PubMatcher: A Comprehensive Tool for Gene-Phenotype Associations

PubMatcher is a full-stack web application designed to facilitate the exploration of gene-phenotype associations. Developed using Node.js version 18, with an Express.js backend and a Vue.js 3.5 frontend, the application employs PostgreSQL 14 for data persistence and is fully containerized using Docker. Users can input one or more genes and phenotypes, utilizing the ‘Extract from Text’ feature, which employs a client-side pattern-matching algorithm to identify gene symbols and aliases.

Nature

The application aggregates information through real-time web scraping of PubMed and queries public APIs from UniProt, the International Mouse Phenotyping Consortium (IMPC), and PanelApp. It provides a comprehensive summary of gene-phenotype pairs, displaying key metrics such as constraint scores, publication counts, and functional descriptions. Notably, PubMatcher utilizes gnomAD constraint metrics to assess gene tolerance to loss-of-function and missense variants, which are crucial for clinical relevance.

Nature

PubMatcher integrates data from several authoritative sources, including the Gene Curation Coalition (GenCC), PanelApp England and Australia, and Online Mendelian Inheritance in Man (OMIM). This integration ensures rapid and accurate curation of clinically relevant genes. The output includes detailed information on gene status, pathogenic variants, and links to relevant entries in these databases, enhancing the tool's utility for genetic interpretation.

Nature

The relevance of PubMatcher is particularly evident in whole-genome sequencing (WGS) analyses conducted at the Auragen laboratory in Lyon, France. This laboratory is part of the French 2025 genomic project, which aims to enhance genomic access in healthcare. The application has been evaluated for its effectiveness in identifying variants that are potentially relevant for medical use, demonstrating its significance in the context of rare diseases.

Nature

While PubMatcher offers a robust platform for gene-phenotype exploration, some critics may point to the challenges of ensuring the accuracy of the data retrieved from various sources. Discrepancies between different versions of gnomAD metrics, for instance, highlight the need for careful interpretation of results, as variations in cohort size and quality can affect the reliability of the data.

Nature

PubMatcher does not require user registration, aligning with guidelines for software tools in scientific research. The developers emphasize the importance of accessibility and ease of use, allowing researchers to efficiently explore gene-phenotype associations without barriers.

Nature

Future developments for PubMatcher may include enhancements to its data integration capabilities and user interface, as well as ongoing updates to its underlying databases to ensure the most current information is available for researchers and clinicians.

Nature