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Mol. Biol. Evol., Mar 01 2024, msae040 | https://doi.org/10.1093/molbev/msae040 PAPipe: a pipeline for comprehensive population genetic analysis

Nayoung Park ¹, Hyeonji Kim ¹, Jeongmin Oh ¹, Jinseok Kim ¹, Charyeong Heo ¹, Jaebum Kim ¹

¹Department of Biomedical Science and Engineering, Konkuk University, Seoul 05029, Republic of Korea.

Correspondence : Jaebum Kim

Abstract

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.

논문정보

형식Research article
게재일2024년 03월 (BRIC 등록일 2024-03-04)
연구진국내 연구진
분야 생명과학 > 유전학

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