A geometric approach for classification and comparison of structural variants.
A geometric approach for classification and comparison of structural variants.
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DOI：
10.1093/bioinformatics/btp208
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发表时间：
2009-06-15
期刊：
影响因子：
--
通讯作者：
Raphael BJ
中科院分区：
文献类型：
--
作者：
Sindi S;Helman E;Bashir A;Raphael BJ
动机：结构变异，包括大段 DNA 序列的重复、插入、删除和倒位，是人类基因组变异的重要贡献者。测量基因组序列中的结构变异通常比测量单核苷酸变化更具挑战性。目前的结构变体识别方法，包括双端 DNA 测序/作图和阵列比较基因组杂交 (aCGH)，并不能精确识别变体的边界。因此，大多数报道的人类结构变异的定义不明确，并且不容易在不同的研究和测量技术之间进行比较。结果：我们引入了结构变体的几何分析（GASV），这是一种用于识别、分类和比较结构变体的几何方法。该方法将结构变体测量的不确定性表示为平面中的多边形，并通过计算多边形的交集来识别支持相同变体的测量。我们推导出一种计算几何算法来有效地识别所有此类交叉点。我们将 GASV 应用到九个人类基因组和几个癌症基因组的测序数据中。我们更好地定位结构变体的边界，区分癌症基因组中的遗传结构变体和假定的体细胞结构变体，并整合 aCGH 和结构变体的双端测序测量。这项工作提出了第一个比较多个样本和测量技术的结构变异的通用框架，并将有助于研究癌症中的遗传结构变异和体细胞重排。可用性：http://cs.brown.edu/people/braphael/software.html 联系方式：braphael@brown.edu
Motivation: Structural variants, including duplications, insertions, deletions and inversions of large blocks of DNA sequence, are an important contributor to human genome variation. Measuring structural variants in a genome sequence is typically more challenging than measuring single nucleotide changes. Current approaches for structural variant identification, including paired-end DNA sequencing/mapping and array comparative genomic hybridization (aCGH), do not identify the boundaries of variants precisely. Consequently, most reported human structural variants are poorly defined and not readily compared across different studies and measurement techniques. Results: We introduce Geometric Analysis of Structural Variants (GASV), a geometric approach for identification, classification and comparison of structural variants. This approach represents the uncertainty in measurement of a structural variant as a polygon in the plane, and identifies measurements supporting the same variant by computing intersections of polygons. We derive a computational geometry algorithm to efficiently identify all such intersections. We apply GASV to sequencing data from nine individual human genomes and several cancer genomes. We obtain better localization of the boundaries of structural variants, distinguish genetic from putative somatic structural variants in cancer genomes, and integrate aCGH and paired-end sequencing measurements of structural variants. This work presents the first general framework for comparing structural variants across multiple samples and measurement techniques, and will be useful for studies of both genetic structural variants and somatic rearrangements in cancer. Availability: http://cs.brown.edu/people/braphael/software.html Contact: braphael@brown.edu
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影响因子：
30.8
作者：
Iafrate, AJ;Feuk, L;Lee, C
通讯作者：
Lee, C
影响因子：
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作者：
Sebat, J;Lakshmi, B;Wigler, M
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Campbell, Peter J.;Stephens, Philip J.;Pleasance, Erin D.;O'Meara, Sarah;Li, Heng;Santarius, Thomas;Stebbings, Lucy A.;Leroy, Catherine;Edkins, Sarah;Hardy, Claire;Teague, Jon W.;Menzies, Andrew;Goodhead, Ian;Turner, Daniel J.;Clee, Christopher M.;Quail, Michael A.;Cox, Antony;Brown, Clive;Durbin, Richard;Hurles, Matthew E.;Edwards, Paul A. W.;Bignell, Graham R.;Stratton, Michael R.;Futreal, P. Andrew
通讯作者：
Futreal, P. Andrew
影响因子：
30.8
作者：
Cooper, Gregory M.;Zerr, Troy;Kidd, Jeffrey M.;Eichler, Evan E.;Nickerson, Deborah A.
通讯作者：
Nickerson, Deborah A.
DOI：
10.1093/bioinformatics/btn176
发表时间：
2008-07-01
期刊：
Bioinformatics (Oxford, England)
影响因子：
--
作者：
Lee S;Cheran E;Brudno M
通讯作者：
Brudno M