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EXPath工具——一个用于从高通量转录组数据中全面分析调控通路和共表达网络的系统。

EXPath tool-a system for comprehensively analyzing regulatory pathways and coexpression networks from high-throughput transcriptome data.

作者信息

Zheng Han-Qin, Wu Nai-Yun, Chow Chi-Nga, Tseng Kuan-Chieh, Chien Chia-Hung, Hung Yu-Cheng, Li Guan-Zhen, Chang Wen-Chi

机构信息

Institute of Tropical Plant Sciences, College of Biosciences and Biotechnology, National Cheng Kung University, Tainan 701, Taiwan.

出版信息

DNA Res. 2017 Aug 1;24(4):371-375. doi: 10.1093/dnares/dsx009.

DOI:10.1093/dnares/dsx009
PMID:28338930
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5737374/
Abstract

Next generation sequencing (NGS) has become the mainstream approach for monitoring gene expression levels in parallel with various experimental treatments. Unfortunately, there is no systematical webserver to comprehensively perform further analysis based on the huge amount of preliminary data that is obtained after finishing the process of gene annotation. Therefore, a user-friendly and effective system is required to mine important genes and regulatory pathways under specific conditions from high-throughput transcriptome data. EXPath Tool (available at: http://expathtool.itps.ncku.edu.tw/) was developed for the pathway annotation and comparative analysis of user-customized gene expression profiles derived from microarray or NGS platforms under various conditions to infer metabolic pathways for all organisms in the KEGG database. EXPath Tool contains several functions: access the gene expression patterns and the candidates of co-expression genes; dissect differentially expressed genes (DEGs) between two conditions (DEGs search), functional grouping with pathway and GO (Pathway/GO enrichment analysis), and correlation networks (co-expression analysis), and view the expression patterns of genes involved in specific pathways to infer the effects of the treatment. Additionally, the effectively of EXPath Tool has been performed by a case study on IAA-responsive genes. The results demonstrated that critical hub genes under IAA treatment could be efficiently identified.

摘要

下一代测序(NGS)已成为与各种实验处理并行监测基因表达水平的主流方法。不幸的是,没有系统的网络服务器可基于基因注释过程完成后获得的大量初步数据进行全面的进一步分析。因此,需要一个用户友好且有效的系统,从高通量转录组数据中挖掘特定条件下的重要基因和调控途径。EXPath工具(可在:http://expathtool.itps.ncku.edu.tw/获取)是为了对在各种条件下从微阵列或NGS平台获得的用户定制基因表达谱进行通路注释和比较分析而开发的,以推断KEGG数据库中所有生物的代谢途径。EXPath工具包含几个功能:访问基因表达模式和共表达基因的候选基因;剖析两种条件之间的差异表达基因(DEGs搜索)、通过通路和基因本体(GO)进行功能分组(通路/GO富集分析)以及相关网络(共表达分析),并查看参与特定通路的基因的表达模式以推断处理的效果。此外,通过对生长素(IAA)响应基因的案例研究验证了EXPath工具的有效性。结果表明,IAA处理下的关键枢纽基因能够被有效识别。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e6ab/5737374/4d0aeece95e7/dsx009f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e6ab/5737374/414b8463978f/dsx009f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e6ab/5737374/7f57988f6ca2/dsx009f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e6ab/5737374/4d0aeece95e7/dsx009f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e6ab/5737374/414b8463978f/dsx009f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e6ab/5737374/7f57988f6ca2/dsx009f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e6ab/5737374/4d0aeece95e7/dsx009f3.jpg

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