Unknown

Dataset Information

0

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.

SUBMITTER: Bibby JA 

PROVIDER: S-EPMC10704209 | biostudies-literature | 2022 Nov

REPOSITORIES: biostudies-literature

altmetric image

Publications


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 activi  ...[more]

Similar Datasets

2022-09-01 | GSE212270 | GEO
| PRJNA874734 | ENA
| S-EPMC3615553 | biostudies-literature
| S-EPMC5798330 | biostudies-literature
2012-08-08 | E-GEOD-34550 | biostudies-arrayexpress
| EGAS00001003479 | EGA
2012-08-08 | GSE34550 | GEO
2018-01-01 | GSE69581 | GEO
| S-EPMC9869179 | biostudies-literature
| S-EPMC2858074 | biostudies-literature