Analysis methods for studying the 3D architecture of the genome.
Analysis methods for studying the 3D architecture of the genome.
复制标题
DOI：
10.1186/s13059-015-0745-7
复制
发表时间：
2015-09-02
期刊：
影响因子：
12.3
通讯作者：
Noble WS
中科院分区：
文献类型：
--
作者：
Ay F;Noble WS
全基因组范围内染色体构象捕获数据的快速增长为三维基因组的计算建模和解释带来了巨大的机遇和挑战。特别是，随着最近的趋势向更高分辨率的高通量染色体构象捕获（Hi-C）数据，可以测试的生物学假设的多样性和复杂性需要严格的计算和统计方法以及可扩展的管道来解释这些数据集。在这里，我们回顾了解释Hi-C数据的计算工具，包括映射，过滤和归一化的管道，以及置信度估计，域调用，可视化和三维建模的方法。
The rapidly increasing quantity of genome-wide chromosome conformation capture data presents great opportunities and challenges in the computational modeling and interpretation of the three-dimensional genome. In particular, with recent trends towards higher-resolution high-throughput chromosome conformation capture (Hi-C) data, the diversity and complexity of biological hypotheses that can be tested necessitates rigorous computational and statistical methods as well as scalable pipelines to interpret these datasets. Here we review computational tools to interpret Hi-C data, including pipelines for mapping, filtering, and normalization, and methods for confidence estimation, domain calling, visualization, and three-dimensional modeling.