Probabilistic modeling of Hi-C contact maps eliminates systematic biases to characterize global chromosomal architecture.

Yaffe E; Tanay A

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Probabilistic modeling of Hi-C contact maps eliminates systematic biases to characterize global chromosomal architecture.

机译：Hi-C接触图的概率建模消除了表征全局染色体架构的系统偏差。

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Hi-C experiments measure the probability of physical proximity between pairs of chromosomal loci on a genomic scale. We report on several systematic biases that substantially affect the Hi-C experimental procedure, including the distance between restriction sites, the GC content of trimmed ligation junctions and sequence uniqueness. To address these biases, we introduce an integrated probabilistic background model and develop algorithms to estimate its parameters and renormalize Hi-C data. Analysis of corrected human lymphoblast contact maps provides genome-wide evidence for interchromosomal aggregation of active chromatin marks, including DNase-hypersensitive sites and transcriptionally active foci. We observe extensive long-range (up to 400 kb) cis interactions at active promoters and derive asymmetric contact profiles next to transcription start sites and CTCF binding sites. Clusters of interacting chromosomal domains suggest physical separation of centromere-proximal and centromere-distal regions. These results provide a computational basis for the inference of chromosomal architectures from Hi-C experiments.

机译：Hi-C实验在基因组尺度上测量成对的染色体基因座之间的物理接近性概率。我们报告了几个实质上影响Hi-C实验程序的系统性偏见，包括限制性酶切位点之间的距离，修饰连接结的GC含量和序列唯一性。为了解决这些偏差，我们引入了一个集成的概率背景模型，并开发了算法来估计其参数并重新标准化Hi-C数据。校正后的人类淋巴母细胞接触图的分析为活性染色质标记（包括DNase超敏位点和转录活性灶）的染色体间聚集提供了全基因组证据。我们观察到在活性启动子上广泛的远距离（高达400 kb）顺式相互作用，并在转录起始位点和CTCF结合位点附近获得了不对称的接触曲线。相互作用的染色体结构域的簇建议将着丝粒-近端和着丝粒-远端区分开。这些结果为从Hi-C实验推论染色体结构提供了计算基础。

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《Nature Genetics》 |2011年第11期|共7页
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Yaffe E; Tanay A;
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正文语种 eng
中图分类医学遗传学;
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1. Probabilistic modeling of Hi-C contact maps eliminates systematic biases to characterize global chromosomal architecture. [J] . Yaffe E, Tanay A Nature Genetics . 2011,第11期

机译：Hi-C接触图的概率建模消除了表征全局染色体架构的系统偏差。
2. From Hi-C Contact Map to Three-Dimensional Organization of Interphase Human Chromosomes [J] . Guang Shi, D. Thirumalai Physical Review X . 2021,第1期

机译：从Hi-C联系地图到三维人类染色体的三维组织
3. HiC-Hiker: a probabilistic model to determine contig orientation in chromosome-length scaffolds with Hi-C [J] . Bioinformatics . 2020,第13期

机译：HIC-HIKER：一种概率模型，用于测定HI-C染色体长度支架中的CONTIG定位
4. Topological Data Analysis of Single-Cell Hi-C Contact Maps [C] . Mathieu Carriere, Raul Rabadan Abel Symposia . 2020

机译：单细胞Hi-C联系地图的拓扑数据分析
5. HiCsr: A Hi-C Super-Resolution Framework for Producing Highly Realistic Contact Maps [D] . Dimmick, Michael. 2020

机译：HISSR：一个高级分辨率的高度现实联系地图的超级分辨率框架
6. Correction: GOTHiC a probabilistic model to resolve complex biases and to identify real interactions in Hi-C data [O] . -1

机译：校正：GOTHiC一种概率模型用于解决复杂的偏差并识别Hi-C数据中的实际相互作用
7. Figure 1: Example of visualization of long range contacts for: (A) regions, here enhancer-promoter contacts, for two 10 kb resolution Hi-C maps from human Fetal Brain cells. Contacts were calculated up to 30 bins distance each way from the point of interest. Top to bottom: a Jbrowse (Skinner et al., 2009) screenshot with genes and interaction profile representation (points of interest in green, their contact predictions in yellow); HiCEnterprise interaction profile plot with intensities (weighted by distance) and −log10 of FDR corrected p-values (q-values) with a threshold set at 0.01. (B) TADs, here HiCEnterprise visualization for 150 kb resolution Hi-C map of 17th chromosome from HUVEC. Left upper trianle: original Hi-C map contact frequencies; right lower triangle: −log10 of q-values of the interdomain interactions calculated with hypergeometric distribution. [O] . -1

机译：图1：用于：（a）区域的长距离触点的可视化示例，这里增强了来自人胎儿脑细胞的两个10kb分辨率的Hi-C地图。从兴趣点计算联系人高达30个距离距离。顶部到底：jbrowse（Skinner等，2009）截图，具有基因和互动曲线表示（绿色兴趣点，它们的黄色接触预测）; HICENTERPLISE交互配置曲线图具有强度（由距离加权）和FDR校正的P值（Q值）的-LOG10，其阈值设置为0.01。（b）TADS，这里是来自Huvec的第17次染色体的150 KB分辨率Hi-C地图的Hicenterprise可视化。左上三角：原版Hi-C地图接触频率;右下三角形：跨度相互作用的Q值的-log10计算，使用超几何分布计算。

Probabilistic modeling of Hi-C contact maps eliminates systematic biases to characterize global chromosomal architecture.

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