GWASLab: a Python package for processing and visualizing GWAS summary statistics

He, Yunye; Masaru Koido; Yuka Shimmori; Yoichiro Kamatani

doi:10.51094/jxiv.370

##article.authors##

He, Yunye Laboratory of Complex Trait Genomics, Graduate School of Frontier Sciences, The University of Tokyo https://orcid.org/0000-0001-8581-7826
Masaru Koido Laboratory of Complex Trait Genomics, Graduate School of Frontier Sciences, The University of Tokyo https://orcid.org/0000-0002-0348-0666 https://researchmap.jp/mkoido
Yuka Shimmori Laboratory of Complex Trait Genomics, Graduate School of Frontier Sciences, The University of Tokyo
Yoichiro Kamatani Laboratory of Complex Trait Genomics, Graduate School of Frontier Sciences, The University of Tokyo

DOI:

https://doi.org/10.51094/jxiv.370

キーワード:

GWAS、 Python、 summary statistics、 visualization、 QC

抄録

GWASLab is a comprehensive Python toolkit for processing and visualizing summary statistics (SumStats) derived from genome-wide association studies (GWAS). GWASLab provides functions including quality control (QC) of statistics, standardization of chromosome and allele notation, variant normalization, harmonization for meta-analysis, and data visualization. Modular implementation of functions allows users to customize their own pipelines for utilizing SumStats. An expandable formatting library and standalone utilities persistently ensure seamless compatibility with many post-GWAS tools.
Availability and implementation: GWASLab is implemented in Python; the source code is publicly and freely available at https://github.com/Cloufield/gwaslab, and the documentation is available at https://cloufield.github.io/gwaslab/.

利益相反に関する開示

The authors have declared no conflicts of interest.

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