Systematic single-cell pathway analysis to characterize early T cell activation

JA Bibby; D Agarwal; T Freiwald; N Kunz; NS Merle; EE West; P Singh; A Larochelle; F Chinian; S Mukherjee; B Afzali; C Kemper; NR Zhang

doi:10.1016/j.celrep.2022.111697

Systematic single-cell pathway analysis to characterize early T cell activation

Standard

Systematic single-cell pathway analysis to characterize early T cell activation. / Bibby, JA; Agarwal, D; Freiwald, T; Kunz, N; Merle, NS; West, EE; Singh, P; Larochelle, A; Chinian, F; Mukherjee, S; Afzali, B; Kemper, C; Zhang, NR.

In: CELL REP, Vol. 41, No. 8, 111697, 22.11.2022, p. 111697.

Research output: SCORING: Contribution to journal › SCORING: Journal article › Research › peer-review

Harvard

Bibby, JA, Agarwal, D, Freiwald, T, Kunz, N, Merle, NS, West, EE, Singh, P, Larochelle, A, Chinian, F, Mukherjee, S, Afzali, B, Kemper, C & Zhang, NR 2022, 'Systematic single-cell pathway analysis to characterize early T cell activation', CELL REP, vol. 41, no. 8, 111697, pp. 111697. https://doi.org/10.1016/j.celrep.2022.111697

APA

Bibby, JA., Agarwal, D., Freiwald, T., Kunz, N., Merle, NS., West, EE., Singh, P., Larochelle, A., Chinian, F., Mukherjee, S., Afzali, B., Kemper, C., & Zhang, NR. (2022). Systematic single-cell pathway analysis to characterize early T cell activation. CELL REP, 41(8), 111697. [111697]. https://doi.org/10.1016/j.celrep.2022.111697

Vancouver

Bibby JA, Agarwal D, Freiwald T, Kunz N, Merle NS, West EE et al. Systematic single-cell pathway analysis to characterize early T cell activation. CELL REP. 2022 Nov 22;41(8):111697. 111697. https://doi.org/10.1016/j.celrep.2022.111697

Bibtex

@article{46e7ef2644e04c32a382c5ff83b8ba75,

title = "Systematic single-cell pathway analysis to characterize early T cell activation",

abstract = "Pathway analysis is a key analytical stage in the interpretation of omics data, providing a powerful method for detecting alterations in cellular processes. We recently developed a sensitive and distribution-free statistical framework for multisample distribution testing, which we implement here in the open-source R package single-cell pathway analysis (SCPA). We demonstrate the effectiveness of SCPA over commonly used methods, generate a scRNA-seq T cell dataset, and characterize pathway activity over early cellular activation. This reveals regulatory pathways in T cells, including an intrinsic type I interferon system regulating T cell survival and a reliance on arachidonic acid metabolism throughout T cell activation. A systems-level characterization of pathway activity in T cells across multiple tissues also identifies alpha-defensin expression as a hallmark of bone-marrow-derived T cells. Overall, this work provides a widely applicable tool for single-cell pathway analysis and highlights regulatory mechanisms of T cells.",

author = "JA Bibby and D Agarwal and T Freiwald and N Kunz and NS Merle and EE West and P Singh and A Larochelle and F Chinian and S Mukherjee and B Afzali and C Kemper and NR Zhang",

year = "2022",

month = nov,

day = "22",

doi = "10.1016/j.celrep.2022.111697",

language = "English",

volume = "41",

pages = "111697",

journal = "CELL REP",

issn = "2211-1247",

publisher = "Elsevier",

number = "8",

}

RIS

TY - JOUR

T1 - Systematic single-cell pathway analysis to characterize early T cell activation

AU - Bibby, JA

AU - Agarwal, D

AU - Freiwald, T

AU - Kunz, N

AU - Merle, NS

AU - West, EE

AU - Singh, P

AU - Larochelle, A

AU - Chinian, F

AU - Mukherjee, S

AU - Afzali, B

AU - Kemper, C

AU - Zhang, NR

PY - 2022/11/22

Y1 - 2022/11/22

N2 - Pathway analysis is a key analytical stage in the interpretation of omics data, providing a powerful method for detecting alterations in cellular processes. We recently developed a sensitive and distribution-free statistical framework for multisample distribution testing, which we implement here in the open-source R package single-cell pathway analysis (SCPA). We demonstrate the effectiveness of SCPA over commonly used methods, generate a scRNA-seq T cell dataset, and characterize pathway activity over early cellular activation. This reveals regulatory pathways in T cells, including an intrinsic type I interferon system regulating T cell survival and a reliance on arachidonic acid metabolism throughout T cell activation. A systems-level characterization of pathway activity in T cells across multiple tissues also identifies alpha-defensin expression as a hallmark of bone-marrow-derived T cells. Overall, this work provides a widely applicable tool for single-cell pathway analysis and highlights regulatory mechanisms of T cells.

AB - Pathway analysis is a key analytical stage in the interpretation of omics data, providing a powerful method for detecting alterations in cellular processes. We recently developed a sensitive and distribution-free statistical framework for multisample distribution testing, which we implement here in the open-source R package single-cell pathway analysis (SCPA). We demonstrate the effectiveness of SCPA over commonly used methods, generate a scRNA-seq T cell dataset, and characterize pathway activity over early cellular activation. This reveals regulatory pathways in T cells, including an intrinsic type I interferon system regulating T cell survival and a reliance on arachidonic acid metabolism throughout T cell activation. A systems-level characterization of pathway activity in T cells across multiple tissues also identifies alpha-defensin expression as a hallmark of bone-marrow-derived T cells. Overall, this work provides a widely applicable tool for single-cell pathway analysis and highlights regulatory mechanisms of T cells.

UR - http://europepmc.org/abstract/med/36417885

U2 - 10.1016/j.celrep.2022.111697

DO - 10.1016/j.celrep.2022.111697

M3 - SCORING: Journal article

C2 - 36417885

VL - 41

SP - 111697

JO - CELL REP

JF - CELL REP

SN - 2211-1247

IS - 8

M1 - 111697

ER -