Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, 44 Binney St, Boston, MA 02115, USA.
Bioinformatics. 2009 Oct 1;25(19):2605-6. doi: 10.1093/bioinformatics/btp479. Epub 2009 Aug 18.
We present a tool designed to characterize genome-wide protein-DNA interaction patterns from ChIP-chip and ChIP-Seq data. This stand-alone extension of our web application CEAS (cis-regulatory element annotation system) provides summary statistics on ChIP enrichment in important genomic regions such as individual chromosomes, promoters, gene bodies or exons, and infers the genes most likely to be regulated by the binding factor under study. CEAS also enables biologists to visualize the average ChIP enrichment signals over specific genomic regions, particularly allowing observation of continuous and broad ChIP enrichment that might be too subtle to detect from ChIP peaks alone.
The CEAS Python package is publicly available at http://liulab.dfci.harvard.edu/CEAS.
我们提出了一个工具，旨在从 ChIP-chip 和 ChIP-Seq 数据中描述全基因组蛋白-DNA 相互作用模式。这是我们的网络应用程序 CEAS（顺式调控元件注释系统）的独立扩展，提供了 ChIP 富集在重要基因组区域（如单个染色体、启动子、基因体或外显子）的重要统计信息，并推断出最有可能受研究结合因子调控的基因。CEAS 还使生物学家能够可视化特定基因组区域上的平均 ChIP 富集信号，特别是允许观察到连续和广泛的 ChIP 富集，这些富集可能过于微妙，仅凭 ChIP 峰无法检测到。
CEAS Python 包可在 http://liulab.dfci.harvard.edu/CEAS 上公开获取。
