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{"title":"Identifying Significantly Impacted Pathways and Putative Mechanisms with iPathwayGuide","authors":"Sidra Ahsan, Sorin Drăghici","doi":"10.1002/cpbi.24","DOIUrl":null,"url":null,"abstract":"<p>iPathwayGuide is a gene expression analysis tool that provides biological context and inferences from data generated by high-throughput sequencing. iPathwayGuide utilizes a systems biology approach to identify significantly impacted signaling pathways, Gene Ontology terms, disease processes, predicted microRNAs, and putative mechanisms based on the given differential expression signature. By using a novel analytical approach called Impact Analysis, iPathwayGuide considers the role, position, and relationships of each gene within a pathway, which results in a significant reduction in false positives, as well as a better ability to identify the truly impacted pathways and putative mechanisms that can explain all measured gene expression changes. It is a Web-based, user-friendly, interactive tool that does not require prior training in bioinformatics. The protocols in this unit describe how to use iPathwayGuide to analyze a single contrast between two phenotypes (any number of samples), and provide guidance on how to interpret the results obtained from iPathwayGuide. Even though iPathwayGuide has powerful meta-analysis capabilities, these are not covered in this unit. © 2017 by John Wiley & Sons, Inc.</p>","PeriodicalId":10958,"journal":{"name":"Current protocols in bioinformatics","volume":"57 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2017-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1002/cpbi.24","citationCount":"61","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Current protocols in bioinformatics","FirstCategoryId":"1085","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/cpbi.24","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"Biochemistry, Genetics and Molecular Biology","Score":null,"Total":0}
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Abstract
iPathwayGuide is a gene expression analysis tool that provides biological context and inferences from data generated by high-throughput sequencing. iPathwayGuide utilizes a systems biology approach to identify significantly impacted signaling pathways, Gene Ontology terms, disease processes, predicted microRNAs, and putative mechanisms based on the given differential expression signature. By using a novel analytical approach called Impact Analysis, iPathwayGuide considers the role, position, and relationships of each gene within a pathway, which results in a significant reduction in false positives, as well as a better ability to identify the truly impacted pathways and putative mechanisms that can explain all measured gene expression changes. It is a Web-based, user-friendly, interactive tool that does not require prior training in bioinformatics. The protocols in this unit describe how to use iPathwayGuide to analyze a single contrast between two phenotypes (any number of samples), and provide guidance on how to interpret the results obtained from iPathwayGuide. Even though iPathwayGuide has powerful meta-analysis capabilities, these are not covered in this unit. © 2017 by John Wiley & Sons, Inc.
使用iPathwayGuide识别显著受影响的通路和推测的机制
iPathwayGuide是一种基因表达分析工具,可从高通量测序产生的数据中提供生物学背景和推断。iPathwayGuide利用系统生物学方法识别显著受影响的信号通路、基因本体术语、疾病过程、预测的microrna和基于给定差异表达特征的推测机制。通过使用一种称为影响分析的新型分析方法,iPathwayGuide考虑了途径中每个基因的作用、位置和关系,从而大大减少了假阳性,以及更好地识别真正受影响的途径和可以解释所有测量基因表达变化的假定机制的能力。它是一个基于网络的、用户友好的交互式工具,不需要事先接受生物信息学方面的培训。本单元的协议描述了如何使用iPathwayGuide来分析两种表型(任意数量的样本)之间的单个对比,并提供了如何解释从iPathwayGuide获得的结果的指导。尽管iPathwayGuide具有强大的元分析功能,但本单元并未涉及这些功能。©2017 by John Wiley &儿子,Inc。
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