Modeling nucleosome position distributions from experimental nucleosome positioning maps
Modeling nucleosome position distributions from experimental nucleosome positioning maps
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DOI：
10.1093/bioinformatics/btt404
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发表时间：
2013-10
期刊：
影响因子：
5.8
通讯作者：
R. Schöpflin;V. B. Teif;Oliver Müller;Christin Weinberg;K. Rippe;Gero Wedemann
中科院分区：
文献类型：
--
作者：
R. Schöpflin;V. B. Teif;Oliver Müller;Christin Weinberg;K. Rippe;Gero Wedemann
动机 最近的实验进展允许确定完整基因组的核小体位置。然而，所得的核小体占据图是异质细胞群的平均值。因此，它们代表了单个时间点动态整体的快照，其中覆盖了来自不同细胞的许多配置。为了研究核小体沿着基因组的组织并了解核小体易位的机制，有必要从群体平均值中检索特定构象的特征。结果在这里，我们提出了一种识别非重叠核小体构型的方法，该方法将二元变量分析和蒙特卡罗方法与模拟退火方案相结合。通过这种方式，我们从实验数据中获得了特定的核小体构型和复杂定位模式的优化解决方案。我们应用该方法来比较不同小鼠细胞类型中转录因子结合位点的核小体定位。我们的方法可以模拟调节基因组元件处的核小体易位，并生成用于模拟核小体链空间折叠的配置。可用性 源代码、预编译的二进制文件、测试数据和基于 Web 的测试安装可在 http://bioinformatics.fh-stralsund.de/nucpos/ 上免费获取
MOTIVATION Recent experimental advancements allow determining positions of nucleosomes for complete genomes. However, the resulting nucleosome occupancy maps are averages of heterogeneous cell populations. Accordingly, they represent a snapshot of a dynamic ensemble at a single time point with an overlay of many configurations from different cells. To study the organization of nucleosomes along the genome and to understand the mechanisms of nucleosome translocation, it is necessary to retrieve features of specific conformations from the population average. RESULTS Here, we present a method for identifying non-overlapping nucleosome configurations that combines binary-variable analysis and a Monte Carlo approach with a simulated annealing scheme. In this manner, we obtain specific nucleosome configurations and optimized solutions for the complex positioning patterns from experimental data. We apply the method to compare nucleosome positioning at transcription factor binding sites in different mouse cell types. Our method can model nucleosome translocations at regulatory genomic elements and generate configurations for simulations of the spatial folding of the nucleosome chain. AVAILABILITY Source code, precompiled binaries, test data and a web-based test installation are freely available at http://bioinformatics.fh-stralsund.de/nucpos/