ArticleBioinformatics (Oxford, England)2021
Systematic determination of the mitochondrial proportion in human and mice tissues for single-cell RNA-sequencing data quality control.
Article in Bioinformatics (Oxford, England), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 158 papers, 3 of them syntheses that pooled it.
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158 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- Meta-Analysis of Human Cancer Single-Cell RNA-Seq Datasets Using the IMMUcan Database.Cancer research · 2023Pooled it
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- What are the applications of single-cell RNA sequencing in cancer research: a systematic review.Journal of experimental & clinical cancer research : CR · 2021Pooled it
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- Machine learning-driven development of a novel unfolded protein response-related gene signature for predicting lung adenocarcinoma patient prognosis.BMC cancer · 2026Article
- ScQCenrich enables multi-metric quality control for single-cell RNA sequencing.Communications biology · 2026Article
- RNAlater-compatible protocol for nuclei isolation from radical prostatectomy prostate cancer resections, enabling single-nucleus resolution RNA-seq.Scientific reports · 2026Article
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98 more citing papers are in PubMed but not listed here.
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Abstract
motivationQuality control (QC) is a critical step in single-cell RNA-seq (scRNA-seq) data analysis. Low-quality cells are removed from the analysis during the QC process to avoid misinterpretation of the data. An important QC metric is the mitochondrial proportion (mtDNA%), which is used as a threshold to filter out low-quality cells. Early publications in the field established a threshold of 5% and since then, it has been used as a default in several software packages for scRNA-seq data analysis, and adopted as a standard in many scRNA-seq studies. However, the validity of using a uniform threshold across different species, single-cell technologies, tissues and cell types has not been adequately assessed.
resultsWe systematically analyzed 5 530 106 cells reported in 1349 annotated datasets available in the PanglaoDB database and found that the average mtDNA% in scRNA-seq data across human tissues is significantly higher than in mouse tissues. This difference is not confounded by the platform used to generate the data. Based on this finding, we propose new reference values of the mtDNA% for 121 tissues of mouse and 44 tissues of humans. In general, for mouse tissues, the 5% threshold performs well to distinguish between healthy and low-quality cells. However, for human tissues, the 5% threshold should be reconsidered as it fails to accurately discriminate between healthy and low-quality cells in 29.5% (13 of 44) tissues analyzed. We conclude that omitting the mtDNA% QC filter or adopting a suboptimal mtDNA% threshold may lead to erroneous biological interpretations of scRNA-seq data. AVAILABILITYAND IMPLEMENTATION: The code used to download datasets, perform the analyzes and produce the figures is available at https://github.com/dosorio/mtProportion. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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