Journal
BIOINFORMATICS
Volume 36, Issue 18, Pages 4817-4818Publisher
OXFORD UNIV PRESS
DOI: 10.1093/bioinformatics/btaa611
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Funding
- Austrian Science Fund (FWF) [T 974-B30, I3978]
- European Research Council (ERC) [786295]
- German Research Foundation (DFG) [TRR 241]
- Austrian Science Fund (FWF) [I3978] Funding Source: Austrian Science Fund (FWF)
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A Summary: Advances in single-cell technologies have enabled the investigation of T-cell phenotypes and repertoires at unprecedented resolution and scale. Bioinformatic methods for the efficient analysis of these large-scale datasets are instrumental for advancing our understanding of adaptive immune responses. However, while well-established solutions are accessible for the processing of single-cell transcriptomes, no streamlined pipelines are available for the comprehensive characterization of T-cell receptors. Here, we propose single-cell immune repertoires in Python (Scirpy), a scalable Python toolkit that provides simplified access to the analysis and visualization of immune repertoires from single cells and seamless integration with transcriptomic data.
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