Gene implication methods (GIMs) are crucial tools for analyzing genome-wide association studies, but are often ambiguous. We present the LocusCompare2 platform to incorporate six popular GIMs and hundreds of quantitative trait loci datasets, enabling validation across several GIMs and window settings to improve accuracy and reproducibility.
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Data availability
GTEx eQTL data can be accessed via https://gtexportal.org/home/datasets. eQTL catalogue data can be accessed via https://www.ebi.ac.uk/eqtl/Studies/. Human blood cell GWAS summary statistics are available in the GWAS catalog https://www.ebi.ac.uk/gwas/downloads/summary-statistics. Pre-computed predictive models for GTEx 49 tissues for FUSION are from http://gusevlab.org/projects/fusion/. Pre-computed transcriptome weights for GTEx 49 tissues for PrediXcan are downloaded from https://predictdb.org/. The simulated data and the LocusCompare2 results of 36 human blood cell traits GWAS summary statistics can be accessed via Zenodo at https://doi.org/10.5281/zenodo.13831373.
Code availability
LocusCompare2 is available at https://www.locuscompare2.com, and an open-source software is at locuscompare2-standalone. Processing scripts for LocusCompare2 are at LocusCompare2_visualization.
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Acknowledgements
B.L. is supported by the Ministry of Education, Singapore, under its Academic Research Fund Tier 2 (MOE-T2EP30123-0015) and Academic Research Fund Tier 1 (FY2023; 23-0434-A0001; 22-5800-A0001), by A*STAR under the Nucleic Acid Therapeutics Initiative (award H24J5a0066), by the National University of Singapore Presidential Young Professorship, and by the NUS Artificial Intelligence Institute (NAII-SG-2025-026). This research is partially supported by the Precision Medicine Translational Research Programme Core Funding under NUHSRO/2020/080/MSC/04/PM. The computational work for this article was partially performed on resources of the National Supercomputing Centre, Singapore (https://www.nscc.sg) and partially supported by NUS IT’s Cloud Credits for Research Programme. We thank Hangzhou LUCA Intelligent Technology for their contribution to the software development and testing efforts.
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Nature Genetics thanks Ayellet Segrè and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.
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Supplementary Methods, and Supplementary Figures 1-5.
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Excel workbook containing Supplementary Tables 1-6. Including literature review details, lists of used GWAS and eQTL datasets, gene implication results used in manuscript, and a reporting templete for gene implication methods.
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Liu, F., Gao, J., Lin, Y. et al. Mitigating inconsistencies in GWAS follow-up analyses with LocusCompare2. Nat Genet 57, 2606–2613 (2025). https://doi.org/10.1038/s41588-025-02331-x
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DOI: https://doi.org/10.1038/s41588-025-02331-x
