Read count approach for DNA copy number variants detection
Read count approach for DNA copy number variants detection
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DOI：
10.1093/bioinformatics/btr707
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发表时间：
2012-02-15
期刊：
影响因子：
5.8
通讯作者：
Benelli, Matteo
中科院分区：
文献类型：
--
作者：
Magi, Alberto;Tattini, Lorenzo;Benelli, Matteo
动机：高通量测序技术的出现彻底改变了我们发现和基因分型DNA拷贝数变异（CNVs）的能力。基于读取计数的方法能够以前所未有的分辨率检测CNV区域。虽然这种计算策略最近才在文献中被引入，但是对于这类数据的准备、规范化和分析已经做了很多工作。结果：在这里，我们面临着使用读计数方法检测CNVs的许多方面。我们首先研究了读计数分布的特征和系统偏差，重点研究了消除这些偏差的归一化方法。随后，我们比较了用于检测CNVs边界的算法，并研究了读取计数数据预测DNA拷贝精确数量的能力。最后，我们回顾了可公开用于分析读取计数数据的工具。为了更好地了解读取计数方法的最新进展，我们比较了三种最广泛使用的测序技术（Illumina Genome Analyzer， Roche 454和Life technologies SOLiD）在我们执行的所有分析中的性能。
Motivation: The advent of high-throughput sequencing technologies is revolutionizing our ability in discovering and genotyping DNA copy number variants (CNVs). Read count-based approaches are able to detect CNV regions with an unprecedented resolution. Although this computational strategy has been recently introduced in literature, much work has been already done for the preparation, normalization and analysis of this kind of data.Results: Here we face the many aspects that cover the detection of CNVs by using read count approach. We first study the characteristics and systematic biases of read count distributions, focusing on the normalization methods designed for removing these biases. Subsequently, we compare the algorithms designed to detect the boundaries of CNVs and we investigate the ability of read count data to predict the exact number of DNA copy. Finally, we review the tools publicly available for analysing read count data. To better understand the state of the art of read count approaches, we compare the performance of the three most widely used sequencing technologies (Illumina Genome Analyzer, Roche 454 and Life Technologies SOLiD) in all the analyses that we perform.