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Blood transcriptome analysis of patients with uncomplicated bacterial infection and sepsis
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...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7913415/ https://www.ncbi.nlm.nih.gov/pubmed/33640018 http://dx.doi.org/10.1186/s13104-021-05488-w |
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author | Herwanto, Velma Tang, Benjamin Wang, Ya Shojaei, Maryam Nalos, Marek Shetty, Amith Lai, Kevin McLean, Anthony S. Schughart, Klaus |
author_facet | Herwanto, Velma Tang, Benjamin Wang, Ya Shojaei, Maryam Nalos, Marek Shetty, Amith Lai, Kevin McLean, Anthony S. Schughart, Klaus |
author_sort | Herwanto, Velma |
collection | PubMed |
description | 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 log(2) 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. |
format | Online Article Text |
id | pubmed-7913415 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-79134152021-03-02 Blood transcriptome analysis of patients with uncomplicated bacterial infection and sepsis Herwanto, Velma Tang, Benjamin Wang, Ya Shojaei, Maryam Nalos, Marek Shetty, Amith Lai, Kevin McLean, Anthony S. Schughart, Klaus BMC Res Notes Data Note 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 log(2) 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. BioMed Central 2021-02-27 /pmc/articles/PMC7913415/ /pubmed/33640018 http://dx.doi.org/10.1186/s13104-021-05488-w Text en © The Author(s) 2021 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Data Note Herwanto, Velma Tang, Benjamin Wang, Ya Shojaei, Maryam Nalos, Marek Shetty, Amith Lai, Kevin McLean, Anthony S. Schughart, Klaus Blood transcriptome analysis of patients with uncomplicated bacterial infection and sepsis |
title | Blood transcriptome analysis of patients with uncomplicated bacterial infection and sepsis |
title_full | Blood transcriptome analysis of patients with uncomplicated bacterial infection and sepsis |
title_fullStr | Blood transcriptome analysis of patients with uncomplicated bacterial infection and sepsis |
title_full_unstemmed | Blood transcriptome analysis of patients with uncomplicated bacterial infection and sepsis |
title_short | Blood transcriptome analysis of patients with uncomplicated bacterial infection and sepsis |
title_sort | blood transcriptome analysis of patients with uncomplicated bacterial infection and sepsis |
topic | Data Note |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7913415/ https://www.ncbi.nlm.nih.gov/pubmed/33640018 http://dx.doi.org/10.1186/s13104-021-05488-w |
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