EmptyDropsMultiome discriminates real cells from background in single-cell multiomics assays

Abstract Multiomic droplet-based technologies allow different molecular modalities, such as chromatin accessibility and gene expression (scATAC-seq and scRNA-seq), to be probed in the same nucleus. We develop EmptyDropsMultiome, an approach that distinguishes true nuclei-containing droplets from bac...

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Main Authors: Stathis Megas, Valentina Lorenzi, John C. Marioni
Format: Article
Language:English
Published: BMC 2024-05-01
Series:Genome Biology
Subjects:
Online Access:https://doi.org/10.1186/s13059-024-03259-x
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author Stathis Megas
Valentina Lorenzi
John C. Marioni
author_facet Stathis Megas
Valentina Lorenzi
John C. Marioni
author_sort Stathis Megas
collection DOAJ
description Abstract Multiomic droplet-based technologies allow different molecular modalities, such as chromatin accessibility and gene expression (scATAC-seq and scRNA-seq), to be probed in the same nucleus. We develop EmptyDropsMultiome, an approach that distinguishes true nuclei-containing droplets from background. Using simulations, we show that EmptyDropsMultiome has higher statistical power and accuracy than existing approaches, including CellRanger-arc and EmptyDrops. On real datasets, we observe that CellRanger-arc misses more than half of the nuclei identified by EmptyDropsMultiome and, moreover, is biased against certain cell types, some of which have a retrieval rate lower than 20%.
format Article
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publishDate 2024-05-01
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spelling doaj-art-dc7e5b4fb0f44f3ba80919314a8e35b32025-08-20T02:18:35ZengBMCGenome Biology1474-760X2024-05-0125111510.1186/s13059-024-03259-xEmptyDropsMultiome discriminates real cells from background in single-cell multiomics assaysStathis Megas0Valentina Lorenzi1John C. Marioni2European Molecular Biology Laboratory European Bioinformatics InstituteEuropean Molecular Biology Laboratory European Bioinformatics InstituteEuropean Molecular Biology Laboratory European Bioinformatics InstituteAbstract Multiomic droplet-based technologies allow different molecular modalities, such as chromatin accessibility and gene expression (scATAC-seq and scRNA-seq), to be probed in the same nucleus. We develop EmptyDropsMultiome, an approach that distinguishes true nuclei-containing droplets from background. Using simulations, we show that EmptyDropsMultiome has higher statistical power and accuracy than existing approaches, including CellRanger-arc and EmptyDrops. On real datasets, we observe that CellRanger-arc misses more than half of the nuclei identified by EmptyDropsMultiome and, moreover, is biased against certain cell types, some of which have a retrieval rate lower than 20%.https://doi.org/10.1186/s13059-024-03259-xMultiomicsSingle-cellMethod
spellingShingle Stathis Megas
Valentina Lorenzi
John C. Marioni
EmptyDropsMultiome discriminates real cells from background in single-cell multiomics assays
Genome Biology
Multiomics
Single-cell
Method
title EmptyDropsMultiome discriminates real cells from background in single-cell multiomics assays
title_full EmptyDropsMultiome discriminates real cells from background in single-cell multiomics assays
title_fullStr EmptyDropsMultiome discriminates real cells from background in single-cell multiomics assays
title_full_unstemmed EmptyDropsMultiome discriminates real cells from background in single-cell multiomics assays
title_short EmptyDropsMultiome discriminates real cells from background in single-cell multiomics assays
title_sort emptydropsmultiome discriminates real cells from background in single cell multiomics assays
topic Multiomics
Single-cell
Method
url https://doi.org/10.1186/s13059-024-03259-x
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AT valentinalorenzi emptydropsmultiomediscriminatesrealcellsfrombackgroundinsinglecellmultiomicsassays
AT johncmarioni emptydropsmultiomediscriminatesrealcellsfrombackgroundinsinglecellmultiomicsassays