CoNVEX: copy number variation estimation in exome sequencing data using HMM.
CoNVEX: copy number variation estimation in exome sequencing data using HMM.
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DOI：
10.1186/1471-2105-14-s2-s2
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发表时间：
2013
影响因子：
3
通讯作者：
Halgamuge SK
中科院分区：
文献类型：
--
作者：
Amarasinghe KC;Li J;Halgamuge SK
癌症中的主要遗传变异类型之一是拷贝数变异（CNV）。全外显子组测序（WES）是研究疾病特异性基因组变异的一种流行的全基因组测序（WGS）替代方法。然而，使用WES数据在癌症样本中发现CNV尚未得到充分探索。我们提出了一种新的方法，称为CoNVEX，估计拷贝数的变化，在整个外显子组测序数据。它使用每个外显子区域的肿瘤和匹配的正常平均读取深度的比率来预测拷贝获得或丢失。WES数据产生的有用信号将受到数据本身固有噪声的阻碍。这限制了其用作高度可靠的CNV检测源的能力。在这里，我们提出了一种方法，包括离散小波变换（DWT），以减少噪音。通过隐马尔可夫模型（HMM）进行每个靶向区域的拷贝数增加/损失的鉴定。HMM经常用于识别由各种技术产生的数据中的CNV，包括阵列比较基因组杂交（aCGH）和WGS。在这里，我们提出了一种隐马尔可夫模型来检测癌症外显子组数据中的CNV。我们使用修改后的数据从1000个基因组计划，以评估所提出的方法的性能。使用这些数据，我们已经证明CoNVEX在精度方面明显优于现有方法。总体而言，CoNVEX的灵敏度超过92%，精确度超过50%。
One of the main types of genetic variations in cancer is Copy Number Variations (CNV). Whole exome sequenicng (WES) is a popular alternative to whole genome sequencing (WGS) to study disease specific genomic variations. However, finding CNV in Cancer samples using WES data has not been fully explored. We present a new method, called CoNVEX, to estimate copy number variation in whole exome sequencing data. It uses ratio of tumour and matched normal average read depths at each exonic region, to predict the copy gain or loss. The useful signal produced by WES data will be hindered by the intrinsic noise present in the data itself. This limits its capacity to be used as a highly reliable CNV detection source. Here, we propose a method that consists of discrete wavelet transform (DWT) to reduce noise. The identification of copy number gains/losses of each targeted region is performed by a Hidden Markov Model (HMM). HMM is frequently used to identify CNV in data produced by various technologies including Array Comparative Genomic Hybridization (aCGH) and WGS. Here, we propose an HMM to detect CNV in cancer exome data. We used modified data from 1000 Genomes project to evaluate the performance of the proposed method. Using these data we have shown that CoNVEX outperforms the existing methods significantly in terms of precision. Overall, CoNVEX achieved a sensitivity of more than 92% and a precision of more than 50%.