Curtis, David;
(2025)
Assessment of ability of a DNA language model to predict pathogenicity of rare coding variants.
Journal of Human Genetics
, 70
pp. 603-607.
10.1038/s10038-025-01385-3.
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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.
| Type: | Article |
|---|---|
| Title: | Assessment of ability of a DNA language model to predict pathogenicity of rare coding variants |
| Location: | England |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1038/s10038-025-01385-3 |
| Publisher version: | https://doi.org/10.1038/s10038-025-01385-3 |
| Language: | English |
| Additional information: | This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences > Div of Biosciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences > Div of Biosciences > Genetics, Evolution and Environment |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10219479 |
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