Albert Istvan, Wachi Shinichiro, Jiang Cizhong, Pugh B Franklin
Huck Institutes for the Life Sciences, Pennsylvania State University, University Park, Pennsylvania, 16802, USA.
Bioinformatics. 2008 May 15;24(10):1305-6. doi: 10.1093/bioinformatics/btn119. Epub 2008 Apr 3.
High-throughput 'ChIP-chip' and 'ChIP-seq' methodologies generate sufficiently large data sets that analysis poses significant informatics challenges, particularly for research groups with modest computational support. To address this challenge, we devised a software platform for storing, analyzing and visualizing high resolution genome-wide binding data. GeneTrack automates several steps of a typical data processing pipeline, including smoothing and peak detection, and facilitates dissemination of the results via the web. Our software is freely available via the Google Project Hosting environment at http://genetrack.googlecode.com
高通量“芯片免疫沉淀-芯片”（ChIP-chip）和“芯片免疫沉淀-测序”（ChIP-seq）方法产生了足够大的数据集，以至于分析带来了重大的信息学挑战，特别是对于计算支持有限的研究团队而言。为应对这一挑战，我们设计了一个软件平台，用于存储、分析和可视化高分辨率全基因组结合数据。GeneTrack自动化了典型数据处理流程的多个步骤，包括平滑处理和峰检测，并通过网络促进结果的传播。我们的软件可通过谷歌项目托管环境在http://genetrack.googlecode.com免费获取。
