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利用 ATAC-seq 鉴定转录因子结合位点。

Identification of transcription factor binding sites using ATAC-seq.

机构信息

Institute for Computational Genomics, Joint Research Center for Computational Biomedicine, RWTH Aachen University Medical School, Aachen, 52074, Germany.

Department of Cell Biology, Institute of Biomedical Engineering, RWTH Aachen University Medical School, Aachen, 52074, Germany.

出版信息

Genome Biol. 2019 Feb 26;20(1):45. doi: 10.1186/s13059-019-1642-2.

Abstract

Transposase-Accessible Chromatin followed by sequencing (ATAC-seq) is a simple protocol for detection of open chromatin. Computational footprinting, the search for regions with depletion of cleavage events due to transcription factor binding, is poorly understood for ATAC-seq. We propose the first footprinting method considering ATAC-seq protocol artifacts. HINT-ATAC uses a position dependency model to learn the cleavage preferences of the transposase. We observe strand-specific cleavage patterns around transcription factor binding sites, which are determined by local nucleosome architecture. By incorporating all these biases, HINT-ATAC is able to significantly outperform competing methods in the prediction of transcription factor binding sites with footprints.

摘要

转座酶可及染色质测序(ATAC-seq)是一种简单的检测开放染色质的方法。对于 ATAC-seq,计算足迹分析(寻找由于转录因子结合导致的酶切事件缺失的区域)的理解很差。我们提出了第一个考虑 ATAC-seq 协议人工制品的足迹分析方法。HINT-ATAC 使用位置依赖模型来学习转座酶的切割偏好。我们观察到转录因子结合位点周围的链特异性切割模式,这些模式由局部核小体结构决定。通过整合所有这些偏差,HINT-ATAC 能够在预测具有足迹的转录因子结合位点方面显著优于竞争方法。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/da39/6391789/dc811a905952/13059_2019_1642_Fig1_HTML.jpg

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