GWASLab: a Python package for processing and visualizing GWAS summary statistics
##article.authors##
- Yunye He 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.370Keywords:
GWAS, Python, summary statistics, visualization, QCAbstract
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/.
Conflicts of Interest Disclosure
The authors have declared no conflicts of interest.Downloads *Displays the aggregated results up to the previous day.
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Submitted: 2023-04-28 08:36:45 UTC
Published: 2023-05-01 09:59:49 UTC
License
Copyright (c) 2023
Yunye He
Masaru Koido
Yuka Shimmori
Yoichiro Kamatani
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
