| Autor: |
Jack A. Bibby, Divyansh Agarwal, Tilo Freiwald, Natalia Kunz, Nicolas S. Merle, Erin E. West, Andre Larochelle, Fariba Chinian, Somabha Mukherjee, Behdad Afzali, Claudia Kemper, Nancy R. Zhang |
| Rok vydání: |
2022 |
| Zdroj: |
SSRN Electronic Journal. |
| ISSN: |
1556-5068 |
| Popis: |
SummaryNext generation sequencing technologies have revolutionized the study of T cell biology, capturing previously unrecognized diversity in cellular states and functions. Pathway analysis is a key analytical stage in the interpretation of such transcriptomic data, providing a powerful method for detecting alterations in important biological processes. Current pathway analysis tools are built on models developed for bulk-RNA sequencing, limiting their effectiveness when applied to more complex single cell RNA-sequencing (scRNA-seq) datasets. 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). After demonstrating the effectiveness of SCPA over commonly used methods, we generate a scRNA-seq T cell dataset and characterize pathway activity over early cellular activation and between T cell populations. This revealed unexpected regulatory pathways in T cells, such as 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 human tissues also revealed alpha defensin expression as a hallmark of bone marrow derived T cells. Overall, our work here provides a widely applicable tool for single cell pathway analysis, and highlights unexpected regulatory mechanisms of T cells using a novel T cell dataset. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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