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Differential co-expression analysis of venous thromboembolism based on gene expression profile data

The aim of the present study was to screen differentially co-expressed genes and the involved transcription factors (TFs) and microRNAs (miRNAs) in venous thromboembolism (VTE). Microarray data of GSE19151 were downloaded from Gene Expression Omnibus, including 70 patients with VTE and 63 healthy co...

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Autores principales: MING, ZHIBING, DING, WENBIN, YUAN, RUIFAN, JIN, JIE, LI, XIAOQIANG
Formato: Online Artículo Texto
Lenguaje:English
Publicado: D.A. Spandidos 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4887825/
https://www.ncbi.nlm.nih.gov/pubmed/27284300
http://dx.doi.org/10.3892/etm.2016.3208
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author MING, ZHIBING
DING, WENBIN
YUAN, RUIFAN
JIN, JIE
LI, XIAOQIANG
author_facet MING, ZHIBING
DING, WENBIN
YUAN, RUIFAN
JIN, JIE
LI, XIAOQIANG
author_sort MING, ZHIBING
collection PubMed
description The aim of the present study was to screen differentially co-expressed genes and the involved transcription factors (TFs) and microRNAs (miRNAs) in venous thromboembolism (VTE). Microarray data of GSE19151 were downloaded from Gene Expression Omnibus, including 70 patients with VTE and 63 healthy controls. Principal component analysis (PCA) was performed using R software. Differential co-expression analysis was performed using R, followed by screening of modules using Cytoscape. Functional annotation was performed using Database for Annotation, Visualization, and Integrated Discovery. Moreover, Fisher test was used to screen key TFs and miRNAs for the modules. PCA revealed the disease and healthy samples could not be distinguished at the gene expression level. A total of 4,796 upregulated differentially co-expressed genes (e.g. zinc finger protein 264, electron-transfer-flavoprotein, beta polypeptide and Janus kinase 2) and 3,629 downregulated differentially co-expressed genes (e.g. adenylate cyclase 7 and single-stranded DNA binding protein 2) were identified, which were further mined to obtain 17 and eight modules separately. Functional annotation revealed that the largest upregulated module was primarily associated with acetylation and the largest downregulated module was mainly involved in mitochondrion. Moreover, 48 TFs and 62 miRNA families were screened for the 17 upregulated modules, such as E2F transcription factor 4, miR-30 and miR-135 regulating the largest module. Conversely, 35 TFs and 18 miRNA families were identified for the 8 downregulated modules, including mitochondrial ribosomal protein S12 and miR-23 regulating the largest module. Differentially co-expressed genes regulated by TFs and miRNAs may jointly contribute to the abnormal acetylation and mitochondrion presentation in the progression of VTE.
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spelling pubmed-48878252016-06-09 Differential co-expression analysis of venous thromboembolism based on gene expression profile data MING, ZHIBING DING, WENBIN YUAN, RUIFAN JIN, JIE LI, XIAOQIANG Exp Ther Med Articles The aim of the present study was to screen differentially co-expressed genes and the involved transcription factors (TFs) and microRNAs (miRNAs) in venous thromboembolism (VTE). Microarray data of GSE19151 were downloaded from Gene Expression Omnibus, including 70 patients with VTE and 63 healthy controls. Principal component analysis (PCA) was performed using R software. Differential co-expression analysis was performed using R, followed by screening of modules using Cytoscape. Functional annotation was performed using Database for Annotation, Visualization, and Integrated Discovery. Moreover, Fisher test was used to screen key TFs and miRNAs for the modules. PCA revealed the disease and healthy samples could not be distinguished at the gene expression level. A total of 4,796 upregulated differentially co-expressed genes (e.g. zinc finger protein 264, electron-transfer-flavoprotein, beta polypeptide and Janus kinase 2) and 3,629 downregulated differentially co-expressed genes (e.g. adenylate cyclase 7 and single-stranded DNA binding protein 2) were identified, which were further mined to obtain 17 and eight modules separately. Functional annotation revealed that the largest upregulated module was primarily associated with acetylation and the largest downregulated module was mainly involved in mitochondrion. Moreover, 48 TFs and 62 miRNA families were screened for the 17 upregulated modules, such as E2F transcription factor 4, miR-30 and miR-135 regulating the largest module. Conversely, 35 TFs and 18 miRNA families were identified for the 8 downregulated modules, including mitochondrial ribosomal protein S12 and miR-23 regulating the largest module. Differentially co-expressed genes regulated by TFs and miRNAs may jointly contribute to the abnormal acetylation and mitochondrion presentation in the progression of VTE. D.A. Spandidos 2016-06 2016-03-30 /pmc/articles/PMC4887825/ /pubmed/27284300 http://dx.doi.org/10.3892/etm.2016.3208 Text en Copyright: © Ming et al. This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License (https://creativecommons.org/licenses/by-nc-nd/4.0/) , which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.
spellingShingle Articles
MING, ZHIBING
DING, WENBIN
YUAN, RUIFAN
JIN, JIE
LI, XIAOQIANG
Differential co-expression analysis of venous thromboembolism based on gene expression profile data
title Differential co-expression analysis of venous thromboembolism based on gene expression profile data
title_full Differential co-expression analysis of venous thromboembolism based on gene expression profile data
title_fullStr Differential co-expression analysis of venous thromboembolism based on gene expression profile data
title_full_unstemmed Differential co-expression analysis of venous thromboembolism based on gene expression profile data
title_short Differential co-expression analysis of venous thromboembolism based on gene expression profile data
title_sort differential co-expression analysis of venous thromboembolism based on gene expression profile data
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4887825/
https://www.ncbi.nlm.nih.gov/pubmed/27284300
http://dx.doi.org/10.3892/etm.2016.3208
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