Advancements in next-generation sequencing (NGS) technologies have led to a substantial increase in the availability of population genetic variant data, thus prompting the development of various population analysis tools to enhance our understanding of population structure and evolution. The tools that are currently used to analyze population genetic variant data generally require different environments, parameters, and formats of the input data, which can act as a barrier preventing the wide-spread usage of such tools by general researchers who may not be familiar with bioinformatics. To address this problem, we have developed an automated and comprehensive pipeline called PAPipe to perform nine widely used population genetic analyses using population NGS data. PAPipe seamlessly interconnects and serializes multiple steps, such as read trimming and mapping, genetic variant calling, data filtering and format converting, along with nine population genetic analyses such as principal component analysis, phylogenetic analysis, population tree analysis, population structure analysis, linkage disequilibrium decay analysis, selective sweep analysis, population admixture analysis, sequentially Markovian coalescent analysis, and fixation index analysis. PAPipe also provides an easy-to-use web interface that allows for the parameters to be set and the analysis results to be browsed in intuitive manner. PAPipe can be used to generate extensive results that provide insights that can help enhance user convenience and data usability. PAPipe is freely available at https://github.com/jkimlab/PAPipe.

中文翻译：

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PAPipe：综合群体遗传分析的管道

下一代测序（NGS）技术的进步导致群体遗传变异数据的可用性大幅增加，从而促进了各种群体分析工具的开发，以增强我们对群体结构和进化的理解。目前用于分析群体遗传变异数据的工具通常需要不同的环境、参数和输入数据格式，这可能成为不熟悉的一般研究人员广泛使用此类工具的障碍。生物信息学。为了解决这个问题，我们开发了一个名为 PAPipe 的自动化综合管道，利用群体 NGS 数据执行九种广泛使用的群体遗传分析。PAPipe无缝互连和序列化多个步骤，例如读段修剪和映射、遗传变异调用、数据过滤和格式转换，以及主成分分析、系统发育分析、群体树分析、群体结构分析、连锁不平衡等九种群体遗传分析衰减分析、选择性扫描分析、群体混合分析、顺序马尔可夫聚结分析和固定指数分析。PAPipe 还提供易于使用的 Web 界面，允许以直观的方式设置参数和浏览分析结果。PAPipe 可用于生成广泛的结果，提供有助于增强用户便利性和数据可用性的见解。PAPipe 可在 https://github.com/jkimlab/PAPipe 上免费获取。