Ewha Global Top5 Research Program, Ewha Womans University, 52 Ewhayeodae-gil, Seodaemun-gu, Seoul 120-750, Korea.
BMC Bioinformatics. 2014 Jan 14;15:13. doi: 10.1186/1471-2105-15-13.
Gene set analysis (GSA) is useful in deducing biological significance of gene lists using a priori defined gene sets such as gene ontology (GO) or pathways. Phenotypic annotation is sparse for human genes, but is far more abundant for other model organisms such as mouse, fly, and worm. Often, GSA needs to be done highly interactively by combining or modifying gene lists or inspecting gene-gene interactions in a molecular network.
We developed gsGator, a web-based platform for functional interpretation of gene sets with useful features such as cross-species GSA, simultaneous analysis of multiple gene sets, and a fully integrated network viewer for visualizing both GSA results and molecular networks. An extensive set of gene annotation information is amassed including GO & pathways, genomic annotations, protein-protein interaction, transcription factor-target (TF-target), miRNA targeting, and phenotype information for various model organisms. By combining the functionalities of Set Creator, Set Operator and Network Navigator, user can perform highly flexible and interactive GSA by creating a new gene list by any combination of existing gene sets (intersection, union and difference) or expanding genes interactively along the molecular networks such as protein-protein interaction and TF-target. We also demonstrate the utility of our interactive and cross-species GSA implemented in gsGator by several usage examples for interpreting genome-wide association study (GWAS) results. gsGator is freely available at http://gsGator.ewha.ac.kr.
Interactive and cross-species GSA in gsGator greatly extends the scope and utility of GSA, leading to novel insights via conserved functional gene modules across different species.
基因集分析(GSA)在使用先验定义的基因集(如基因本体论(GO)或途径)推断基因列表的生物学意义方面非常有用。人类基因的表型注释很少,但对于其他模式生物(如鼠、蝇和线虫)则要丰富得多。通常,GSA 需要通过组合或修改基因列表或在分子网络中检查基因-基因相互作用来高度交互地进行。
我们开发了 gsGator,这是一个基于网络的基因集功能解释平台,具有跨物种 GSA、同时分析多个基因集以及用于可视化 GSA 结果和分子网络的完全集成网络查看器等有用功能。收集了广泛的基因注释信息,包括 GO 和途径、基因组注释、蛋白质-蛋白质相互作用、转录因子-靶(TF-靶)、miRNA 靶向以及各种模式生物的表型信息。通过组合 Set Creator、Set Operator 和 Network Navigator 的功能,用户可以通过任何现有基因集(交集、并集和差集)的组合创建新的基因列表,或者沿着分子网络(如蛋白质-蛋白质相互作用和 TF-靶)交互式扩展基因,从而执行高度灵活和交互的 GSA。我们还通过在 gsGator 中实现的交互式和跨物种 GSA 的几个使用示例来展示其对全基因组关联研究(GWAS)结果进行解释的实用性。gsGator 可在 http://gsGator.ewha.ac.kr 免费获得。
gsGator 中的交互式和跨物种 GSA 大大扩展了 GSA 的范围和实用性,通过不同物种之间保守的功能基因模块带来了新的见解。