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SampleQC: robust multivariate, multi-cell type, multi-sample quality control for single-cell data

Quality control (QC) is a critical component of single-cell RNA-seq (scRNA-seq) processing pipelines. Current approaches to QC implicitly assume that datasets are comprised of one cell type, potentially resulting in biased exclusion of rare cell types. We introduce SampleQC, which robustly fits a Ga...

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Detalles Bibliográficos
Autores principales: Macnair, Will, Robinson, Mark
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9912498/
https://www.ncbi.nlm.nih.gov/pubmed/36765378
http://dx.doi.org/10.1186/s13059-023-02859-3
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author Macnair, Will
Robinson, Mark
author_facet Macnair, Will
Robinson, Mark
author_sort Macnair, Will
collection PubMed
description Quality control (QC) is a critical component of single-cell RNA-seq (scRNA-seq) processing pipelines. Current approaches to QC implicitly assume that datasets are comprised of one cell type, potentially resulting in biased exclusion of rare cell types. We introduce SampleQC, which robustly fits a Gaussian mixture model across multiple samples, improves sensitivity, and reduces bias compared to current approaches. We show via simulations that SampleQC is less susceptible to exclusion of rarer cell types. We also demonstrate SampleQC on a complex real dataset (867k cells over 172 samples). SampleQC is general, is implemented in R, and could be applied to other data types. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13059-023-02859-3.
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spelling pubmed-99124982023-02-11 SampleQC: robust multivariate, multi-cell type, multi-sample quality control for single-cell data Macnair, Will Robinson, Mark Genome Biol Method Quality control (QC) is a critical component of single-cell RNA-seq (scRNA-seq) processing pipelines. Current approaches to QC implicitly assume that datasets are comprised of one cell type, potentially resulting in biased exclusion of rare cell types. We introduce SampleQC, which robustly fits a Gaussian mixture model across multiple samples, improves sensitivity, and reduces bias compared to current approaches. We show via simulations that SampleQC is less susceptible to exclusion of rarer cell types. We also demonstrate SampleQC on a complex real dataset (867k cells over 172 samples). SampleQC is general, is implemented in R, and could be applied to other data types. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13059-023-02859-3. BioMed Central 2023-02-10 /pmc/articles/PMC9912498/ /pubmed/36765378 http://dx.doi.org/10.1186/s13059-023-02859-3 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Method
Macnair, Will
Robinson, Mark
SampleQC: robust multivariate, multi-cell type, multi-sample quality control for single-cell data
title SampleQC: robust multivariate, multi-cell type, multi-sample quality control for single-cell data
title_full SampleQC: robust multivariate, multi-cell type, multi-sample quality control for single-cell data
title_fullStr SampleQC: robust multivariate, multi-cell type, multi-sample quality control for single-cell data
title_full_unstemmed SampleQC: robust multivariate, multi-cell type, multi-sample quality control for single-cell data
title_short SampleQC: robust multivariate, multi-cell type, multi-sample quality control for single-cell data
title_sort sampleqc: robust multivariate, multi-cell type, multi-sample quality control for single-cell data
topic Method
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9912498/
https://www.ncbi.nlm.nih.gov/pubmed/36765378
http://dx.doi.org/10.1186/s13059-023-02859-3
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