Assocplots: a Python package for static and interactive visualization of multiple-group GWAS results.
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 (QQ) 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 QQ plots, but also through a dynamic extension which allows to interactively visualize the relationships between GWAS results from multiple cohorts or studies.



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.



ekhramts@medicine.bsd.uchicago.edu or bstranger@medicine.bsd.uchicago.edu
Department of Medicine, Section of Genetic Medicine, The University of Chicago, Chicago, IL, USA.|Institute for Genomics and Systems Biology, The University of Chicago, Chicago, IL, USA.
Ekaterina A
EA
Khramtsova
Department of Medicine, Section of Genetic Medicine, The University of Chicago, Chicago, IL, USA.|Institute for Genomics and Systems Biology, The University of Chicago, Chicago, IL, USA.|Center for Data Intensive Science, The University of Chicago, Chicago, IL, USA.
Barbara E
BE
Stranger
D014644:Genetic Variation; D055106:Genome-Wide Association Study / Q000379:methods*; D012984:Software