topr: an R package for viewing and annotating genetic association results

Author:

Juliusdottir Thorhildur

Abstract

Abstract Background The successful identification of genetic loci for complex traits in genome-wide association studies (GWAS) has resulted in thousands of GWAS summary statistics becoming publicly available for hundreds of complex traits from multiple cohorts and studies. Visualisation is an important aid for interpreting, comparing, validating, and obtaining an overview of large amounts of data. However, the current software is limited in its ability and flexibility to annotate and simultaneously display multiple GWAS results which is useful when interpreting and comparing association results. Therefore, I created the topr R package to facilitate visualisation, annotation, and comparisons of single or multiple GWAS results. It contains functions tailored for viewing and analysing GWAS results. Results topr provides a fast and elegant visual display of association results, along with the annotation of association peaks with their nearest gene. Association results from multiple analyses can be viewed simultaneously over the entire genome or in a more detailed regional view along with gene information. Users can perform the essential steps of visually exploring and annotating association results and generating elegant publication-ready plots. Conclusions topr is developed as a package for the R statistical computing environment, released under the GNU General Public License, and is freely available on the Comprehensive R Archive Network (http://cran.r-project.org/package=topr). The source code is available at GitHub (https://github.com/totajuliusd/topr). topr provides several advantages and advances over the current alternatives, particularly in its gene annotation functionality and customisable display of single- or multiple-association results. With topr, I provide a flexible tool with multiple features to aid in the analysis and evaluation of GWAS association results.

Publisher

Springer Science and Business Media LLC

Subject

Applied Mathematics,Computer Science Applications,Molecular Biology,Biochemistry,Structural Biology

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