Shanghai Key Laboratory of Tuberculosis, Clinical Translational Research Center, Shanghai Pulmonary Hospital, School of Life Sciences and Technology, Tongji University, Shanghai 200092, China.
Department of Data Sciences, Dana-Farber Cancer Institute and Harvard T.H. Chan School of Public Health, Boston, MA 02215, USA.
Nucleic Acids Res. 2019 Jul 2;47(W1):W206-W211. doi: 10.1093/nar/gkz332.
Characterizing the ontologies of genes directly regulated by a transcription factor (TF), can help to elucidate the TF's biological role. Previously, we developed a widely used method, BETA, to integrate TF ChIP-seq peaks with differential gene expression (DGE) data to infer direct target genes. Here, we provide Cistrome-GO, a website implementation of this method with enhanced features to conduct ontology analyses of gene regulation by TFs in human and mouse. Cistrome-GO has two working modes: solo mode for ChIP-seq peak analysis; and ensemble mode, which integrates ChIP-seq peaks with DGE data. Cistrome-GO is freely available at http://go.cistrome.org/.
对受转录因子 (TF) 直接调控的基因的本体论进行分析，可以帮助阐明 TF 的生物学作用。此前，我们开发了一种广泛使用的方法 BETA，该方法将 TF ChIP-seq 峰与差异基因表达 (DGE) 数据整合，以推断直接靶基因。在这里，我们提供了 Cistrome-GO，这是该方法的网站实现，具有增强的功能，可对人和小鼠中 TF 基因调控的本体论进行分析。Cistrome-GO 有两种工作模式：solo 模式用于 ChIP-seq 峰分析；和集成模式，将 ChIP-seq 峰与 DGE 数据集成。Cistrome-GO 可免费在 http://go.cistrome.org/ 获取。
