Bock Christoph, Von Kuster Greg, Halachev Konstantin, Taylor James, Nekrutenko Anton, Lengauer Thomas
Max-Planck-Institut für Informatik, Saarbrücken, Germany.
Methods Mol Biol. 2010;628:275-96. doi: 10.1007/978-1-60327-367-1_15.
Modern life sciences are becoming increasingly data intensive, posing a significant challenge for most researchers and shifting the bottleneck of scientific discovery from data generation to data analysis. As a result, progress in genome research is increasingly impeded by bioinformatic hurdles. A new generation of powerful and easy-to-use genome analysis tools has been developed to address this issue, enabling biologists to perform complex bioinformatic analyses online - without having to learn a programming language or downloading and manually processing large datasets. In this tutorial paper, we describe the use of EpiGRAPH (http://epigraph.mpi-inf.mpg.de/) and Galaxy (http://galaxyproject.org/) for genome and epigenome analysis, and we illustrate how these two web services work together to identify epigenetic modifications that are characteristics of highly polymorphic (SNP-rich) promoters. This paper is supplemented with video tutorials (http://tinyurl.com/yc5xkqq), which provide a step-by-step guide through each example analysis.
现代生命科学的数据量日益增大,这给大多数研究人员带来了巨大挑战,并将科学发现的瓶颈从数据生成转移到了数据分析上。因此,基因组研究的进展越来越受到生物信息学障碍的阻碍。为了解决这个问题,新一代强大且易于使用的基因组分析工具应运而生,使生物学家能够在线进行复杂的生物信息学分析——无需学习编程语言,也无需下载和手动处理大型数据集。在本教程论文中,我们描述了如何使用EpiGRAPH(http://epigraph.mpi-inf.mpg.de/)和Galaxy(http://galaxyproject.org/)进行基因组和表观基因组分析,并说明了这两个网络服务如何协同工作以识别高度多态性(富含单核苷酸多态性,SNP)启动子所特有的表观遗传修饰。本文还配有视频教程(http://tinyurl.com/yc5xkqq),为每个示例分析提供了逐步指导。