通过抽样对 Hi-C 接触频率进行后验推断。

IF 2.8 Q2 MATHEMATICAL & COMPUTATIONAL BIOLOGY
Frontiers in bioinformatics Pub Date : 2024-02-22 eCollection Date: 2023-01-01 DOI:10.3389/fbinf.2023.1285828
Yanlin Zhang, Christopher J F Cameron, Mathieu Blanchette
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引用次数: 0

摘要

Hi-C 是研究三维基因组构象最广泛使用的方法之一。Hi-C 实验捕获的接触用接触频率矩阵表示。由于测序深度和其他因素的限制,Hi-C 接触频率矩阵只是真实相互作用频率的近似值,在进一步报告时没有对不确定性进行量化。因此,基于 Hi-C 接触图的下游分析(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),它通过利用相邻基因座之间的依赖关系,可靠地推断出给定 Hi-C 接触图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。由 HiCSampler 计算出的汇总统计量可测量 Hi-C 实验的不确定性,而且由 HiCSampler 推断出的样本可供大多数现成的下游分析工具使用,无需修改即可在这些分析中进行不确定性测量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Posterior inference of Hi-C contact frequency through sampling.

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.

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CiteScore
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