基于ssGSEA算法和ceRNA调控网络评价的脓毒症早期重要因素筛选

IF 1.7 4区 生物学 Q4 EVOLUTIONARY BIOLOGY Evolutionary Bioinformatics Pub Date : 2021-11-26 eCollection Date: 2021-01-01 DOI:10.1177/11769343211058463
Liou Huang, Chunrong Wu, Dan Xu, Yuhui Cui, Jianguo Tang
{"title":"基于ssGSEA算法和ceRNA调控网络评价的脓毒症早期重要因素筛选","authors":"Liou Huang,&nbsp;Chunrong Wu,&nbsp;Dan Xu,&nbsp;Yuhui Cui,&nbsp;Jianguo Tang","doi":"10.1177/11769343211058463","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Sepsis is a dysregulated host response to pathogens. Delay in sepsis diagnosis has become a primary cause of patient death. This study determines some factors to prevent septic shock in its early stage, contributing to the early treatment of sepsis.</p><p><strong>Methods: </strong>The sequencing data (RNA- and miRNA-sequencing) of patients with septic shock were obtained from the NCBI GEO database. After re-annotation, we obtained lncRNAs, miRNA, and mRNA information. Then, we evaluated the immune characteristics of the sample based on the ssGSEA algorithm. We used the WGCNA algorithm to obtain genes significantly related to immunity and screen for important related factors by constructing a ceRNA regulatory network.</p><p><strong>Result: </strong>After re-annotation, we obtained 1708 lncRNAs, 129 miRNAs, and 17 326 mRNAs. Also, through the ssGSEA algorithm, we obtained 5 important immune cells. Finally, we constructed a ceRNA regulation network associated with SS pathways.</p><p><strong>Conclusion: </strong>We identified 5 immune cells with significant changes in the early stage of septic shock. We also constructed a ceRNA network, which will help us explore the pathogenesis of septic shock.</p>","PeriodicalId":50472,"journal":{"name":"Evolutionary Bioinformatics","volume":"17 ","pages":"11769343211058463"},"PeriodicalIF":1.7000,"publicationDate":"2021-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/ac/ad/10.1177_11769343211058463.PMC8637398.pdf","citationCount":"20","resultStr":"{\"title\":\"Screening of Important Factors in the Early Sepsis Stage Based on the Evaluation of ssGSEA Algorithm and ceRNA Regulatory Network.\",\"authors\":\"Liou Huang,&nbsp;Chunrong Wu,&nbsp;Dan Xu,&nbsp;Yuhui Cui,&nbsp;Jianguo Tang\",\"doi\":\"10.1177/11769343211058463\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Sepsis is a dysregulated host response to pathogens. Delay in sepsis diagnosis has become a primary cause of patient death. This study determines some factors to prevent septic shock in its early stage, contributing to the early treatment of sepsis.</p><p><strong>Methods: </strong>The sequencing data (RNA- and miRNA-sequencing) of patients with septic shock were obtained from the NCBI GEO database. After re-annotation, we obtained lncRNAs, miRNA, and mRNA information. Then, we evaluated the immune characteristics of the sample based on the ssGSEA algorithm. We used the WGCNA algorithm to obtain genes significantly related to immunity and screen for important related factors by constructing a ceRNA regulatory network.</p><p><strong>Result: </strong>After re-annotation, we obtained 1708 lncRNAs, 129 miRNAs, and 17 326 mRNAs. Also, through the ssGSEA algorithm, we obtained 5 important immune cells. Finally, we constructed a ceRNA regulation network associated with SS pathways.</p><p><strong>Conclusion: </strong>We identified 5 immune cells with significant changes in the early stage of septic shock. We also constructed a ceRNA network, which will help us explore the pathogenesis of septic shock.</p>\",\"PeriodicalId\":50472,\"journal\":{\"name\":\"Evolutionary Bioinformatics\",\"volume\":\"17 \",\"pages\":\"11769343211058463\"},\"PeriodicalIF\":1.7000,\"publicationDate\":\"2021-11-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/ac/ad/10.1177_11769343211058463.PMC8637398.pdf\",\"citationCount\":\"20\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Evolutionary Bioinformatics\",\"FirstCategoryId\":\"99\",\"ListUrlMain\":\"https://doi.org/10.1177/11769343211058463\",\"RegionNum\":4,\"RegionCategory\":\"生物学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2021/1/1 0:00:00\",\"PubModel\":\"eCollection\",\"JCR\":\"Q4\",\"JCRName\":\"EVOLUTIONARY BIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Evolutionary Bioinformatics","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1177/11769343211058463","RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2021/1/1 0:00:00","PubModel":"eCollection","JCR":"Q4","JCRName":"EVOLUTIONARY BIOLOGY","Score":null,"Total":0}
引用次数: 20

