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Blood transcriptome analysis of patients with uncomplicated bacterial infection and sepsis
- Source :
- BMC Research Notes, Vol 14, Iss 1, Pp 1-3 (2021), BMC research notes, England, BMC Research Notes
- Publication Year :
- 2021
- Publisher :
- BMC, 2021.
-
Abstract
- Objectives Hospitalized patients who presented within the last 24 h with a bacterial infection were recruited. Participants were assigned into sepsis and uncomplicated infection groups. In addition, healthy volunteers were recruited as controls. RNA was prepared from whole blood, depleted from beta-globin mRNA and sequenced. This dataset represents a highly valuable resource to better understand the biology of sepsis and to identify biomarkers for severe sepsis in humans. Data description The data presented here consists of raw and processed transcriptome data obtained by next generation RNA sequencing from 105 peripheral blood samples from patients with uncomplicated infections, patients who developed sepsis, septic shock patients, and healthy controls. It is provided as raw sequenced reads and as normalized log2 transformed relative expression levels. This data will allow performing detailed analyses of gene expression changes between uncomplicated infections and sepsis patients, such as identification of differentially expressed genes, co-regulated modules as well as pathway activation studies.
- Subjects :
- 0301 basic medicine
Hospitalized patients
Whole blood transcriptome
lcsh:Medicine
Data Note
General Biochemistry, Genetics and Molecular Biology
Sepsis
Transcriptome
03 medical and health sciences
0302 clinical medicine
Gene expression
Medicine
Humans
030212 general & internal medicine
lcsh:Science (General)
lcsh:QH301-705.5
Whole blood
Messenger RNA
business.industry
Septic shock
Gene Expression Profiling
lcsh:R
RNA
General Medicine
Bacterial Infections
Uncomplicated infection
medicine.disease
030104 developmental biology
lcsh:Biology (General)
Case-Control Studies
Immunology
business
lcsh:Q1-390
Subjects
Details
- Language :
- English
- ISSN :
- 17560500
- Volume :
- 14
- Issue :
- 1
- Database :
- OpenAIRE
- Journal :
- BMC Research Notes
- Accession number :
- edsair.doi.dedup.....1cf438e7188d5e779be4643e496ed578