DNA测序
结构变异
计算生物学
人口
计算机科学
断点
比例(比率)
算法
数据挖掘
生物
遗传学
DNA
基因组
基因
地图学
医学
地理
环境卫生
染色体易位
标识
DOI:10.1007/978-1-0716-2293-3_8
摘要
Next-generation sequencing technologies have been widely used to query genetic variants in normal individuals as well as in those with diseases. Large-scale structural variations are a common source of genetic diversity in human population, and some of them have significant contributions to the etiology of diseases. However, the detection of large-scale structural variations from sequencing data remains challenging. Here, we describe Meerkat—an algorithm which can reliably detect structural variations from Illumina short-read sequencing data at basepair resolution. A unique feature of Meerkat is that it can infer the variant forming mechanisms based on the DNA content and features at the breakpoints.
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