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HOCOMOCO:通过大规模的 ChIP-Seq 分析,构建人类和小鼠转录因子结合模型的完整集合。

HOCOMOCO: towards a complete collection of transcription factor binding models for human and mouse via large-scale ChIP-Seq analysis.

机构信息

Engelhardt Institute of Molecular Biology, Russian Academy of Sciences, 119991, GSP-1, Vavilova 32, Moscow, Russia.

Vavilov Institute of General Genetics, Russian Academy of Sciences, 119991, GSP-1, Gubkina 3, Moscow, Russia.

出版信息

Nucleic Acids Res. 2018 Jan 4;46(D1):D252-D259. doi: 10.1093/nar/gkx1106.

Abstract

We present a major update of the HOCOMOCO collection that consists of patterns describing DNA binding specificities for human and mouse transcription factors. In this release, we profited from a nearly doubled volume of published in vivo experiments on transcription factor (TF) binding to expand the repertoire of binding models, replace low-quality models previously based on in vitro data only and cover more than a hundred TFs with previously unknown binding specificities. This was achieved by systematic motif discovery from more than five thousand ChIP-Seq experiments uniformly processed within the BioUML framework with several ChIP-Seq peak calling tools and aggregated in the GTRD database. HOCOMOCO v11 contains binding models for 453 mouse and 680 human transcription factors and includes 1302 mononucleotide and 576 dinucleotide position weight matrices, which describe primary binding preferences of each transcription factor and reliable alternative binding specificities. An interactive interface and bulk downloads are available on the web: http://hocomoco.autosome.ru and http://www.cbrc.kaust.edu.sa/hocomoco11. In this release, we complement HOCOMOCO by MoLoTool (Motif Location Toolbox, http://molotool.autosome.ru) that applies HOCOMOCO models for visualization of binding sites in short DNA sequences.

摘要

我们展示了 HOCOMOCO 集合的一个主要更新,该集合包含描述人类和小鼠转录因子 DNA 结合特异性的模式。在这个版本中,我们利用了近两倍的已发表的关于转录因子(TF)结合的体内实验,扩展了结合模型的范围,用基于体内数据的高质量模型替换了之前的低质量模型,并涵盖了以前未知结合特异性的超过一百个 TF。这是通过在 BioUML 框架内使用多个 ChIP-Seq 峰调用工具对超过五千个 ChIP-Seq 实验进行系统的 motif 发现来实现的,并在 GTRD 数据库中进行了汇总。HOCOMOCO v11 包含 453 个小鼠和 680 个人类转录因子的结合模型,包括 1302 个单核苷酸和 576 个二核苷酸位置权重矩阵,这些矩阵描述了每个转录因子的主要结合偏好和可靠的替代结合特异性。一个交互式界面和批量下载可在以下网址获得:http://hocomoco.autosome.ruhttp://www.cbrc.kaust.edu.sa/hocomoco11。在这个版本中,我们通过 MoLoTool(Motif Location Toolbox,http://molotool.autosome.ru)来补充 HOCOMOCO,MoLoTool 可以应用 HOCOMOCO 模型来可视化短 DNA 序列中的结合位点。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dabc/5753240/876de73ef6d5/gkx1106fig1.jpg

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