A Non-Homogeneous Hidden-State Model on First Order Differences for Automatic Detection of Nucleosome Positions
A Non-Homogeneous Hidden-State Model on First Order Differences for Automatic Detection of Nucleosome Positions
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DOI：
10.2202/1544-6115.1454
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发表时间：
2009-01-01
影响因子：
0.9
通讯作者：
Keles, Sunduz
中科院分区：
文献类型：
--
作者：
Kuan, Pei Fen;Huebert, Dana;Keles, Sunduz
在基因组中准确绘制单个核小体的能力使得能够研究核小体定位/占据和基因调控的动态变化之间的关系。然而，核小体密度在基因组和短接头区域之间的高度异质性对基于微球菌核酸酶（MNase）消化的DNA的高通量微阵列数据绘制核小体位置提出了挑战。以前的工作依赖于额外的去趋势和仔细的视觉检查来检测低信号核小体，这可能存在于细胞亚群中。我们提出了一个非均匀的隐藏状态模型的基础上，一阶差异的实验数据沿着基因组坐标，绕过需要本地去趋势，可以自动检测核小体的位置的各种占用水平。我们提出的方法适用于低分辨率和高分辨率的MNase-Chip和MNase-Seq（高通量测序）数据，并且能够准确地映射核小体-接头边界。这种自动算法在计算上也是高效的，并且只需要简单的预处理步骤。我们提供了几个例子，说明现有方法的陷阱，所观察到的杂交信号的去趋势的困难，并证明了利用一阶差分检测核小体占位的优势，通过模拟和案例研究涉及Mnase-Chip和Mnase-Seq数据的核小体占位在酵母S。啤酒。
The ability to map individual nucleosomes accurately across genomes enables the study of relationships between dynamic changes in nucleosome positioning/occupancy and gene regulation. However, the highly heterogeneous nature of nucleosome densities across genomes and short linker regions pose challenges in mapping nucleosome positions based on high-throughput microarray data of micrococcal nuclease (MNase) digested DNA. Previous works rely on additional detrending and careful visual examination to detect low-signal nucleosomes, which may exist in a subpopulation of cells. We propose a non-homogeneous hidden-state model based on first order differences of experimental data along genomic coordinates that bypasses the need for local detrending and can automatically detect nucleosome positions of various occupancy levels. Our proposed approach is applicable to both low and high resolution MNase-Chip and MNase-Seq (high throughput sequencing) data, and is able to map nucleosome-linker boundaries accurately. This automated algorithm is also computationally efficient and only requires a simple preprocessing step. We provide several examples illustrating the pitfalls of existing methods, the difficulties of detrending the observed hybridization signals and demonstrate the advantages of utilizing first order differences in detecting nucleosome occupancies via simulations and case studies involving MNase-Chip and MNase-Seq data of nucleosome occupancy in yeast S. cerevisiae.