EXPath tool—a system for comprehensively analyzing regulatory pathways and coexpression networks from high-throughput transcriptome data
| Autor: | Han Qin Zheng, Yu Cheng Hung, Wen Chi Chang, Kuan Chieh Tseng, Chia Hung Chien, Guan Zhen Li, Nai Yun Wu, Chi Nga Chow |
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| Jazyk: | angličtina |
| Rok vydání: | 2017 |
| Předmět: |
0301 basic medicine
Microarray Arabidopsis Computational biology Biology DNA sequencing Biological pathway Transcriptome 03 medical and health sciences Annotation User-Computer Interface Gene expression Databases Genetic Genetics Molecular Biology Gene co-expression network Indoleacetic Acids Sequence Analysis RNA High-Throughput Nucleotide Sequencing General Medicine Gene Annotation Full Papers 030104 developmental biology NGS Algorithms Software biological pathway |
| Zdroj: | DNA Research: An International Journal for Rapid Publication of Reports on Genes and Genomes |
| ISSN: | 1756-1663 1340-2838 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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