ArticleBMC genomics2021
scReQTL: an approach to correlate SNVs to gene expression from individual scRNA-seq datasets.
Article in BMC genomics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis 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
12 citing papers in PubMed, 1 synthesis or guideline pooled it, 28 citations in OpenAlex.
- Guidelines for bioinformatics of single-cell sequencing data analysis in Alzheimer's disease: review, recommendation, implementation and application.Molecular neurodegeneration · 2022Pooled it
- Experimental and computational methods for allelic imbalance analysis from single-nucleus RNA-seq data.Genome biology · 2026Article
- GhLPF1 Associated Network Is Involved with Cotton Lint Percentage Regulation Revealed by the Integrative Analysis of Spatial Transcriptome.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- A brief guide to analyzing expression quantitative trait loci.Molecules and cells · 2024Review
- Hemoglobin nanoclusters-mediated regulation of KPNA4 in hypoxic tumor microenvironment enhances photodynamic therapy in hepatocellular carcinoma.Journal of nanobiotechnology · 2024Article
- Methods and Insights from Single-Cell Expression Quantitative Trait Loci.Annual review of genomics and human genetics · 2023Review
- Genetic control of the dynamic transcriptional response to immune stimuli and glucocorticoids at single-cell resolution.Genome research · 2023Article
- eQTL Studies: from Bulk Tissues to Single Cells.ArXiv · 2023Article
- SCExecute: custom cell barcode-stratified analyses of scRNA-seq data.Bioinformatics (Oxford, England) · 2023Article
- Genetic control of the dynamic transcriptional response to immune stimuli and glucocorticoids at single cell resolution.bioRxiv : the preprint server for biology · 2022Article
- Article
- SCReadCounts: estimation of cell-level SNVs expression from scRNA-seq data.BMC genomics · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors at 4 institutions in 4 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundRecently, pioneering expression quantitative trait loci (eQTL) studies on single cell RNA sequencing (scRNA-seq) data have revealed new and cell-specific regulatory single nucleotide variants (SNVs). Here, we present an alternative QTL-related approach applicable to transcribed SNV loci from scRNA-seq data: scReQTL. ScReQTL uses Variant Allele Fraction (VAF
resultsOur approach employs the advantage that, when estimated from multiple cells, VAF
conclusionScReQTL is relevant to the rapidly growing source of scRNA-seq data and can be applied to outline SNVs potentially contributing to cell type-specific and/or dynamic genetic interactions from an individual scRNA-seq dataset. AVAILABILITY: https://github.com/HorvathLab/NGS/tree/master/scReQTL.
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.