pandasPGS:一个Python包,可以轻松检索多基因分数目录数据.
Zheyu Zhang1, Jintong Zhou1, Tianze Cao1
1School of Mathematics, Hangzhou Normal University, Hangzhou, Zhejiang, China.
PeerJ
|February 17, 2025
概括
一个新的Python包,pandasPGS,简化了访问和分析多基因分数 (PGS) 目录数据. 该工具通过消除学习复杂的REST API的需求来简化研究,使多基因风险评分集成变得更容易.
科学领域:
- 遗传学 是一个遗传学.
- 生物信息学是一种生物信息学.
- 计算生物学 计算生物学
背景情况:
- 多基因评分 (PGS) 目录是一个公共数据库,包含656个特征的5000多基因风险评分.
- 访问 PGS Catalog 数据需要研究人员与其 REST API 进行交互,这需要大量的学习时间和自定义客户端实现.
- 缺乏特定语言的数据客户端,阻碍了PGS数据与研究工作流程的无整合.
研究的目的:
- 介绍pandasPGS,这是一个Python软件包,旨在对PGS目录进行程序化访问.
- 为研究人员简化检索和分析多基因风险评分数据的过程.
- 为了减少研究人员使用PGS目录资源的技术障碍.
主要方法:
- 开发了pandasPGS,这是一个Python包,为PGS目录数据检索提供了一个直观的界面.
- 实现了自动处理URL选择,数据请求和页面合并的功能.
- 集成数据预处理功能,将检索的数据转换为层次的熊猫.数据框架对象.
主要成果:
- pandasPGS为研究人员提供了PGS目录的直接程序访问.
- 该软件包自动检索和合并数据,大大减少获得多基因风险评分数据所需的努力.
- 将数据转换成用户友好的数据框架,方便下游分析.
结论:
- pandasPGS有效地减轻了研究人员学习和使用PGS Catalog REST API所需的时间投资.
- 该方案提高了用于遗传研究的多基因风险评分数据的可访问性和可用性.
- 源代码和文档是公开可用的,以支持采用和进一步开发.
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