SNPannotator: Automated Functional Annotation of Genetic Variants and Linked Proxies

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ID: 326345
2026
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Abstract
SUMMARY: Genome-wide association studies (GWASs) have identified thousands of genetic variants associated with complex traits and diseases. However, explaining the mechanisms underlying phenotypic variation remains challenging. Here, we introduce SNPannotator, an automated post-GWAS analysis software package designed to streamline the interpretation of GWAS findings. Our pipeline implements a multi-step process that identifies proxy variants in high linkage disequilibrium (LD) with associated lead variants, then queries comprehensive resources (including Ensembl, the GTEx Portal, the eQTL Catalog, and STRING DB) for genomic position, deleteriousness, regulatory annotations, clinical significance, trait associations, expression (eQTLs) and splicing quantitative trait loci (sQTLs), and functional enrichment analyses and compiles the results into user-friendly reports. This package is implemented in the R programming language and includes auxiliary functions for variant lookup and LD exploration. SNPannotator provides a practical framework for efficiently deriving biologically meaningful insights from GWAS data and for assisting researchers in prioritizing candidate variants for functional validation. AVAILABILITY AND IMPLEMENTATION: The SNPannotator package is available from the Comprehensive R Archive Network (CRAN) at https://cran.r-project.org/web/packages/SNPannotator. The development version and tutorial is available on GitHub (https://github.com/omicslaboratory/SNPannotator). The online version of the package is available at https://omicslab.org/snpannotator. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Reference Key
openalex_W7204136169 Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Alireza Ani, Ilja M Nolte, Zoha Kamali, Harold Snieder, Ahmad Vaez
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Journal BMC Bioinformatics
Year 2026
DOI
10.1093/bioinformatics/btag603
URL
https://doi.org/10.1093/bioinformatics/btag603
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