Sydney Brenner Institute for Molecular Bioscience, University of the Witwatersrand, Johannesburg, South Africa.
HPCBio, Roy J. Carver Biotechnology Center, University of Illinois at Urbana-Champaign, Urbana, IL, USA.
BMC Bioinformatics. 2022 Nov 19;23(1):498. doi: 10.1186/s12859-022-05034-w.
Genome-wide association studies (GWAS) are a powerful method to detect associations between variants and phenotypes. A GWAS requires several complex computations with large data sets, and many steps may need to be repeated with varying parameters. Manual running of these analyses can be tedious, error-prone and hard to reproduce.
The H3AGWAS workflow from the Pan-African Bioinformatics Network for H3Africa is a powerful, scalable and portable workflow implementing pre-association analysis, implementation of various association testing methods and post-association analysis of results.
The workflow is scalable-laptop to cluster to cloud (e.g., SLURM, AWS Batch, Azure). All required software is containerised and can run under Docker or Singularity.
全基因组关联研究（GWAS）是一种检测变异体和表型之间关联的强大方法。GWAS 需要对大型数据集进行多次复杂的计算，并且许多步骤可能需要根据不同的参数进行重复。手动运行这些分析可能会很繁琐、容易出错且难以重现。
来自 H3Africa 泛非生物信息学网络的 H3AGWAS 工作流程是一种强大、可扩展且可移植的工作流程，它实现了预关联分析、各种关联测试方法的实施以及结果的后关联分析。
该工作流程具有可扩展性——从笔记本电脑到集群再到云（例如，SLURM、AWS Batch、Azure）。所有必需的软件都已容器化，可以在 Docker 或 Singularity 下运行。
