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SegAnnDB：交互式基于网络的基因组分割。

SegAnnDB: interactive Web-based genomic segmentation.

机构信息

Department of Computer Science, Tokyo Institute of Technology, Tokyo 152-8552, Japan, Institut Curie, 26 rue d'Ulm, 75248 Paris Cedex 05, INSERM U900, Paris F-75248, France, Mines ParisTech, Centre for Computational Biology, 77300 Fontainebleau, Unité de Recherche en Génomique Végétale INRA-CNRS-Université d'Evry Val d'Essonne, Évry 91057, France, INSERM U830, Paris F-75248, France, Aichi Cancer Center Research Institute, 1-1 Kanokoden, Chikusa-ku, Nagoya-city 464-8681, Japan and INRIA-Sierra Project-Team, Département d'Informatique de l'École Normale Supérieure, Paris F-75013, France.

Department of Computer Science, Tokyo Institute of Technology, Tokyo 152-8552, Japan, Institut Curie, 26 rue d'Ulm, 75248 Paris Cedex 05, INSERM U900, Paris F-75248, France, Mines ParisTech, Centre for Computational Biology, 77300 Fontainebleau, Unité de Recherche en Génomique Végétale INRA-CNRS-Université d'Evry Val d'Essonne, Évry 91057, France, INSERM U830, Paris F-75248, France, Aichi Cancer Center Research Institute, 1-1 Kanokoden, Chikusa-ku, Nagoya-city 464-8681, Japan and INRIA-Sierra Project-Team, Département d'Informatique de l'École Normale Supérieure, Paris F-75013, FranceDepartment of Computer Science, Tokyo Institute of Technology, Tokyo 152-8552, Japan, Institut Curie, 26 rue d'Ulm, 75248 Paris Cedex 05, INSERM U900, Paris F-75248, France, Mines ParisTech, Centre for Computational Biology, 77300 Fontainebleau, Unité de Recherche en Génomique Végétale INRA-CNRS-Université d'Evry Val d'Essonne, Évry 91057, France, INSERM U830, Paris F-75248, France, Aichi Cancer Center Research Institute, 1-1 Kanokoden, Chikusa-ku, Nagoya-city 464-8681, Japan and INRIA-Sierra Project-Team, Département d'Informatique de l'École Normale Supérieure, Paris F-75013, FranceDepartment of Computer Science, Tokyo Institute of Technology, Tokyo 152-8552, Japan, Institut Curie, 26 rue d'Ulm, 75248 Paris Cedex 05, INSERM U900, Paris F-75248, France, Mines ParisTech, Centre for Computational Biology, 77300 Fontainebleau, Unité de Recherche en Génomique Végétale INRA-CNRS-Université d'Evry Val d'Essonne, Évry 91057, France, INSERM U830, Paris F-75248, France, Aichi Cancer Center Research Institute, 1-1 Kanokoden, Chikusa-ku, Nagoya-city 464-8681, Japan and INRIA-Sierra Project-Team, Département d'Informatique de l'École Normale Supérieure, Paris F-75013, France.

出版信息

Bioinformatics. 2014 Jun 1;30(11):1539-46. doi: 10.1093/bioinformatics/btu072. Epub 2014 Feb 3.

DOI:10.1093/bioinformatics/btu072
PMID:24493034
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC4029035/
Abstract

MOTIVATION: DNA copy number profiles characterize regions of chromosome gains, losses and breakpoints in tumor genomes. Although many models have been proposed to detect these alterations, it is not clear which model is appropriate before visual inspection the signal, noise and models for a particular profile. RESULTS: We propose SegAnnDB, a Web-based computer vision system for genomic segmentation: first, visually inspect the profiles and manually annotate altered regions, then SegAnnDB determines the precise alteration locations using a mathematical model of the data and annotations. SegAnnDB facilitates collaboration between biologists and bioinformaticians, and uses the University of California, Santa Cruz genome browser to visualize copy number alterations alongside known genes. AVAILABILITY AND IMPLEMENTATION: The breakpoints project on INRIA GForge hosts the source code, an Amazon Machine Image can be launched and a demonstration Web site is http://bioviz.rocq.inria.fr.

摘要

动机：DNA 拷贝数谱可描述肿瘤基因组中染色体增益、缺失和断裂点区域。虽然已经提出了许多模型来检测这些改变，但在视觉检查信号、噪声和特定谱的模型之前，尚不清楚哪个模型是合适的。

结果：我们提出了 SegAnnDB，这是一个基于网络的基因组分割计算机视觉系统：首先，直观地检查谱图并手动注释改变区域，然后 SegAnnDB 使用数据和注释的数学模型来确定精确的改变位置。SegAnnDB 促进了生物学家和生物信息学家之间的合作，并使用加利福尼亚大学圣克鲁兹基因组浏览器来可视化拷贝数改变以及已知基因。

可用性和实现：INRIA GForge 上的断点项目托管源代码，可以启动亚马逊机器映像，演示网站是 http://bioviz.rocq.inria.fr。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5dbd/4029035/6289135c6814/btu072f5p.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5dbd/4029035/c17ad147f49b/btu072f1p.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5dbd/4029035/9f0b6aea6e78/btu072f2p.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5dbd/4029035/359159ddf494/btu072f3p.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5dbd/4029035/7b538f4ec47e/btu072f4p.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5dbd/4029035/6289135c6814/btu072f5p.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5dbd/4029035/c17ad147f49b/btu072f1p.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5dbd/4029035/9f0b6aea6e78/btu072f2p.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5dbd/4029035/359159ddf494/btu072f3p.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5dbd/4029035/7b538f4ec47e/btu072f4p.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5dbd/4029035/6289135c6814/btu072f5p.jpg

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引用本文的文献

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本文引用的文献

[1]
Learning smoothing models of copy number profiles using breakpoint annotations.

BMC Bioinformatics. 2013-5-22

[2]
Statistical challenges associated with detecting copy number variations with next-generation sequencing.

Bioinformatics. 2012-8-31

[3]
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Bioinformatics. 2011-12-6

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Nucleic Acids Res. 2011-11-15

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IEEE Trans Vis Comput Graph. 2011-12

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Proc Natl Acad Sci U S A. 2009-2-10

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Bioinformatics. 2008-4-1

[10]
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Nucleic Acids Res. 2007-7

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