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dc.contributor.authorChen, Xien
dc.contributor.authorShi, Xuen
dc.contributor.authorNeuwald, Andrew F.en
dc.contributor.authorHilakivi-Clarke, Leenaen
dc.contributor.authorClarke, Roberten
dc.contributor.authorXuan, Jianhuaen
dc.identifier.citationBMC Bioinformatics. 2021 Apr 15;22(1):193en
dc.description.abstractBackground ChIP-seq combines chromatin immunoprecipitation assays with sequencing and identifies genome-wide binding sites for DNA binding proteins. While many binding sites have strong ChIP-seq ‘peak’ observations and are well captured, there are still regions bound by proteins weakly, with a relatively low ChIP-seq signal enrichment. These weak binding sites, especially those at promoters and enhancers, are functionally important because they also regulate nearby gene expression. Yet, it remains a challenge to accurately identify weak binding sites in ChIP-seq data due to the ambiguity in differentiating these weak binding sites from the amplified background DNAs. Results ChIP-BIT2 ( is a software package for ChIP-seq peak detection. ChIP-BIT2 employs a mixture model integrating protein and control ChIP-seq data and predicts strong or weak protein binding sites at promoters, enhancers, or other genomic locations. For binding sites at gene promoters, ChIP-BIT2 simultaneously predicts their target genes. ChIP-BIT2 has been validated on benchmark regions and tested using large-scale ENCODE ChIP-seq data, demonstrating its high accuracy and wide applicability. Conclusion ChIP-BIT2 is an efficient ChIP-seq peak caller. It provides a better lens to examine weak binding sites and can refine or extend the existing binding site collection, providing additional regulatory regions for decoding the mechanism of gene expression regulation.en
dc.rightsCreative Commons Attribution 4.0 Internationalen
dc.titleChIP-BIT2: a software tool to detect weak binding events using a Bayesian integration approachen
dc.typeArticle - Refereeden
dc.rights.holderThe Author(s)en
dc.contributor.departmentElectrical and Computer Engineeringen
dc.title.serialBMC Bioinformaticsen

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Creative Commons Attribution 4.0 International
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