Dataset Information

Microarray data analysis to identify differentially expressed genes and biological pathways associated with asthma.

ABSTRACT: The present study aimed to identify differentially expressed genes (DEGs) and biological processes (BPs) associated with asthma. DEGs between allergic asthma and healthy controls were screened from GSE15823. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses were performed using Database for Annotation, Visualization and Integrated Discovery. A protein-protein interaction network was constructed, followed by module mining and functional analysis. Additionally, GSE41649 was downloaded to validate the reliability of the results. In GSE41649, DEGs were identified and compared with key DEGs identified in GSE15823. A total of 43 upregulated and 275 downregulated DEGs were obtained from GSE15823. Upregulated DEGs, such as nitric oxide synthase 2 (NOS2), were enriched in BPs related to oxidation reduction. Downregulated DEGs, such as chemokine (C-C motif) ligand 19 (CCL21) and Cys-X-Cys ligand (CXCL9), were enriched in immune response-related BPs. Protein tyrosine phosphatase receptor type C (PTPRC), CCL21, and CXCL9 were identified as hub genes. The DEGs in module 1 were significantly involved in the chemokine signaling pathway (P<0.05). The expression of the key genes obtained in GSE15823 demonstrated the same variation directions in the two datasets. The immune response, oxidants and nitric oxide metabolic pathways may have important roles in the progression of asthma. DEGs of PTPRC, CCL21, CXCL9 and NOS2 may be the potential targets for asthma diagnosis and treatment.

SUBMITTER: Qi S

PROVIDER: S-EPMC6122392 | biostudies-literature | 2018 Sep

REPOSITORIES: biostudies-literature

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Microarray data analysis to identify differentially expressed genes and biological pathways associated with asthma.

Qi Shanshan S Liu Guanghui G Dong Xiang X Huang Nan N Li Wenjing W Chen Hao H

Experimental and therapeutic medicine 20180628 3

The present study aimed to identify differentially expressed genes (DEGs) and biological processes (BPs) associated with asthma. DEGs between allergic asthma and healthy controls were screened from GSE15823. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses were performed using Database for Annotation, Visualization and Integrated Discovery. A protein-protein interaction network was constructed, followed by module mining and functional analysis. Additionally, ...[more]

PMID: 30186379

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Project description:BackgroundThere has been a dramatic increase in the amount of quantitative data derived from the measurement of changes at different levels of biological complexity during the post-genomic era. However, there are a number of issues associated with the use of computational tools employed for the analysis of such data. For example, computational tools such as R and MATLAB require prior knowledge of their programming languages in order to implement statistical analyses on data. Combining two or more tools in an analysis may also be problematic since data may have to be manually copied and pasted between separate user interfaces for each tool. Furthermore, this transfer of data may require a reconciliation step in order for there to be interoperability between computational tools.ResultsDevelopments in the Taverna workflow system have enabled pipelines to be constructed and enacted for generic and ad hoc analyses of quantitative data. Here, we present an example of such a workflow involving the statistical identification of differentially-expressed genes from microarray data followed by the annotation of their relationships to cellular processes. This workflow makes use of customised maxdBrowse web services, a system that allows Taverna to query and retrieve gene expression data from the maxdLoad2 microarray database. These data are then analysed by R to identify differentially-expressed genes using the Taverna RShell processor which has been developed for invoking this tool when it has been deployed as a service using the RServe library. In addition, the workflow uses Beanshell scripts to reconcile mismatches of data between services as well as to implement a form of user interaction for selecting subsets of microarray data for analysis as part of the workflow execution. A new plugin system in the Taverna software architecture is demonstrated by the use of renderers for displaying PDF files and CSV formatted data within the Taverna workbench.ConclusionTaverna can be used by data analysis experts as a generic tool for composing ad hoc analyses of quantitative data by combining the use of scripts written in the R programming language with tools exposed as services in workflows. When these workflows are shared with colleagues and the wider scientific community, they provide an approach for other scientists wanting to use tools such as R without having to learn the corresponding programming language to analyse their own data.

Dataset Information

Microarray data analysis to identify differentially expressed genes and biological pathways associated with asthma.

Publications

Microarray data analysis to identify differentially expressed genes and biological pathways associated with asthma.

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