Department of Electrical Engineering, National Cheng Kung University, Tainan 70101, Taiwan.
Gene. 2013 Apr 10;518(1):26-34. doi: 10.1016/j.gene.2012.11.089. Epub 2012 Dec 22.
The advance of high-throughput experimental technologies generates many gene sets with different biological meanings, where many important insights can only be extracted by identifying the biological (regulatory/functional) features that are distinct between different gene sets (e.g. essential vs. non-essential genes, TATA box-containing vs. TATA box-less genes, induced vs. repressed genes under certain biological conditions). Although many servers have been developed to identify enriched features in a gene set, most of them were designed to analyze one gene set at a time but cannot compare two gene sets. Moreover, the features used in existing servers were mainly focused on functional annotations (GO terms), pathways, transcription factor binding sites (TFBSs) and/or protein-protein interactions (PPIs). In yeast, various important regulatory features, including promoter bendability, nucleosome occupancy, 5'-UTR length, and TF-gene regulation evidence, are available but have not been used in any enrichment analysis servers. This motivates us to develop the Yeast Genes Analyzer (YGA), a web server that simultaneously analyzes various biological (regulatory/functional) features of two gene sets and performs statistical tests to identify the distinct features between them. Many well-studied gene sets such as essential, stress-response, TATA box-containing and cell cycle genes were pre-compiled in YGA for users, if they have only one gene set, to compare with. In comparison with the existing enrichment analysis servers, YGA tests more comprehensive regulatory features (e.g. promoter bendability, nucleosome occupancy, 5'-UTR length, experimental evidence of TF-gene binding and TF-gene regulation) and functional features (e.g. PPI, GO terms, pathways and functional groups of genes, including essential/non-essential genes, stress-induced/-repressed genes, TATA box-containing/-less genes, occupied/depleted proximal-nucleosome genes and cell cycle genes). Furthermore, YGA uses various statistical tests to provide objective comparison measures. The two major contributions of YGA, comprehensive features and statistical comparison, help to mine important information that cannot be obtained from other servers. The sophisticated analysis tools of YGA can identify distinct biological features between two gene sets, which help biologists to form new hypotheses about the underlying biological mechanisms responsible for the observed difference between these two gene sets. YGA can be accessed from the following web pages: http://cosbi.ee.ncku.edu.tw/yga/ and http://yga.ee.ncku.edu.tw/.
高通量实验技术的进步产生了许多具有不同生物学意义的基因集,其中许多重要的见解只能通过识别不同基因集之间具有独特的生物学(调节/功能)特征来提取(例如,必需基因与非必需基因、含 TATA 框基因与不含 TATA 框基因、在特定生物条件下诱导基因与抑制基因)。虽然已经开发了许多服务器来识别基因集中的富集特征,但大多数服务器都是设计用于一次分析一个基因集,而不能比较两个基因集。此外,现有服务器中使用的特征主要集中在功能注释(GO 术语)、途径、转录因子结合位点(TFBS)和/或蛋白质-蛋白质相互作用(PPI)上。在酵母中,各种重要的调节特征,包括启动子弯曲性、核小体占有率、5'-UTR 长度和 TF-基因调控证据,都是可用的,但尚未在任何富集分析服务器中使用。这促使我们开发了 Yeast Genes Analyzer(YGA),这是一个网络服务器,可以同时分析两个基因集的各种生物学(调节/功能)特征,并进行统计检验以识别它们之间的独特特征。许多经过充分研究的基因集,如必需基因、应激反应基因、含 TATA 框基因和细胞周期基因,已预先编译在 YGA 中供用户使用,如果他们只有一个基因集,则可以与其他基因集进行比较。与现有的富集分析服务器相比,YGA 测试更全面的调节特征(例如启动子弯曲性、核小体占有率、5'-UTR 长度、TF-基因结合和 TF-基因调控的实验证据)和功能特征(例如 PPI、GO 术语、途径和基因的功能组,包括必需/非必需基因、应激诱导/抑制基因、含 TATA 框基因/不含 TATA 框基因、占用/耗尽近核小体基因和细胞周期基因)。此外,YGA 使用各种统计检验提供客观的比较措施。YGA 的两个主要贡献,全面的特征和统计比较,有助于挖掘从其他服务器无法获得的重要信息。YGA 的复杂分析工具可以识别两个基因集之间独特的生物学特征,这有助于生物学家形成关于导致这两个基因集之间观察到的差异的潜在生物学机制的新假设。YGA 可以从以下网页访问:http://cosbi.ee.ncku.edu.tw/yga/ 和 http://yga.ee.ncku.edu.tw/。