Summary: Over the last decade, genome-wide association studies (GWAS) have generated vast amounts of analysis results, requiring development of novel tools for data visualization. Quantile-quantile plots and Manhattan plots are classical tools which have been utilized to visually summarize GWAS results and identify genetic variants significantly associated with traits of interest. However, static visualizations are limiting in the information that can be shown. Here we present Assocplots, a python package for viewing and exploring GWAS results not only using classic static Manhattan and quantile-quantile plots, but also through a dynamic extension which allows to visualize data interactively, and to visualize the relationships between GWAS results from multiple cohorts or studies. Availability: The Assocplots package is open source and distributed under the MIT license via GitHub (https://github.com/khramts/assocplots) along with examples, documentation and installation instructions. Contact: email@example.com, firstname.lastname@example.org
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