ChIP-BIT2: a software tool to detect weak binding events using a Bayesian integration approach.
ChIP-BIT2: a software tool to detect weak binding events using a Bayesian integration approach.
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ChIP-BIT2:一个使用贝叶斯集成方法检测弱绑定事件的软件工具。
DOI:
10.1186/s12859-021-04108-5
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发表时间:
2021-04-15
影响因子:
3
通讯作者:
Xuan J
中科院分区:
文献类型:
--
作者:
Chen X;Shi X;Neuwald AF;Hilakivi-Clarke L;Clarke R;Xuan J
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. ChIP-BIT2 (http://sourceforge.net/projects/chipbitc/) 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. 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. The online version contains supplementary material available at 10.1186/s12859-021-04108-5.
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影响因子:
5.8
作者:
Chen, Xi;Gu, Jinghua;Xuan, Jianhua
通讯作者:
Xuan, Jianhua
影响因子:
4.6
作者:
Chen, Xi;Gu, Jinghua;Xuan, Jianhua
通讯作者:
Xuan, Jianhua
DOI:
10.1073/pnas.1813565116
发表时间:
2019-02-26
影响因子:
11.1
作者:
Ngo, Vu;Chen, Zhao;Wang, Wei
通讯作者:
Wang, Wei
影响因子:
16.6
作者:
Mercado, Nicolas;Schutzius, Gabi;Kirkland, Susan
通讯作者:
Kirkland, Susan
影响因子:
64.8
作者:
Visel, Axel;Blow, Matthew J.;Li, Zirong;Zhang, Tao;Akiyama, Jennifer A.;Holt, Amy;Plajzer-Frick, Ingrid;Shoukry, Malak;Wright, Crystal;Chen, Feng;Afzal, Veena;Ren, Bing;Rubin, Edward M.;Pennacchio, Len A.
通讯作者:
Pennacchio, Len A.