteristics. To survey shuffling efficiency, subsequences of chimeras can be computationally assigned to their corresponding parental counterpart, yielding insight into frequency of recombination events, diversity of shuffling libraries and actual composition of final variants. Whereas tools for parental assignment exist, they do not provide direct visualization of the results, making the analysis time-consuming and cumbersome. Here we present ShuffleAnalyzer, a comprehensive, user-friendly, Python-based analysis tool that directly generates graphical outputs of parental assignments and is freely available under a BSD-3 license (https://github.com/joerg-swg/ShuffleAnalyzer/releases). Besides DNA shuffling, peptide insertions can be simultaneously analyzed and visualized, which makes ShuffleAnalyzer a highly valuable tool for integrated approaches often used in synthetic biology, such as AAV capsid engineering in gene therapy applications.
摘要：
DNA改组是通过同源亲本序列的重组产生合成DNA的强大技术。通常将所得的嵌合体掺入复杂文库中用于功能性筛选,以鉴定具有改进特征的新变体。为了调查洗牌效率，嵌合体的子序列可以计算地分配给它们对应的父母对应物，深入了解重组事件的频率，改组文库的多样性和最终变体的实际组成。尽管存在父母分配的工具，它们不提供结果的直接可视化，使分析耗时且繁琐。这里我们介绍ShuffleAnalyzer，一个全面的，用户友好，基于Python的分析工具，可直接生成父母分配的图形输出，并在BSD-3许可证下免费提供（https://github.com/joerg-swg/ShuffleAnalyzer/releases）。除了DNA改组,肽插入可以同时分析和可视化，这使得ShuffleAnalyzer成为合成生物学中经常使用的集成方法的非常有价值的工具，例如在基因治疗应用中的AAV衣壳工程。
