ArticleGenes2020
Estimating the Allele-Specific Expression of SNVs From 10× Genomics Single-Cell RNA-Sequencing Data.
Article in Genes, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 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.
The trial behind it
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Who cites it
15 citing papers in PubMed, 25 citations in OpenAlex.
- Experimental and computational methods for allelic imbalance analysis from single-nucleus RNA-seq data.Genome biology · 2026Article
- Assessment of XCI skewing and demonstration of XCI escape region based on single-cell RNA sequencing: comparison between female Grave's disease and control.BMC molecular and cell biology · 2025Article
- Computational methods for allele-specific expression in single cells.Trends in genetics : TIG · 2024Review
- Cell-cell communication: new insights and clinical implications.Signal transduction and targeted therapy · 2024Review
- CanCellVar: A database for single-cell variants map in human cancer.American journal of human genetics · 2024Article
- Detection of allele-specific expression in spatial transcriptomics with spASE.Genome biology · 2024Article
- Examining parent-of-origin effects on transcription and RNA methylation in mediating aggressive behavior in honey bees (Apis mellifera).BMC genomics · 2023Article
- Random allelic expression in the adult human body.Cell reports · 2023Article
- SCExecute: custom cell barcode-stratified analyses of scRNA-seq data.Bioinformatics (Oxford, England) · 2023Article
- Review
- Article
- SCReadCounts: estimation of cell-level SNVs expression from scRNA-seq data.BMC genomics · 2021Article
- scReQTL: an approach to correlate SNVs to gene expression from individual scRNA-seq datasets.BMC genomics · 2021Article
- Biological and Medical Importance of Cellular Heterogeneity Deciphered by Single-Cell RNA Sequencing.Cells · 2020Review
- Review
Corrections and comments
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Authors and funding
9 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
With the recent advances in single-cell RNA-sequencing (scRNA-seq) technologies, the estimation of allele expression from single cells is becoming increasingly reliable. Allele expression is both quantitative and dynamic and is an essential component of the genomic interactome. Here, we systematically estimate the allele expression from heterozygous single nucleotide variant (SNV) loci using scRNA-seq data generated on the 10×Genomics Chromium platform. We analyzed 26,640 human adipose-derived mesenchymal stem cells (from three healthy donors), sequenced to an average of 150K sequencing reads per cell (more than 4 billion scRNA-seq reads in total). High-quality SNV calls assessed in our study contained approximately 15% exonic and >50% intronic loci. To analyze the allele expression, we estimated the expressed variant allele fraction (VAF
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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.