CoffeeProt: an online tool for correlation and functional enrichment of systems genetics data.

Jeffrey Molendijk,Marcus M Seldin,Benjamin L Parker

doi:10.1093/nar/gkab352

Jeffrey Molendijk, Marcus M Seldin + Show 1 more

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https://doi.org/10.1093/nar/gkab352

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Abstract

The integration of genomics, transcriptomics, proteomics and phenotypic traits across genetically diverse populations is a powerful approach to discover novel biological regulators. The increasing volume of complex data require new and easy-to-use tools accessible to a variety of scientists for the discovery and visualization of functionally relevant associations. To meet this requirement, we developed CoffeeProt, an open-source tool that analyses genetic variants associated to protein networks, other omics datatypes and phenotypic traits. CoffeeProt uses transcriptomics or proteomics data to perform correlation network analyses and annotates results with protein-protein interactions, subcellular localisations and drug associations. It then integrates genetic variants associated with gene expression (eQTLs) or protein abundance (pQTLs) and includes predictions of the potential consequences of variants on gene function. Finally, genetic variants are co-mapped to molecular or phenotypic traits either provided by the user or retrieved directly from publicly available GWAS results. We demonstrate its utility with the analysis of mouse and human population data enabling the rapid identification of genetic variants associated with druggable proteins and clinical traits. We expect that CoffeeProt will serve the systems genetics and basic science research communities, leading to the discovery of novel biologically relevant associations. CoffeeProt is available at www.coffeeprot.com.

Highlights

The field of genetics has realized significant progress in the discovery of phenotype-associated genetic variation in recent years [1]
We present CoffeeProt, a novel online tool for the correlation and functional enrichment of proteome-wide systems genetics
The use of a dedicated database for SNP variant effects has allowed the rapid annotation of QTLs, enabling easy prioritization of associations based on predicted variant impacts

Summary

Introduction

The field of genetics has realized significant progress in the discovery of phenotype-associated genetic variation in recent years [1]. As of February 2021, over 247,000 genetic associations have been extracted from more than 11,600 genome-wide associations studies (GWAS), summarised in the GWAS Catalog [2]. This success is attributable to technological advances, access to increasing amounts of genetic and phenotypic data, and the continuous development of novel analytical tools. The functional relevance of phenotype–genotype associations in diverse populations and environments is a rapidly evolving and challenging area in deciphering molecular mechanisms of complex health and disease traits. Systems genetics is an approach in which intermediate molecular phenotypes are examined in relation to genetic variation to improve our understanding of complex traits and common diseases [3]. Linking genetic loci to complex traits via association analysis can be better understood through linking quantitative trait loci

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