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基于 MNase 或超声处理短读数据的核小体定位的概率推断。

Probabilistic inference for nucleosome positioning with MNase-based or sonicated short-read data.

机构信息

Statistics Department, University of British Columbia, Vancouver, British Columbia, Canada.

出版信息

PLoS One. 2012;7(2):e32095. doi: 10.1371/journal.pone.0032095. Epub 2012 Feb 29.

Abstract

We describe a model-based method, PING, for predicting nucleosome positions in MNase-Seq and MNase- or sonicated-ChIP-Seq data. PING compares favorably to NPS and TemplateFilter in scalability, accuracy and robustness to low read density. To demonstrate that PING predictions from widely available sonicated data can have sufficient spatial resolution to be to be useful for biological inference, we use Illumina H3K4me1 ChIP-seq data to detect changes in nucleosome positioning around transcription factor binding sites due to tamoxifen stimulation, to discriminate functional and non-functional transcription factor binding sites more effectively than with enrichment profiles, and to confirm that the pioneer transcription factor Foxa2 associates with the accessible major groove of nucleosomal DNA.

摘要

我们描述了一种基于模型的方法 PING,用于预测 MNase-Seq 和 MNase 或超声 ChIP-Seq 数据中的核小体位置。PING 在可扩展性、准确性和对低读密度的稳健性方面优于 NPS 和 TemplateFilter。为了证明来自广泛可用的超声数据的 PING 预测具有足够的空间分辨率,足以用于生物学推断,我们使用 Illumina H3K4me1 ChIP-seq 数据来检测由于他莫昔芬刺激导致的转录因子结合位点附近核小体定位的变化,与富集谱相比,更有效地区分功能和非功能转录因子结合位点,并证实先驱转录因子 Foxa2 与核小体 DNA 的可及主沟结合。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7d31/3290535/f583f6d0ede2/pone.0032095.g001.jpg

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