Zogopoulos Vasileios L, Saxami Georgia, Malatras Apostolos, Angelopoulou Antonia, Jen Chih-Hung, Duddy William J, Daras Gerasimos, Hatzopoulos Polydefkis, Westhead David R, Michalopoulos Ioannis
Centre of Systems Biology, Biomedical Research Foundation, Academy of Athens, Athens 11527, Greece.
Center for Research in Myology, Sorbonne Université, Paris 75013, France.
iScience. 2021 Jul 10;24(8):102848. doi: 10.1016/j.isci.2021.102848. eCollection 2021 Aug 20.
Gene coexpression analysis refers to the discovery of sets of genes which exhibit similar expression patterns across multiple transcriptomic data sets, such as microarray experiment data of public repositories. Coexpression Tool (ACT), a gene coexpression analysis web tool for , identifies genes which are correlated to a driver gene. Primary microarray data from ATH1 Affymetrix platform were processed with Single-Channel Array Normalization algorithm and combined to produce a coexpression tree which contains ∼21,000 genes. ACT was developed to present subclades of coexpressed genes, as well as to perform gene set enrichment analysis, being unique in revealing enriched transcription factors targeting coexpressed genes. ACT offers a simple and user-friendly interface producing working hypotheses which can be experimentally verified for the discovery of gene partnership, pathway membership, and transcriptional regulation. ACT analyses have been successful in identifying not only genes with coordinated ubiquitous expressions but also genes with tissue-specific expressions.
基因共表达分析是指发现一组在多个转录组数据集中呈现相似表达模式的基因,比如公共数据库的微阵列实验数据。共表达工具(ACT)是一款用于基因共表达分析的网络工具,它能识别与驱动基因相关的基因。来自Affymetrix ATH1平台的原始微阵列数据采用单通道阵列归一化算法进行处理,并合并生成一棵包含约21,000个基因的共表达树。ACT的开发目的是展示共表达基因的亚分支,以及进行基因集富集分析,其独特之处在于能够揭示靶向共表达基因的富集转录因子。ACT提供了一个简单且用户友好的界面,可生成工作假设,这些假设可通过实验验证,以发现基因伙伴关系、通路成员关系和转录调控。ACT分析不仅成功识别出具有协调普遍表达的基因,还识别出具有组织特异性表达的基因。