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通过采样对Hi-C接触频率进行后验推断。

Posterior inference of Hi-C contact frequency through sampling.

作者信息

Zhang Yanlin, Cameron Christopher J F, Blanchette Mathieu

机构信息

School of Computer Science, McGill University, Montréal, QC, Canada.

Department of Biochemistry and Goodman Cancer Research Center, McGill University, Montreal, QC, Canada.

出版信息

Front Bioinform. 2024 Feb 22;3:1285828. doi: 10.3389/fbinf.2023.1285828. eCollection 2023.

Abstract

Hi-C is one of the most widely used approaches to study three-dimensional genome conformations. Contacts captured by a Hi-C experiment are represented in a contact frequency matrix. Due to the limited sequencing depth and other factors, Hi-C contact frequency matrices are only approximations of the true interaction frequencies and are further reported without any quantification of uncertainty. Hence, downstream analyses based on Hi-C contact maps (e.g., TAD and loop annotation) are themselves point estimations. Here, we present the Hi-C interaction frequency sampler (HiCSampler) that reliably infers the posterior distribution of the interaction frequency for a given Hi-C contact map by exploiting dependencies between neighboring loci. Posterior predictive checks demonstrate that HiCSampler can infer highly predictive chromosomal interaction frequency. Summary statistics calculated by HiCSampler provide a measurement of the uncertainty for Hi-C experiments, and samples inferred by HiCSampler are ready for use by most downstream analysis tools off the shelf and permit uncertainty measurements in these analyses without modifications.

摘要

Hi-C是研究三维基因组构象应用最广泛的方法之一。Hi-C实验捕获的接触在接触频率矩阵中表示。由于测序深度有限和其他因素,Hi-C接触频率矩阵只是真实相互作用频率的近似值,并且在报告时没有对不确定性进行任何量化。因此,基于Hi-C接触图谱的下游分析(例如,TAD和环注释)本身就是点估计。在这里,我们提出了Hi-C相互作用频率采样器(HiCSampler),它通过利用相邻位点之间的依赖性,可靠地推断给定Hi-C接触图谱的相互作用频率的后验分布。后验预测检查表明,HiCSampler可以推断出具有高度预测性的染色体相互作用频率。HiCSampler计算的汇总统计数据提供了对Hi-C实验不确定性的度量,并且HiCSampler推断的样本可直接供大多数下游分析工具使用,并允许在这些分析中进行不确定性测量而无需修改。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e620/10919286/0d542c46cf87/fbinf-03-1285828-g001.jpg

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