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基因组浏览器中三维数据可视化面临的挑战。

Challenges for visualizing three-dimensional data in genomic browsers.

作者信息

Goodstadt Mike, Marti-Renom Marc A

机构信息

Structural Genomics Group, CNAG-CRG, The Barcelona Institute of Science and Technology (BIST), Spain.

Gene Regulation, Stem Cells and Cancer Program, Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology (BIST), Spain.

出版信息

FEBS Lett. 2017 Sep;591(17):2505-2519. doi: 10.1002/1873-3468.12778. Epub 2017 Aug 24.

DOI:10.1002/1873-3468.12778
PMID:28771695
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5638070/
Abstract

Genomic interactions reveal the spatial organization of genomes and genomic domains, which is known to play key roles in cell function. Physical proximity can be represented as two-dimensional heat maps or matrices. From these, three-dimensional (3D) conformations of chromatin can be computed revealing coherent structures that highlight the importance of nonsequential relationships across genomic features. Mainstream genomic browsers have been classically developed to display compact, stacked tracks based on a linear, sequential, per-chromosome coordinate system. Genome-wide comparative analysis demands new approaches to data access and new layouts for analysis. The legibility can be compromised when displaying track-aligned second dimension matrices, which require greater screen space. Moreover, 3D representations of genomes defy vertical alignment in track-based genome browsers. Furthermore, investigation at previously unattainable levels of detail is revealing multiscale, multistate, time-dependent complexity. This article outlines how these challenges are currently handled in mainstream browsers as well as how novel techniques in visualization are being explored to address them. A set of requirements for coherent visualization of novel spatial genomic data is defined and the resulting potential for whole genome visualization is described.

摘要

基因组相互作用揭示了基因组和基因组结构域的空间组织,已知其在细胞功能中发挥关键作用。物理邻近性可以表示为二维热图或矩阵。由此,可以计算染色质的三维(3D)构象,揭示连贯的结构,突出基因组特征间非顺序关系的重要性。主流基因组浏览器传统上是基于线性、顺序的每条染色体坐标系来显示紧凑的堆叠轨迹而开发的。全基因组比较分析需要新的数据访问方法和新的分析布局。显示基于轨迹对齐的二维矩阵时,易读性可能会受到影响,因为这需要更大的屏幕空间。此外,基因组的三维表示在基于轨迹的基因组浏览器中难以进行垂直对齐。此外,在以前无法达到的细节水平上进行的研究正在揭示多尺度、多状态、时间依赖性的复杂性。本文概述了主流浏览器目前如何应对这些挑战,以及正在探索哪些新颖的可视化技术来解决这些问题。定义了一组对新型空间基因组数据进行连贯可视化的要求,并描述了全基因组可视化的潜在结果。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9d03/5638070/f3eb9438f305/FEB2-591-2505-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9d03/5638070/8da02558955d/FEB2-591-2505-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9d03/5638070/2314392be72d/FEB2-591-2505-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9d03/5638070/f3eb9438f305/FEB2-591-2505-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9d03/5638070/8da02558955d/FEB2-591-2505-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9d03/5638070/2314392be72d/FEB2-591-2505-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9d03/5638070/f3eb9438f305/FEB2-591-2505-g003.jpg

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Automatic analysis and 3D-modelling of Hi-C data using TADbit reveals structural features of the fly chromatin colors.
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