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GoFCards: an integrated database and analytic platform for gain of function variants in humans. | LitMetric

GoFCards: an integrated database and analytic platform for gain of function variants in humans.

Nucleic Acids Res

National Clinical Research Center for Geriatric Disorders, Department of Geriatrics, Xiangya Hospital & Center for Medical Genetics, School of Life Sciences, Central South University, No. 87 Xiangya Road, Furong District, Changsha, Hunan 410008, China.

Published: January 2025

AI Article Synopsis

  • Gain-of-function (GOF) variants enhance or change protein functions and are crucial for understanding diseases, but identifying them is tough due to scattered data and limited databases.
  • The authors reviewed existing research to gather 3089 single-nucleotide variants and 72 small insertions/deletions across 579 genes linked to 1299 diseases, combining this with 3.5 million predicted GOF variants and employing a custom scoring system to rank their significance.
  • They created GoFCards, a user-friendly database that allows geneticists and clinicians to easily access and analyze GOF variants, providing extensive annotations and the ability to prioritize variants even for those with limited bioinformatics experience.

Article Abstract

Gain-of-function (GOF) variants, which introduce new or amplify protein functions, are essential for understanding disease mechanisms. Despite advances in genomics and functional research, identifying and analyzing pathogenic GOF variants remains challenging owing to fragmented data and database limitations, underscoring the difficulty in accessing critical genetic information. To address this challenge, we manually reviewed the literature, pinpointing 3089 single-nucleotide variants and 72 insertions and deletions in 579 genes associated with 1299 diseases from 2069 studies, and integrated these with the 3.5 million predicted GOF variants. Our approach is complemented by a proprietary scoring system that prioritizes GOF variants on the basis of the evidence supporting their GOF effects and provides predictive scores for variants that lack existing documentation. We then developed a database named GoFCards for general geneticists and clinicians to easily obtain GOF variants in humans (http://www.genemed.tech/gofcards). This database also contains data from >150 sources and offers comprehensive variant-level and gene-level annotations, with the aim of providing users with convenient access to detailed and relevant genetic information. Furthermore, GoFCards empowers users with limited bioinformatic skills to analyze and annotate genetic data, and prioritize GOF variants. GoFCards offers an efficient platform for interpreting GOF variants and thereby advancing genetic research.

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Source
http://dx.doi.org/10.1093/nar/gkae1079DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11701611PMC

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