HiCMC: 高效接触式矩阵压缩机

IF 2.9 3区 生物学 Q2 BIOCHEMICAL RESEARCH METHODS
Yeremia Gunawan Adhisantoso, Tim Körner, Fabian Müntefering, Jörn Ostermann, Jan Voges
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引用次数: 0

摘要

染色体组织在复制、调节和转录等生物过程中发挥着重要作用。研究染色体结构与其生物功能之间关系的一种方法是 Hi-C 研究,这是一种捕捉染色体构象的全基因组方法。这种研究会产生大量数据。染色体组织是动态的,需要在不同的时间点进行快照,这进一步增加了需要存储的数据量,从而使问题更加严重。我们提出了一种名为高效接触矩阵压缩器(HiCMC)的新方法,用于高效压缩 Hi-C 数据。通过对接触矩阵中发现的底层结构(如隔室和域)进行建模,HiCMC 在多个细胞系和接触矩阵分辨率上的表现比最先进的 CMC 方法优胜约 8%,比其他最先进的 Cooler、LZMA 和 bzip2 方法优胜 50%以上。此外,HiCMC 还将特定领域的信息整合到其生成的压缩比特流中,这些信息可用于加速下游分析。HiCMC 是一种新颖的压缩方法,它利用了接触矩阵的固有特性,如区块和域。与最先进的方法相比,它能实现更好的压缩效果。HiCMC 可在 https://github.com/sXperfect/hicmc 上获取。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
HiCMC: High-Efficiency Contact Matrix Compressor
Chromosome organization plays an important role in biological processes such as replication, regulation, and transcription. One way to study the relationship between chromosome structure and its biological functions is through Hi-C studies, a genome-wide method for capturing chromosome conformation. Such studies generate vast amounts of data. The problem is exacerbated by the fact that chromosome organization is dynamic, requiring snapshots at different points in time, further increasing the amount of data to be stored. We present a novel approach called the High-Efficiency Contact Matrix Compressor (HiCMC) for efficient compression of Hi-C data. By modeling the underlying structures found in the contact matrix, such as compartments and domains, HiCMC outperforms the state-of-the-art method CMC by approximately 8% and the other state-of-the-art methods cooler, LZMA, and bzip2 by over 50% across multiple cell lines and contact matrix resolutions. In addition, HiCMC integrates domain-specific information into the compressed bitstreams that it generates, and this information can be used to speed up downstream analyses. HiCMC is a novel compression approach that utilizes intrinsic properties of contact matrix, such as compartments and domains. It allows for a better compression in comparison to the state-of-the-art methods. HiCMC is available at https://github.com/sXperfect/hicmc .
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来源期刊
BMC Bioinformatics
BMC Bioinformatics 生物-生化研究方法
CiteScore
5.70
自引率
3.30%
发文量
506
审稿时长
4.3 months
期刊介绍: BMC Bioinformatics is an open access, peer-reviewed journal that considers articles on all aspects of the development, testing and novel application of computational and statistical methods for the modeling and analysis of all kinds of biological data, as well as other areas of computational biology. BMC Bioinformatics is part of the BMC series which publishes subject-specific journals focused on the needs of individual research communities across all areas of biology and medicine. We offer an efficient, fair and friendly peer review service, and are committed to publishing all sound science, provided that there is some advance in knowledge presented by the work.
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