ReviewFrontiers in genetics2023
Expression quantitative trait locus studies in the era of single-cell omics.
Review in Frontiers in genetics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.
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.
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
8 citing papers in PubMed, 1 synthesis or guideline pooled it, 6 citations in OpenAlex.
- Integrating cell-type-specific gene expression and genome-wide associations identifies risk genes for schizophrenia.Molecular psychiatry · 2026Pooled it
- Machine learning and statistical methods for molecular quantitative trait loci.Nature reviews. Genetics · 2026Review
- Single-Cell and Spatial Omics Technologies in Rice Abiotic Stress Biology: A Methodological Review.International journal of molecular sciences · 2026Review
- Deciphering the genetic control of immune cell function at single-cell resolution: Disease-Specific Cis-eQTLs analysis of COVID-19.Immunogenetics · 2026Article
- distQTL: distribution quantitative trait loci identification by population-scale single-cell data.NAR genomics and bioinformatics · 2025Article
- distQTL: Distribution Quantitative Trait Loci Identification by Population-Scale Single-Cell Data.bioRxiv : the preprint server for biology · 2025Article
- EQTL analyses are a formidable tool to define the immunogenetic mechanisms underpinning Spondyloarthropathies.Frontiers in immunology · 2025Article
- Single-cell sequencing to multi-omics: technologies and applications.Biomarker research · 2024Review
Corrections and comments
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Authors and funding
6 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Genome-wide association studies have revealed that the regulation of gene expression bridges genetic variants and complex phenotypes. Profiling of the bulk transcriptome coupled with linkage analysis (expression quantitative trait locus (eQTL) mapping) has advanced our understanding of the relationship between genetic variants and gene regulation in the context of complex phenotypes. However, bulk transcriptomics has inherited limitations as the regulation of gene expression tends to be cell-type-specific. The advent of single-cell RNA-seq technology now enables the identification of the cell-type-specific regulation of gene expression through a single-cell eQTL (sc-eQTL). In this review, we first provide an overview of sc-eQTL studies, including data processing and the mapping procedure of the sc-eQTL. We then discuss the benefits and limitations of sc-eQTL analyses. Finally, we present an overview of the current and future applications of sc-eQTL discoveries.
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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.