ArticleeLife2020
The single-cell eQTLGen consortium.
Article in eLife, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 143 papers, 5 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
The trial behind it
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
143 citing papers in PubMed, 5 syntheses or guidelines pooled it, 238 citations in OpenAlex.
- Optimized summary-statistic-based single-cell eQTL meta-analysis.Scientific reports · 2025Pooled it
- Identification of genetic variants that impact gene co-expression relationships using large-scale single-cell data.Genome biology · 2023Pooled it
- Meta-analysis of harmonized brain transcriptomics data prioritizes therapeutic target genes.Nature genetics · 2023Pooled it
- Guidelines for bioinformatics of single-cell sequencing data analysis in Alzheimer's disease: review, recommendation, implementation and application.Molecular neurodegeneration · 2022Pooled it
- Multi-ancestry eQTL meta-analysis of human brain identifies candidate causal variants for brain-related traits.Nature genetics · 2022Pooled it
- Translating genome-wide association studies at multiple scales: Drug target prioritization, cellular architectures, and organ imaging.Cell genomics · 2026Review
- Regulatory network topology and the genetic architecture of gene expression.Cell genomics · 2026Article
- FastGxC: Fast and powerful context-specific eQTL mapping in bulk and single-cell data.Cell genomics · 2026Article
- Single-cell eQTL-based Mendelian randomization identifies immune cell subtype-specific regulators of epigenetic aging and prioritizes candidate therapeutic targets.Biogerontology · 2026Review
- eQTL analysis: A bridge from genome to mechanism.Genes & diseases · 2026Review
- Moving Mendelian Randomization From Traditional Risk Factors to Molecular Targets for Drug Development and Clinical Trials in Nephrology.Kidney international reports · 2026Review
- Widespread gene-environment interactions shape the immune response to SARS-CoV-2 infection in hospitalized COVID-19 patients.Nature communications · 2026Article
- Unraveling the Link Between Azathioprine and Acute Pancreatitis: Integrating Network Toxicology, Machine Learning, and Mendelian Randomization.CPT: pharmacometrics & systems pharmacology · 2026Article
- Bridging the variant-to-function gap in type 2 diabetes: advances and challenges.Diabetologia · 2026Review
- Federated single-cell QTL meta-analysis reveals novel disease mechanisms.bioRxiv : the preprint server for biology · 2026Article
- baal-nf identifies motif-disrupting variants that decrease transcription factor binding affinity.Genome biology · 2026Article
- Genetic insights revealed ADRB1 as potential target for clear cell renal cell carcinoma.Frontiers in pharmacology · 2026Article
- Multi-Omics Bioinformatic Analyses Linking LOXL4 with Spondylolisthesis.Orthopedic research and reviews · 2026Article
- High cell-type specificity of eQTLs revealed by single-nucleus analyses of brain and blood.bioRxiv : the preprint server for biology · 2025Article
- Germline polymorphisms in the immunoglobulin kappa and lambda loci underpinning antibody light chain repertoire variability.Nature communications · 2025Article
83 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
16 authors at 9 institutions in 7 countries.
Funding
Abstract
In recent years, functional genomics approaches combining genetic information with bulk RNA-sequencing data have identified the downstream expression effects of disease-associated genetic risk factors through so-called expression quantitative trait locus (eQTL) analysis. Single-cell RNA-sequencing creates enormous opportunities for mapping eQTLs across different cell types and in dynamic processes, many of which are obscured when using bulk methods. Rapid increase in throughput and reduction in cost per cell now allow this technology to be applied to large-scale population genetics studies. To fully leverage these emerging data resources, we have founded the single-cell eQTLGen consortium (sc-eQTLGen), aimed at pinpointing the cellular contexts in which disease-causing genetic variants affect gene expression. Here, we outline the goals, approach and potential utility of the sc-eQTLGen consortium. We also provide a set of study design considerations for future single-cell eQTL studies.
Indexed as
Identifiers
What OpenQuestion holds
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.