Predicting the direction of phenotypic difference

David Gokhman (), Keith D. Harris, Shai Carmi and Gili Greenbaum ()
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David Gokhman: The Weizmann Institute of Science
Keith D. Harris: The Hebrew University of Jerusalem
Shai Carmi: The Hebrew University of Jerusalem
Gili Greenbaum: The Hebrew University of Jerusalem

Nature Communications, 2025, vol. 16, issue 1, 1-11

Abstract: Abstract Predicting phenotypes from genomes is a major goal in genetics, but for most complex phenotypes, predictions are largely inaccurate. Here, we propose a more achievable alternative: relative prediction of phenotypic differences. Even with incomplete genotype-to-phenotype mapping, we show that it is often straightforward to determine whether an individual’s phenotype exceeds a threshold (e.g., of disease risk) or which of two individuals has a greater phenotypic value. We evaluated prediction accuracy on tens of thousands of individuals from the same family, same population, or different species. We found that the direction of a phenotypic difference can often be identified with >90% accuracy. This approach also helps overcome some limitations in transferring genetic association results across populations. Overall, our approach enables accurate predictions of key information on phenotypes — the direction of phenotypic difference — and suggests that more phenotypic information can be extracted from genomic data than previously appreciated.

Date: 2025
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DOI: 10.1038/s41467-025-62355-z

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