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Chromatin 3D structure reconstruction with consideration of adjacency relationship among genomic loci.
BMC Bioinformatics ( IF 3 ) Pub Date : 2020-07-01 , DOI: 10.1186/s12859-020-03612-4 Fang-Zhen Li 1, 2 , Zhi-E Liu 3 , Xiu-Yuan Li 1, 2 , Li-Mei Bu 4 , Hong-Xia Bu 2 , Hui Liu 1, 5 , Cai-Ming Zhang 1, 5
BMC Bioinformatics ( IF 3 ) Pub Date : 2020-07-01 , DOI: 10.1186/s12859-020-03612-4 Fang-Zhen Li 1, 2 , Zhi-E Liu 3 , Xiu-Yuan Li 1, 2 , Li-Mei Bu 4 , Hong-Xia Bu 2 , Hui Liu 1, 5 , Cai-Ming Zhang 1, 5
Affiliation
Chromatin 3D conformation plays important roles in regulating gene or protein functions. High-throughout chromosome conformation capture (3C)-based technologies, such as Hi-C, have been exploited to acquire the contact frequencies among genomic loci at genome-scale. Various computational tools have been proposed to recover the underlying chromatin 3D structures from in situ Hi-C contact map data. As connected residuals in a polymer, neighboring genomic loci have intrinsic mutual dependencies in building a 3D conformation. However, current methods seldom take this feature into account. We present a method called ShNeigh, which combines the classical MDS technique with local dependence of neighboring loci modeled by a Gaussian formula, to infer the best 3D structure from noisy and incomplete contact frequency matrices. We validated ShNeigh by comparing it to two typical distance-based algorithms, ShRec3D and ChromSDE. The comparison results on simulated Hi-C dataset showed that, while keeping the high-speed nature of classical MDS, ShNeigh can recover the true structure better than ShRec3D and ChromSDE. Meanwhile, ShNeigh is more robust to data noise. On the publicly available human GM06990 Hi-C data, we demonstrated that the structures reconstructed by ShNeigh are more reproducible between different restriction enzymes than by ShRec3D and ChromSDE, especially at high resolutions manifested by sparse contact maps, which means ShNeigh is more robust to signal coverage. Our method can recover stable structures in high noise and sparse signal settings. It can also reconstruct similar structures from Hi-C data obtained using different restriction enzymes. Therefore, our method provides a new direction for enhancing the reconstruction quality of chromatin 3D structures.
中文翻译:
考虑基因组位点之间邻接关系的染色质3D结构重建。
染色质3D构象在调节基因或蛋白质功能中起重要作用。基于高通量染色体构象捕获(3C)的技术(例如Hi-C)已被用于在基因组规模上获取基因组基因座之间的接触频率。已经提出了各种计算工具来从原位Hi-C接触图数据中恢复潜在的染色质3D结构。作为聚合物中的连接残基,相邻的基因组位点在构建3D构象时具有固有的相互依赖性。但是,当前的方法很少考虑此功能。我们提出了一种称为ShNeigh的方法,该方法将经典MDS技术与通过高斯公式建模的相邻基因座的局部依赖性相结合,以从嘈杂和不完整的接触频率矩阵中推断出最佳3D结构。我们通过将ShNeigh与两种典型的基于距离的算法ShRec3D和ChromSDE进行比较来验证其有效性。在模拟Hi-C数据集上的比较结果表明,在保持经典MDS的高速特性的同时,ShNeigh可以比ShRec3D和ChromSDE更好地恢复真实结构。同时,ShNeigh对数据噪声更健壮。在可公开获得的人类GM06990 Hi-C数据上,我们证明了ShNeigh重建的结构在不同的限制酶之间比ShRec3D和ChromSDE更可重现,尤其是在稀疏的接触图显示的高分辨率下,这意味着ShNeigh信号更强健覆盖范围。我们的方法可以在高噪声和稀疏信号设置下恢复稳定的结构。它还可以从使用不同限制酶获得的Hi-C数据重建相似的结构。因此,
更新日期:2020-07-01
中文翻译:
考虑基因组位点之间邻接关系的染色质3D结构重建。
染色质3D构象在调节基因或蛋白质功能中起重要作用。基于高通量染色体构象捕获(3C)的技术(例如Hi-C)已被用于在基因组规模上获取基因组基因座之间的接触频率。已经提出了各种计算工具来从原位Hi-C接触图数据中恢复潜在的染色质3D结构。作为聚合物中的连接残基,相邻的基因组位点在构建3D构象时具有固有的相互依赖性。但是,当前的方法很少考虑此功能。我们提出了一种称为ShNeigh的方法,该方法将经典MDS技术与通过高斯公式建模的相邻基因座的局部依赖性相结合,以从嘈杂和不完整的接触频率矩阵中推断出最佳3D结构。我们通过将ShNeigh与两种典型的基于距离的算法ShRec3D和ChromSDE进行比较来验证其有效性。在模拟Hi-C数据集上的比较结果表明,在保持经典MDS的高速特性的同时,ShNeigh可以比ShRec3D和ChromSDE更好地恢复真实结构。同时,ShNeigh对数据噪声更健壮。在可公开获得的人类GM06990 Hi-C数据上,我们证明了ShNeigh重建的结构在不同的限制酶之间比ShRec3D和ChromSDE更可重现,尤其是在稀疏的接触图显示的高分辨率下,这意味着ShNeigh信号更强健覆盖范围。我们的方法可以在高噪声和稀疏信号设置下恢复稳定的结构。它还可以从使用不同限制酶获得的Hi-C数据重建相似的结构。因此,