Improved integration of single-cell transcriptome and surface protein expression by LinQ-View.
Cell Rep Methods
; 1(4): 100056, 2021 Aug 23.
Article
in English
| MEDLINE | ID: covidwho-1322060
ABSTRACT
Multimodal advances in single-cell sequencing have enabled the simultaneous quantification of cell surface protein expression alongside unbiased transcriptional profiling. Here, we present LinQ-View, a toolkit designed for multimodal single-cell data visualization and analysis. LinQ-View integrates transcriptional and cell surface protein expression profiling data to reveal more accurate cell heterogeneity and proposes a quantitative metric for cluster purity assessment. Through comparison with existing multimodal methods on multiple public CITE-seq datasets, we demonstrate that LinQ-View efficiently generates accurate cell clusters, especially in CITE-seq data with routine numbers of surface protein features, by preventing variations in a single surface protein feature from affecting results. Finally, we utilized this method to integrate single-cell transcriptional and protein expression data from SARS-CoV-2-infected patients, revealing antigen-specific B cell subsets after infection. Our results suggest LinQ-View could be helpful for multimodal analysis and purity assessment of CITE-seq datasets that target specific cell populations (e.g., B cells).
Full text:
Available
Collection:
International databases
Database:
MEDLINE
Language:
English
Journal:
Cell Rep Methods
Year:
2021
Document Type:
Article
Affiliation country:
J.crmeth.2021.100056
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