| Title: | Assessment of ability of a DNA language model to predict pathogenicity of rare coding variants |
| Journal: | Journal of Human Genetics |
| Published: | 15 Aug 2025 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/40813450/ |
| DOI: | https://doi.org/10.1038/s10038-025-01385-3 |
Publication 16556
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Abstract
A recently described method to predict pathogenicity of DNA variants uses a DNA language model and can be applied to both coding and non-coding variants. For coding variants the performance of this method, termed GPN-MSA (genomic pretrained network with multiple-sequence alignment), was reported to be superior to CADD. We compare the performance of this method against 45 other predictors applied to rare coding variants in 18 gene-phenotype pairs. We find that while GPN-MSA produces stronger evidence for association than CADD it is not the best-performing method for any gene and on average other prediction methods are superior. While GPN-MSA may be useful for predicting the pathogenicity of non-coding variants, it would seem sensible for clinicians and researchers to utilise other methods when dealing with coding variants.This research has been conducted using the UK Biobank Resource.</p>
1 Author
- David Curtis
1 Application
| Application ID | Title |
|---|---|
| 51119 | Study of effects of common and rare genetic variants on health-related phenotypes |
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