Zhang Yanlin, Cameron Christopher J F, Blanchette Mathieu
School of Computer Science, McGill University, Montréal, QC, Canada.
Department of Biochemistry and Goodman Cancer Research Center, McGill University, Montreal, QC, Canada.
Front Bioinform. 2024 Feb 22;3:1285828. doi: 10.3389/fbinf.2023.1285828. eCollection 2023.
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.
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。