ArticleNature communications2021
Leveraging supervised learning for functionally informed fine-mapping of cis-eQTLs identifies an additional 20,913 putative causal eQTLs.
Article in Nature communications, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 70 papers, 1 of them a synthesis that pooled it.
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Who cites it
70 citing papers in PubMed, 1 synthesis or guideline pooled it.
- The genetic and biochemical determinants of mRNA degradation rates in mammals.Genome biology · 2022Pooled it
- Base-pair resolution conservation data improves cell type specific sequence-to-expression prediction.Bioinformatics (Oxford, England) · 2026Article
- Integrating single-cell sQTL mapping with deep-learning splicing prediction identifies causal variants under influenza infection.Genome biology · 2026Article
- Massively parallel characterization and predictive modelling of neuronal regulatory variation.bioRxiv : the preprint server for biology · 2026Article
- Genetic Determinants of Peanut-Specific IgG4 Levels in the Context of Sustained Oral Peanut Exposure in the LEAP Study.Immunology · 2026Article
- Early and late RNA eQTL are driven by different genetic mechanisms.Nature communications · 2026Article
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- Distinguishing causal from tagging enhancers using single-cell multiome data.medRxiv : the preprint server for health sciences · 2026Article
- Practical utility of sequence-to-omics models for improving the reproducibility of genetic fine-mapping.bioRxiv : the preprint server for biology · 2026Article
- Parameter-efficient fine-tuning enables scalable transfer of regulatory sequence models to novel contexts.Genome biology · 2026Article
- scVMAP: a comprehensive platform for integrating single-cell chromatin accessibility regions with causal variants.Nucleic acids research · 2026Article
- Integrative analysis of GWAS, Bayesian fine-mapping, Mendelian randomization and colocalization reveals genetic determinants underlying milk-related traits in dairy cattle.Genetics, selection, evolution : GSE · 2026Article
- Widespread naturally variable human exons aid genetic interpretation.Nature communications · 2025Article
- Integrating extensive functional annotations and multiomics of cattle enhances climate resilience prediction and mapping.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Towards improved fine-mapping of candidate causal variants.Nature reviews. Genetics · 2025Review
- Developing a general AI model for integrating diverse genomic modalities and comprehensive genomic knowledge.Nucleic acids research · 2025Article
- PRISM: ancestry-aware integration of tissue-specific genomic annotations enhances the transferability of polygenic scores.bioRxiv : the preprint server for biology · 2025Article
- Fine-mapping methods for complex traits: essential adaptations for samples of related individuals.Briefings in bioinformatics · 2025Article
10 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
14 authors.
Funding
Abstract
The large majority of variants identified by GWAS are non-coding, motivating detailed characterization of the function of non-coding variants. Experimental methods to assess variants' effect on gene expressions in native chromatin context via direct perturbation are low-throughput. Existing high-throughput computational predictors thus have lacked large gold standard sets of regulatory variants for training and validation. Here, we leverage a set of 14,807 putative causal eQTLs in humans obtained through statistical fine-mapping, and we use 6121 features to directly train a predictor of whether a variant modifies nearby gene expression. We call the resulting prediction the expression modifier score (EMS). We validate EMS by comparing its ability to prioritize functional variants with other major scores. We then use EMS as a prior for statistical fine-mapping of eQTLs to identify an additional 20,913 putatively causal eQTLs, and we incorporate EMS into co-localization analysis to identify 310 additional candidate genes across UK Biobank phenotypes.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.