SC2sepsis: sepsis single-cell whole gene expression database.

Abstract

Sepsis, one of the major challenges in the intensive care unit, is characterized by complex host immune status. Improved understandings of the phenotypic changes of immune cells during sepsis and the driving molecular mechanisms are critical to the elucidation of sepsis pathogenesis. Single-cell RNA sequencing (scRNA-seq), which interprets transcriptome at a single-cell resolution, serves as a useful tool to uncover disease-related gene expression signatures of different cell populations in various diseases. It has also been applied to studies on sepsis immunopathological mechanisms. Due to the fact that most sepsis-related studies utilizing scRNA-seq have very small sample sizes and there is a lack of an scRNA-seq database for sepsis, we developed Sepsis Single-cell Whole Gene Expression Database Website (SC2sepsis) (http://www.rjh-sc2sepsis.com/), integrating scRNA-seq datasets of human peripheral blood mononuclear cells from 45 septic patients and 26 healthy controls, with a total amount of 232 226 cells. SC2sepsis is a comprehensive resource database with two major features: (i) retrieval of 1988 differentially expressed genes between pathological and healthy conditions and (ii) automatic cell-type annotation, which is expected to facilitate researchers to gain more insights into the immune dysregulation of sepsis.

DATABASE URL:

http://www.rjh-sc2sepsis.com/.

• Authors: Yinjiaozhi Li, Ruoming Tan, Yang Chen, Zhaojun Liu, Erzhen Chen, Tingting Pan, Hongping Qu
• Journal: Database : the journal of biological databases and curation (Database (Oxford)) Vol. 2022 (08 18 2022) ISSN: 1758-0463 [Electronic] England
• PMID: 35980286 (Publication Type: Journal Article, Research Support, Non-U.S. Gov't)
• Copyright: © The Author(s) 2022. Published by Oxford University Press.

Topics

• Gene Expression Profiling
• High-Throughput Nucleotide Sequencing
• Humans
• Leukocytes, Mononuclear
• Sepsis (genetics)
• Sequence Analysis, RNA
• Single-Cell Analysis
• Software
• Transcriptome (genetics)