Human γδ T cell Identification from Single-cell RNA Sequencing Datasets by Modular TCR Expression
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Human γδ T cell Identification from Single-cell RNA Sequencing Datasets by Modular TCR Expression. / Song, Zheng; Henze, Lara; Casar, Christian; Schwinge, Dorothee; Schramm, Christoph; Fuss, Johannes; Tan, Likai; Prinz, Immo.
In: J LEUKOCYTE BIOL, Vol. 114, No. 6, 24.11.2023, p. 630-638.Research output: SCORING: Contribution to journal › SCORING: Journal article › Research › peer-review
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TY - JOUR
T1 - Human γδ T cell Identification from Single-cell RNA Sequencing Datasets by Modular TCR Expression
AU - Song, Zheng
AU - Henze, Lara
AU - Casar, Christian
AU - Schwinge, Dorothee
AU - Schramm, Christoph
AU - Fuss, Johannes
AU - Tan, Likai
AU - Prinz, Immo
N1 - © The Author(s) 2023. Published by Oxford University Press on behalf of Society for Leukocyte Biology. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
PY - 2023/11/24
Y1 - 2023/11/24
N2 - Accurately identifying γδ T cells in large single-cell RNA sequencing (scRNA-seq) datasets without additional single-cell γδ T cell receptor sequencing (sc-γδTCR-seq) or CITE-seq (cellular indexing of transcriptomes and epitopes sequencing) data remains challenging. In this study, we developed a TCR module scoring strategy for human γδ T cell identification (i.e. based on modular gene expression of constant and variable TRA/TRB and TRD genes). We evaluated our method using 5' scRNA-seq datasets comprising both sc-αβTCR-seq and sc-γδTCR-seq as references and demonstrated that it can identify γδ T cells in scRNA-seq datasets with high sensitivity and accuracy. We observed a stable performance of this strategy across datasets from different tissues and different subtypes of γδ T cells. Thus, we propose this analysis method, based on TCR gene module scores, as a standardized tool for identifying and reanalyzing γδ T cells from 5'-end scRNA-seq datasets.
AB - Accurately identifying γδ T cells in large single-cell RNA sequencing (scRNA-seq) datasets without additional single-cell γδ T cell receptor sequencing (sc-γδTCR-seq) or CITE-seq (cellular indexing of transcriptomes and epitopes sequencing) data remains challenging. In this study, we developed a TCR module scoring strategy for human γδ T cell identification (i.e. based on modular gene expression of constant and variable TRA/TRB and TRD genes). We evaluated our method using 5' scRNA-seq datasets comprising both sc-αβTCR-seq and sc-γδTCR-seq as references and demonstrated that it can identify γδ T cells in scRNA-seq datasets with high sensitivity and accuracy. We observed a stable performance of this strategy across datasets from different tissues and different subtypes of γδ T cells. Thus, we propose this analysis method, based on TCR gene module scores, as a standardized tool for identifying and reanalyzing γδ T cells from 5'-end scRNA-seq datasets.
U2 - 10.1093/jleuko/qiad069
DO - 10.1093/jleuko/qiad069
M3 - SCORING: Journal article
C2 - 37437101
VL - 114
SP - 630
EP - 638
JO - J LEUKOCYTE BIOL
JF - J LEUKOCYTE BIOL
SN - 0741-5400
IS - 6
ER -