cnvHiTSeq: integrative models for high-resolution copy number variation detection and genotyping using population sequencing data.

cnvHiTSeq: integrative models for high-resolution copy number variation detection and genotyping using population sequencing data.
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DOI:
10.1186/gb-2012-13-12-r120
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发表时间:
2012-12-22
期刊:
影响因子:
12.3
通讯作者:
Coin LJ
Coin LJ
中科院分区:
生物学1区
文献类型:
--
作者:
Bellos E;Johnson MR;Coin LJ

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测序技术的最新进展提供了以前所未有的分辨率鉴定拷贝数变异(CNV)的手段。单个下一代测序实验提供了几个可用于检测CNV的特征,但目前的方法并没有将所有可用的特征纳入统一的模型中。cnvHiTSeq是用于CNV发现和基因分型的综合概率方法,其在群体水平上联合分析多个特征。通过结合来自互补来源的证据,cnvHiTSeq实现了高基因分型准确性,并在CNV检测灵敏度方面比现有方法有了实质性的提高,同时保持了低错误发现率。cnvHiTSeq可在http://sourceforge.net/projects/cnvhitseq上获得
Recent advances in sequencing technologies provide the means for identifying copy number variation (CNV) at an unprecedented resolution. A single next-generation sequencing experiment offers several features that can be used to detect CNV, yet current methods do not incorporate all available signatures into a unified model. cnvHiTSeq is an integrative probabilistic method for CNV discovery and genotyping that jointly analyzes multiple features at the population level. By combining evidence from complementary sources, cnvHiTSeq achieves high genotyping accuracy and a substantial improvement in CNV detection sensitivity over existing methods, while maintaining a low false discovery rate. cnvHiTSeq is available at http://sourceforge.net/projects/cnvhitseq
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