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FAÇADE:一种快速且灵敏的算法,用于分割和调用高分辨率阵列 CGH 数据。

FACADE: a fast and sensitive algorithm for the segmentation and calling of high resolution array CGH data.

机构信息

Department of Integrative Oncology, British Columbia Cancer Research Centre, Vancouver, BC, Canada.

出版信息

Nucleic Acids Res. 2010 Aug;38(15):e157. doi: 10.1093/nar/gkq548. Epub 2010 Jun 15.


DOI:10.1093/nar/gkq548
PMID:20551132
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC2926625/
Abstract

The availability of high resolution array comparative genomic hybridization (CGH) platforms has led to increasing complexities in data analysis. Specifically, defining contiguous regions of alterations or segmentation can be computationally intensive and popular algorithms can take hours to days for the processing of arrays comprised of hundreds of thousands to millions of elements. Additionally, tumors tend to demonstrate subtle copy number alterations due to heterogeneity, ploidy and hybridization effects. Thus, there is a need for fast, sensitive array CGH segmentation and alteration calling algorithms. Here, we describe Fast Algorithm for Calling After Detection of Edges (FACADE), a highly sensitive and easy to use algorithm designed to rapidly segment and call high resolution array data.

摘要

高分辨率阵列比较基因组杂交 (CGH) 平台的出现使得数据分析变得越来越复杂。具体来说,定义连续的改变或分割区域在计算上可能很复杂,并且流行的算法可能需要数小时到数天的时间来处理由数十万到数百万个元素组成的阵列。此外,由于异质性、倍性和杂交效应,肿瘤往往表现出细微的拷贝数改变。因此,需要快速、敏感的阵列 CGH 分割和改变调用算法。在这里,我们描述了边缘检测后的快速调用算法 (Fast Algorithm for Calling After Detection of Edges, FACADE),这是一种高度敏感且易于使用的算法,旨在快速分割和调用高分辨率阵列数据。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5ca0/2926625/481d9f366952/gkq548f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5ca0/2926625/493507c4ac56/gkq548f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5ca0/2926625/2b7a5c5c0137/gkq548f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5ca0/2926625/481d9f366952/gkq548f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5ca0/2926625/493507c4ac56/gkq548f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5ca0/2926625/2b7a5c5c0137/gkq548f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5ca0/2926625/481d9f366952/gkq548f3.jpg

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[6]
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[7]
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[8]
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本文引用的文献

[1]
A computational approach to edge detection.

IEEE Trans Pattern Anal Mach Intell. 1986-6

[2]
Comparing CNV detection methods for SNP arrays.

Brief Funct Genomic Proteomic. 2009-9

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Cancer Inform. 2007-9-17

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Genet Med. 2009-3

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Ann N Y Acad Sci. 2009-1

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Genome Res. 2009-1

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BMC Genomics. 2008-9-16

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Bioinformatics. 2008-8-15

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Sparse representation and Bayesian detection of genome copy number alterations from microarray data.

Bioinformatics. 2008-2-1

[10]
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PLoS One. 2007-8-15

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