2024,
Nature Communications.
DOI:
10.1038/s41467-024-44761-x
Orchestrating chromosome conformation capture analysis with Bioconductor
Jacques Serizay, Cyril Matthey-Doret, Amaury Bignaud, Lyam Baudry, Romain Koszul
Abstract:
Abstract Genome-wide chromatin conformation capture assays provide formidable insights into the spatial organization of genomes. However, due to the complexity of the data structure, their integration in multi-omics workflows remains challenging. We present data structures, computational methods and visualization tools available in Bioconductor to investigate Hi-C, micro-C and other 3C-related data, in R. An online book (https://bioconductor.org/books/OHCA/ ) further provides prospective end users with a number of workflows to process, import, analyze and visualize any type of chromosome conformation capture data.
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2024-02-29 10:20:00
徐炳祥:
#paper doi: 10.1038/s41467-024-44761-x Nature communications, 2024, Orchestrating chromosome conformation capture analysis with Bioconductor。全基因组染色质构象捕获技术（Hi-C）及其衍生技术是当前研究真核细胞染色质空间构象的最主流技术手段，基于其的研究所涉及的大体量，多模、多目标的多组学分析问题对生物信息技术提出了许多重大挑战。本文系统性的总结了过去十几年来依托R语言和Bioconductor平台开发的一系列Hi-C及衍生数据分析工具包。按分析流程详细描述了数据的获取和预处理，结果的导入导出，核心数据结构，各拓扑结构单元的识别，数据可视化等数据分析的方方面面。本文的总结对学习Hi-C数据分析有重要参考价值，同时也对定制化的分析流程开发有指导意义。