SNPannotator: automated functional annotation of genetic variants and linked proxies

(2026) SNPannotator: automated functional annotation of genetic variants and linked proxies. Bioinformatics. p. 5. ISSN 1367-4803

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Abstract

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.

Item Type: Article
Keywords: association Biochemistry & Molecular Biology Biotechnology & Applied Microbiology Computer Science Mathematical & Computational Biology Mathematics
Page Range: p. 5
Journal or Publication Title: Bioinformatics
Journal Index: ISI
Volume: 42
Number: 9
Identification Number: https://doi.org/10.1093/bioinformatics/btag603
ISSN: 1367-4803
Depositing User: خانم ناهید ضیائی
URI: http://eprints.mui.ac.ir/id/eprint/33961

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