摘要

背景:败血症是一种失调的宿主对病原体的反应。败血症诊断延误已成为患者死亡的主要原因。本研究确定了早期预防脓毒性休克的一些因素,有助于脓毒症的早期治疗。方法:从NCBI GEO数据库获取感染性休克患者的测序数据(RNA-和mirna -测序)。重新注释后,我们获得了lncRNAs、miRNA和mRNA的信息。然后,我们基于ssGSEA算法评估样本的免疫特性。我们通过构建ceRNA调控网络,利用WGCNA算法获取与免疫显著相关的基因,筛选重要的相关因子。结果:重新注释后,我们获得了1708个lncrna, 129个mirna和17 326个mrna。同时,通过ssGSEA算法,我们获得了5个重要的免疫细胞。最后,我们构建了与SS通路相关的ceRNA调控网络。结论:在脓毒性休克早期,我们发现5种免疫细胞发生了显著变化。我们还构建了ceRNA网络,这将有助于我们探索脓毒性休克的发病机制。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

摘要图片

摘要图片

摘要图片

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Screening of Important Factors in the Early Sepsis Stage Based on the Evaluation of ssGSEA Algorithm and ceRNA Regulatory Network.

Background: Sepsis is a dysregulated host response to pathogens. Delay in sepsis diagnosis has become a primary cause of patient death. This study determines some factors to prevent septic shock in its early stage, contributing to the early treatment of sepsis.

Methods: The sequencing data (RNA- and miRNA-sequencing) of patients with septic shock were obtained from the NCBI GEO database. After re-annotation, we obtained lncRNAs, miRNA, and mRNA information. Then, we evaluated the immune characteristics of the sample based on the ssGSEA algorithm. We used the WGCNA algorithm to obtain genes significantly related to immunity and screen for important related factors by constructing a ceRNA regulatory network.

Result: After re-annotation, we obtained 1708 lncRNAs, 129 miRNAs, and 17 326 mRNAs. Also, through the ssGSEA algorithm, we obtained 5 important immune cells. Finally, we constructed a ceRNA regulation network associated with SS pathways.

Conclusion: We identified 5 immune cells with significant changes in the early stage of septic shock. We also constructed a ceRNA network, which will help us explore the pathogenesis of septic shock.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Evolutionary Bioinformatics
Evolutionary Bioinformatics 生物-进化生物学
CiteScore
4.20
自引率
0.00%
发文量
25
审稿时长
12 months
期刊介绍: Evolutionary Bioinformatics is an open access, peer reviewed international journal focusing on evolutionary bioinformatics. The journal aims to support understanding of organismal form and function through use of molecular, genetic, genomic and proteomic data by giving due consideration to its evolutionary context.
期刊最新文献
In silico Characterization of a Hypothetical Protein (PBJ89160.1) from Neisseria meningitidis Exhibits a New Insight on Nutritional Virulence and Molecular Docking to Uncover a Therapeutic Target. Comparative Phylogenetic Analysis and Protein Prediction Reveal the Taxonomy and Diverse Distribution of Virulence Factors in Foodborne Clostridium Strains. An Effective Computational Method for Predicting Self-Interacting Proteins Based on VGGNet Convolutional Neural Network and Gray-Level Co-occurrence Matrix. Comprehensive Profiling of Transcriptome and m6A Epitranscriptome Uncovers the Neurotoxic Effects of Yunaconitine on HT22 Cells. Label Transfer for Drug Disease Association in Three Meta-Paths
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1