Integrated analysis of multimodal single-cell data

Copyright © 2021 The Authors. Published by Elsevier Inc. All rights reserved..

The simultaneous measurement of multiple modalities represents an exciting frontier for single-cell genomics and necessitates computational methods that can define cellular states based on multimodal data. Here, we introduce "weighted-nearest neighbor" analysis, an unsupervised framework to learn the relative utility of each data type in each cell, enabling an integrative analysis of multiple modalities. We apply our procedure to a CITE-seq dataset of 211,000 human peripheral blood mononuclear cells (PBMCs) with panels extending to 228 antibodies to construct a multimodal reference atlas of the circulating immune system. Multimodal analysis substantially improves our ability to resolve cell states, allowing us to identify and validate previously unreported lymphoid subpopulations. Moreover, we demonstrate how to leverage this reference to rapidly map new datasets and to interpret immune responses to vaccination and coronavirus disease 2019 (COVID-19). Our approach represents a broadly applicable strategy to analyze single-cell multimodal datasets and to look beyond the transcriptome toward a unified and multimodal definition of cellular identity.

Medienart:

E-Artikel

Erscheinungsjahr:

2021

Erschienen:

2021

Enthalten in:

Zur Gesamtaufnahme - volume:184

Enthalten in:

Cell - 184(2021), 13 vom: 24. Juni, Seite 3573-3587.e29

Sprache:

Englisch

Beteiligte Personen:

Hao, Yuhan [VerfasserIn]
Hao, Stephanie [VerfasserIn]
Andersen-Nissen, Erica [VerfasserIn]
Mauck, William M [VerfasserIn]
Zheng, Shiwei [VerfasserIn]
Butler, Andrew [VerfasserIn]
Lee, Maddie J [VerfasserIn]
Wilk, Aaron J [VerfasserIn]
Darby, Charlotte [VerfasserIn]
Zager, Michael [VerfasserIn]
Hoffman, Paul [VerfasserIn]
Stoeckius, Marlon [VerfasserIn]
Papalexi, Efthymia [VerfasserIn]
Mimitou, Eleni P [VerfasserIn]
Jain, Jaison [VerfasserIn]
Srivastava, Avi [VerfasserIn]
Stuart, Tim [VerfasserIn]
Fleming, Lamar M [VerfasserIn]
Yeung, Bertrand [VerfasserIn]
Rogers, Angela J [VerfasserIn]
McElrath, Juliana M [VerfasserIn]
Blish, Catherine A [VerfasserIn]
Gottardo, Raphael [VerfasserIn]
Smibert, Peter [VerfasserIn]
Satija, Rahul [VerfasserIn]

Links:

Volltext

Themen:

CITE-seq
COVID-19
Immune system
Journal Article
Multimodal analysis
Reference mapping
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
Single cell genomics
T cell

Anmerkungen:

Date Completed 01.07.2021

Date Revised 26.04.2023

published: Print-Electronic

Citation Status MEDLINE

doi:

10.1016/j.cell.2021.04.048

funding:

Förderinstitution / Projekttitel:

PPN (Katalog-ID):

NLM326106219