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使用BETA整合转录组和ChIP-seq数据进行靶标分析。

Target analysis by integration of transcriptome and ChIP-seq data with BETA.

作者信息

Wang Su, Sun Hanfei, Ma Jian, Zang Chongzhi, Wang Chenfei, Wang Juan, Tang Qianzi, Meyer Clifford A, Zhang Yong, Liu X Shirley

机构信息

Department of Bioinformatics, School of Life Science and Technology, Tongji University, Shanghai, China.

出版信息

Nat Protoc. 2013 Dec;8(12):2502-15. doi: 10.1038/nprot.2013.150. Epub 2013 Nov 21.

Abstract

The combination of ChIP-seq and transcriptome analysis is a compelling approach to unravel the regulation of gene expression. Several recently published methods combine transcription factor (TF) binding and gene expression for target prediction, but few of them provide an efficient software package for the community. Binding and expression target analysis (BETA) is a software package that integrates ChIP-seq of TFs or chromatin regulators with differential gene expression data to infer direct target genes. BETA has three functions: (i) to predict whether the factor has activating or repressive function; (ii) to infer the factor's target genes; and (iii) to identify the motif of the factor and its collaborators, which might modulate the factor's activating or repressive function. Here we describe the implementation and features of BETA to demonstrate its application to several data sets. BETA requires ~1 GB of RAM, and the procedure takes 20 min to complete. BETA is available open source at http://cistrome.org/BETA/.

摘要

染色质免疫沉淀测序(ChIP-seq)与转录组分析相结合是一种用于揭示基因表达调控机制的有效方法。最近发表的几种方法将转录因子(TF)结合与基因表达相结合用于靶点预测,但其中很少有能为学界提供高效软件包的。结合与表达靶点分析(BETA)软件包将TF或染色质调节因子的ChIP-seq与差异基因表达数据整合起来,以推断直接靶点基因。BETA有三个功能:(i)预测该因子具有激活还是抑制功能;(ii)推断该因子的靶点基因;(iii)识别该因子及其协同因子的基序,这些基序可能会调节该因子的激活或抑制功能。在此,我们描述BETA的实现过程和特点,以展示其在几个数据集上的应用。BETA需要约1GB的随机存取存储器,整个过程需要20分钟完成。BETA可在http://cistrome.org/BETA/上开源获取。

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