一个快速,可复制,高通量变体,为人口基因组学调用工作流
Cade D Mirchandani1,2, Allison J Shultz3, Gregg W C Thomas4
1Department of Biomolecular Engineering, University of California Santa Cruz, Santa Cruz, CA 95064, USA.
Molecular biology and evolution
|December 9, 2023
概括
一个新的工作流,snpArcher,标准化了非模型生物的基因组再测序分析. 该工具通过有效的数据重复使用和对物种间遗传变异的分析来促进比较人口基因组学.
科学领域:
- 基因组学就是基因组学.
- 生物信息学是一种生物信息学.
- 进化生物学 进化生物学
背景情况:
- 基因组再测序数据正在迅速增加,为比较人口基因组学提供了机会.
- 数据重复使用的挑战包括可变变量调用管道,数据质量问题和密集的再分析需求.
- 非模型生物通常缺乏对基因组数据的标准化分析管道.
研究的目的:
- 引入snpArcher,这是一个灵活和高效的工作流程,用于分析非模型生物中的基因组再测序数据.
- 为基因组数据的变异调用和下游分析标准化.
- 通过使数据重复使用,促进对人口基因组进行比较研究.
主要方法:
- 开发了snpArcher,这是一个基于Snakemake的工作流程,包含用于变量调用,质量控制,可视化和过的模块.
- 实现了一个标准化的变体,称为管道.
- 确保与高性能计算集群和云环境的兼容性.
主要成果:
- 应用了snpArcher对26个非哺乳动物脊椎动物的公共复序数据集.
- 在分析各种基因组数据方面展示了工作流的灵活性和效率.
- 为未来的比较分析,公开提供变体数据集.
结论:
- snpArcher提供了一个用户友好的,可复制和高效的解决方案,用于分析非模型生物中的基因组再测序数据.
- 工作流促进了大型基因组数据集的快速使用和重复使用.
- snpArcher将通过增强的比较人群基因组学,促进对物种间遗传变异的理解.
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