Evidence map›Paper›PMID 32840568›Full record

ArticleBioinformatics (Oxford, England)2021

Systematic determination of the mitochondrial proportion in human and mice tissues for single-cell RNA-sequencing data quality control.

Daniel Osorio, James J Cai

Abstract read
In one paragraph

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.

0numbers the graph read from it
0cells of the map it votes in
158citing papers in PubMed, 3 pooled it
–field-weighted citation impact
1 · What the graph read from 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.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

158 citing papers in PubMed, 3 syntheses or guidelines pooled it.

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98 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Daniel OsorioDepartment of Veterinary Integrative Biosciences, Texas A&M University, College Station, TX 77843-4458, USA.ORCID 0000-0003-4424-8422
James J CaiDepartment of Veterinary Integrative Biosciences, Texas A&M University, College Station, TX 77843-4458, USA.ORCID 0000-0002-8081-6725

Funding

MADS-box transcriptional regulation of dimorphic transition in Penicillium marneffeiR21AI126219 · NIAID · TEXAS A&M AGRILIFE RESEARCH · PI CAI, JAMES JING, LIN, XIAORONG · 2016 to 2017
$383k
6 · The paper itself

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.

Indexed as

Gene Expression ProfilingSingle-Cell AnalysisAnimalsHumansMiceQuality ControlSequence Analysis, RNASoftware

Identifiers

PMID32840568
PMCPMC8599307

What OpenQuestion holds

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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.