ArticleDatabase : the journal of biological databases and curation2024
SingleQ: a comprehensive database of single-cell expression quantitative trait loci (sc-eQTLs) cross human tissues.
Article in Database : the journal of biological databases and curation, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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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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Who cites it
7 citing papers in PubMed, 8 citations in OpenAlex.
- Identifying Single-Cell Expression Quantitative Trait Loci Using a Bootstrap Penalized Hurdle Model.Genes · 2026Article
- ceQTL: a co-expression QTL model to detect a variant that affects transcription factor binding and its target regulation.Briefings in bioinformatics · 2026Article
- eQTL analysis: A bridge from genome to mechanism.Genes & diseases · 2026Review
- Single-cell eQTL mapping reveals cell-type-specific genetic regulation in lung cancer.Cell genomics · 2026Article
- Transcriptome-wide association studies at cell-state level using single-cell eQTL data.Cell genomics · 2026Article
- Genetic variants ofFrontiers in immunology · 2026Article
- scEccDNAdb: an integrated single-cell eccDNA resource for human and mouse.Database : the journal of biological databases and curation · 2024Article
Corrections and comments
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Authors and funding
9 authors at 4 institutions in 3 countries.
Funding
Abstract
Mapping of expression quantitative trait loci (eQTLs) and other molecular QTLs can help characterize the modes of action of disease-associated genetic variants. However, current eQTL databases present data from bulk RNA-seq approaches, which cannot shed light on the cell type- and environment-specific regulation of disease-associated genetic variants. Here, we introduce our Single-cell eQTL Interactive Database which collects single-cell eQTL (sc-eQTL) datasets and provides online visualization of sc-eQTLs across different cell types in a user-friendly manner. Although sc-eQTL mapping is still in its early stage, our database curates the most comprehensive summary statistics of sc-eQTLs published to date. sc-eQTL studies have revolutionized our understanding of gene regulation in specific cellular contexts, and we anticipate that our database will further accelerate the research of functional genomics. Database URL: http://www.sqraolab.com/scqtl.
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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.