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Guided construction of single cell reference for human and mouse lung.

Authors :
Guo M
Morley MP
Jiang C
Wu Y
Li G
Du Y
Zhao S
Wagner A
Cakar AC
Kouril M
Jin K
Gaddis N
Kitzmiller JA
Stewart K
Basil MC
Lin SM
Ying Y
Babu A
Wikenheiser-Brokamp KA
Mun KS
Naren AP
Clair G
Adkins JN
Pryhuber GS
Misra RS
Aronow BJ
Tickle TL
Salomonis N
Sun X
Morrisey EE
Whitsett JA
Xu Y
Source :
Nature communications [Nat Commun] 2023 Jul 29; Vol. 14 (1), pp. 4566. Date of Electronic Publication: 2023 Jul 29.
Publication Year :
2023

Abstract

Accurate cell type identification is a key and rate-limiting step in single-cell data analysis. Single-cell references with comprehensive cell types, reproducible and functionally validated cell identities, and common nomenclatures are much needed by the research community for automated cell type annotation, data integration, and data sharing. Here, we develop a computational pipeline utilizing the LungMAP CellCards as a dictionary to consolidate single-cell transcriptomic datasets of 104 human lungs and 17 mouse lung samples to construct LungMAP single-cell reference (CellRef) for both normal human and mouse lungs. CellRefs define 48 human and 40 mouse lung cell types catalogued from diverse anatomic locations and developmental time points. We demonstrate the accuracy and stability of LungMAP CellRefs and their utility for automated cell type annotation of both normal and diseased lungs using multiple independent methods and testing data. We develop user-friendly web interfaces for easy access and maximal utilization of the LungMAP CellRefs.<br /> (© 2023. The Author(s).)

Details

Language :
English
ISSN :
2041-1723
Volume :
14
Issue :
1
Database :
MEDLINE
Journal :
Nature communications
Publication Type :
Academic Journal
Accession number :
37516747
Full Text :
https://doi.org/10.1038/s41467-023-40173-5