胡须：使用尺度空间表示从 Hi-C 和 Micro-C 图谱中进行染色质环的多尺度检测。
Mustache: multi-scale detection of chromatin loops from Hi-C and Micro-C maps using scale-space representation.
机构信息
Centers for Autoimmunity and Cancer Immunotherapy, La Jolla Institute for Immunology, La Jolla, 92037, CA, USA.
Computer Science and Engineering, University of California, Riverside, Riverside, 92521, CA, USA.
出版信息
Genome Biol. 2020 Sep 30;21(1):256. doi: 10.1186/s13059-020-02167-0.
We present MUSTACHE, a new method for multi-scale detection of chromatin loops from Hi-C and Micro-C contact maps. MUSTACHE employs scale-space theory, a technical advance in computer vision, to detect blob-shaped objects in contact maps. MUSTACHE is scalable to kilobase-resolution maps and reports loops that are highly consistent between replicates and between Hi-C and Micro-C datasets. Compared to other loop callers, such as HiCCUPS and SIP, MUSTACHE recovers a higher number of published ChIA-PET and HiChIP loops as well as loops linking promoters to regulatory elements. Overall, MUSTACHE enables an efficient and comprehensive analysis of chromatin loops. Available at: https://github.com/ay-lab/mustache .
我们提出了 MUSTACHE 方法，这是一种从 Hi-C 和 Micro-C 接触图谱中检测染色质环的新方法。MUSTACHE 采用了尺度空间理论，这是计算机视觉领域的一项技术进步，用于检测接触图谱中的斑点状物体。MUSTACHE 可扩展到千碱基分辨率的图谱，并报告在重复实验和 Hi-C 与 Micro-C 数据集之间高度一致的环。与其他环调用器（如 HiCCUPS 和 SIP）相比，MUSTACHE 能够恢复更多已发表的 ChIA-PET 和 HiChIP 环以及连接启动子和调控元件的环。总的来说，MUSTACHE 能够实现对染色质环的高效和全面分析。可在 https://github.com/ay-lab/mustache 获得。
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