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hybpiper-nf和paragon-nf:容器化和目标捕获组件和对比分辨率的额外选项

Chris Jackson¹, Todd McLay^1,2,3, Alexander N Schmidt-Lebuhn²

¹Royal Botanic Gardens Victoria, Birdwood Avenue, Melbourne Victoria 3004 Australia.

Applications in plant sciences

|August 21, 2023

概括

我们将HybPiper集装箱化并开发了paragone-nf,简化了目标捕获数据的分析. 这些管道简化了对应物识别和对应物分组,增强了进化关系推断.

科学领域:

生物信息学是一种生物信息学.
计算生物学计算生物学
进化生物学进化生物学

背景情况:

HybPiper 是一个广泛使用的工具,用于组装目标捕获数据在家族遗传学分析.
准确的对比识别对于从序列数据中推断进化关系至关重要.
使用基因树拓的算法方法对于正义推理是有效的,特别是对于非模型生物.

研究的目的:

容器化和扩展HybPiper的功能和一个ortolog推断管道.
为处理目标捕获序列数据提供新的选项.
为了实现 HybPiper 输出和 ortolog 推断之间的无集成.

主要方法:

使用Singularity对HybPiper和一个正统推断管道的容器化.
实现两个Nextflow脚本 (hybpiper-nf和paragone-nf) 进行简化部署.
开发处理目标捕获序列数据和对比识别的新选择.

主要成果:

集装箱管道 (hybpiper-nf和paragone-nf) 包括所有依赖的管道.
简化了部署,并减少了用户的命令行复杂性.
无集成HybPiper输出作为输入的paragone-nf.

结论:

该hybpiper-nf和paragone-nf管道提供了用户友好的安装和强大的结果为phylogenetics.
这些管道为进化研究提供了准确的对应物识别和对应物分组.
这些管道被澳大利亚安吉奥精子生命树项目积极使用,并可供公众使用.

关键词:

这就是HybPiper.下一个流程下一个流程奇点容器是一个奇点容器.骨科专家的说法一个模拟模拟器.人类基因组学学科.目标捕获目标捕获目标是丰富的目标.

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