ReviewAnnual review of genomics and human genetics2023
Methods and Insights from Single-Cell Expression Quantitative Trait Loci.
Review in Annual review of genomics and human genetics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
36 citing papers in PubMed, 42 citations in OpenAlex.
- Single-nucleus atlas of cell-type specific genetic regulation in the human brain.Nature genetics · 2026Article
- Integrating multi-omics and mendelian randomization identifies therapeutic targets for Lichen Sclerosus: A druggable genome-wide study.Global medical genetics · 2026Article
- Genetic influences on haematopoiesis.Nature reviews. Genetics · 2026Review
- Integrating bulk and single-cell RNA sequencing with GWAS reveals regulatory networks underpinning complex traits in beef cattle.Journal of animal science and biotechnology · 2026Article
- Gene Expression and Alternative Splicing Regulate Phenotypic Plasticity of a Social Wasp.Ecology and evolution · 2026Article
- Integration of single-cell cis-expression quantitative trait locus and Mendelian randomization analyses identifies a Treg-specific gene for precision therapy in rheumatoid arthritis, gonarthrosis, and gouty arthritis.The Journal of international medical research · 2026Article
- Predicting gene-specific regulation with transcriptomic and epigenetic single-cell data.Bioinformatics (Oxford, England) · 2026Article
- Identifying Single-Cell Expression Quantitative Trait Loci Using a Bootstrap Penalized Hurdle Model.Genes · 2026Article
- Single-cell eQTL-based Mendelian randomization identifies immune cell subtype-specific regulators of epigenetic aging and prioritizes candidate therapeutic targets.Biogerontology · 2026Review
- Integrating Genetics and Environment to Find Causal Mechanisms for Multiple Sclerosis.European journal of immunology · 2026Review
- Single-cell polygenic risk scores dissect cellular and molecular heterogeneity of complex human diseases.Nature biotechnology · 2026Article
- eQTL analysis: A bridge from genome to mechanism.Genes & diseases · 2026Review
- Envisioning population-scale immune multi-omics atlas projects.Clinical and translational medicine · 2026Article
- Experimental and computational methods for allelic imbalance analysis from single-nucleus RNA-seq data.Genome biology · 2026Article
- An integrative single-nucleus multiomic atlas of the human left ventricle identifies gene regulatory network dynamics across cardiac development, aging, and disease.Genome biology · 2026Article
- Single-Cell eQTL Revealing Brain Cell-Type-Specific Genetic Control of Insomnia.Journal of molecular neuroscience : MN · 2026Article
- Integrative single-cell eQTL and multi-omics analyses reveal AIM1 and ANXA1 as immune-related hub genes and potential therapeutic targets in head and neck cancer.Frontiers in oncology · 2026Article
- Airqtl dissects cell state-specific causal gene regulatory networks with efficient single-cell eQTL mapping.Nature communications · 2025Article
- Modeling heterogeneity in single-cell perturbation states enhances detection of response eQTLs.Nature genetics · 2025Article
- Research progress of single cell RNA sequencing in nervous system.Molecular biology reports · 2025Review
Corrections and comments
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Authors and funding
5 authors at 4 institutions in 3 countries.
Funding
Abstract
Recent advancements in single-cell technologies have enabled expression quantitative trait locus (eQTL) analysis across many individuals at single-cell resolution. Compared with bulk RNA sequencing, which averages gene expression across cell types and cell states, single-cell assays capture the transcriptional states of individual cells, including fine-grained, transient, and difficult-to-isolate populations at unprecedented scale and resolution. Single-cell eQTL (sc-eQTL) mapping can identify context-dependent eQTLs that vary with cell states, including some that colocalize with disease variants identified in genome-wide association studies. By uncovering the precise contexts in which these eQTLs act, single-cell approaches can unveil previously hidden regulatory effects and pinpoint important cell states underlying molecular mechanisms of disease. Here, we present an overview of recently deployed experimental designs in sc-eQTL studies. In the process, we consider the influence of study design choices such as cohort, cell states, and ex vivo perturbations. We then discuss current methodologies, modeling approaches, and technical challenges as well as future opportunities and applications.
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Registered trials
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.