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使用随机方法解析复杂的结构基因组重排。

Resolving complex structural genomic rearrangements using a randomized approach.

作者信息

Zhao Xuefang, Emery Sarah B, Myers Bridget, Kidd Jeffrey M, Mills Ryan E

机构信息

Department of Computational Medicine & Bioinformatics, University of Michigan, Ann Arbor, MI, 48109, USA.

Department of Human Genetics, University of Michigan, Ann Arbor, MI, 48109, USA.

出版信息

Genome Biol. 2016 Jun 10;17(1):126. doi: 10.1186/s13059-016-0993-1.

Abstract

Complex chromosomal rearrangements are structural genomic alterations involving multiple instances of deletions, duplications, inversions, or translocations that co-occur either on the same chromosome or represent different overlapping events on homologous chromosomes. We present SVelter, an algorithm that identifies regions of the genome suspected to harbor a complex event and then resolves the structure by iteratively rearranging the local genome structure, in a randomized fashion, with each structure scored against characteristics of the observed sequencing data. SVelter is able to accurately reconstruct complex chromosomal rearrangements when compared to well-characterized genomes that have been deeply sequenced with both short and long reads.

摘要

复杂染色体重排是指结构基因组改变,涉及在同一条染色体上同时发生的多个缺失、重复、倒位或易位实例,或者代表同源染色体上不同的重叠事件。我们提出了SVelter算法,该算法可识别基因组中疑似存在复杂事件的区域,然后通过以随机方式迭代重排局部基因组结构来解析结构,并根据观察到的测序数据特征对每个结构进行评分。与使用短读长和长读长进行深度测序的特征明确的基因组相比,SVelter能够准确重建复杂染色体重排。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/88b5/4901421/bfec089d6f09/13059_2016_993_Fig1_HTML.jpg

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