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

By Su-wen Wang, Hanfei Sun, Jian Ma, Chongzhi Zang, Chenfei Wang, Juan Wang, Q. Tang, Clifford A. Meyer, Yong Zhang, Shirley Liu. Nature Protocols, 2013

473 citations recorded by the source corpus.

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/.

Subfields: Molecular Biology

View Paper: https://www.semanticscholar.org/paper/dd07a6ccc8ebc34e791d002806090f411d00fae7

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Citations in the corpus

Cistrome Data Browser: a data portal for ChIP-Seq and chromatin accessibility data in human and mouse (2016, methodology): “Finally, we performed annotation analysis, including average conservation profiles across peak regions, motif analysis (21) and putative gene target identification (22).”
A survey of best practices for RNA-seq data analysis (2016, methodology): “For example, BETA [146] uses differential gene expression in combination with peaks from ChIP-seq experiments to call TF targets.”
A major chromatin regulator determines resistance of tumor cells to T cell–mediated killing (2018, methodology): “Binding and expression target analysis (BETA) (47) was used to integrate ATAC-seq data on accessible chromatin sites with differential gene expression data to infer directly targeted genes.”
Cistrome Data Browser: expanded datasets and new tools for gene regulatory analysis (2018, background): “The first function addresses the question: ‘What factors regulate your gene of interest?’ The assignment of TFs to genes is based on regulatory potential scores that reflect the collective influence of the binding sites of a given TF on genes nearby these sites (30), and assume that TF binding sites”