biostudies-literatureUnknownAw ANHGRI NIH HHSNIGMS NIH HHSFine-mapping methods, which aim to identify genetic variants responsible for complex traits following genetic association studies, typically assume that sufficient adjustments for confounding within the association study cohort have been made, e.g., through regressing out the top principal components (i.e., residualization). Despite its widespread use, however, residualization may not completely remove all sources of confounding. Here, we propose a complementary stability-guided approach that does not rely on residualization, which identifies consistently fine-mapped variants across different genetic backgrounds or environments. We demonstrate the utility of this approach by applying it to fine-map eQTLs in the GEUVADIS data. Using 378 different functional annotations of the human genome, bioRxiv : the preprint server for biology2023.04.11.536456https://www.ebi.ac.uk/biostudies/studies/S-EPMC10120703biostudies-literatureThe Impact of Stability Considerations on Genetic Fine-Mapping.PMC10120703R00 HG009677R35 GM134922Ioannidis NAw AJin LCSong YSfalseThe Impact of Stability Considerations on Genetic Fine-Mapping.Fine-mapping methods, which aim to identify genetic variants responsible for complex traits following genetic association studies, typically assume that sufficient adjustments for confounding within the association study cohort have been made, e.g., through regressing out the top principal components (i.e., residualization). Despite its widespread use, however, residualization may not completely remove all sources of confounding. Here, we propose a complementary stability-guided approach that does not rely on residualization, which identifies consistently fine-mapped variants across different genetic backgrounds or environments. We demonstrate the utility of this approach by applying it to fine-map eQTLs in the GEUVADIS data. Using 378 different functional annotations of the human genome, 2023-01-01T00:00:00Z2023 Apr2025-06-25T03:04:18.636Z2025-06-25T03:04:18.636ZS-EPMC101207033709051410.1101/2023.04.11.536456