Conditional random pattern model for copy number aberration detection.
Conditional random pattern model for copy number aberration detection.
复制标题
DOI：
10.1186/1471-2105-11-200
复制
发表时间：
2010-04-22
影响因子：
3
通讯作者：
Wong ST
中科院分区：
文献类型：
--
作者：
Li F;Zhou X;Huang W;Chang CC;Wong ST
DNA拷贝数畸变（CNA）在肿瘤等疾病的发生中起着重要作用。例如，CNA可能导致抑癌基因的抑制和癌基因的激活，这将导致某些类型的癌症。高密度单核苷酸多态性（SNP）阵列数据被广泛用于CNA检测。然而，自动检测CNA是不平凡的，因为从高密度SNP阵列获得的信号通常具有低信噪比（SNR），这可能是由全基因组扩增、正常细胞和肿瘤细胞的混合、实验噪声或其他技术限制引起的。随着信噪比的降低，许多虚假的CNA区域往往被检测到，而真正的CNA区域被错过。因此，需要更复杂的统计模型来使得使用低SNR信号的CNA检测更加鲁棒和可靠。本文提出了一种条件随机模式（CRP）的CNA检测模型，其中大量的上下文线索，以抑制噪声，提高CNA检测精度。模拟和真实的数据都被用来评估所提出的模型，和验证结果表明，CRP模型是更强大的和可靠的，在存在噪声的CNA检测使用高密度SNP阵列数据，相比一些广泛使用的软件包。所提出的条件随机模式（CRP）模型可以有效地检测CNA区域存在噪声。
DNA copy number aberration (CNA) is very important in the pathogenesis of tumors and other diseases. For example, CNAs may result in suppression of anti-oncogenes and activation of oncogenes, which would cause certain types of cancers. High density single nucleotide polymorphism (SNP) array data is widely used for the CNA detection. However, it is nontrivial to detect the CNA automatically because the signals obtained from high density SNP arrays often have low signal-to-noise ratio (SNR), which might be caused by whole genome amplification, mixtures of normal and tumor cells, experimental noise or other technical limitations. With the reduction in SNR, many false CNA regions are often detected and the true CNA regions are missed. Thus, more sophisticated statistical models are needed to make the CNAs detection, using the low SNR signals, more robust and reliable. This paper presents a conditional random pattern (CRP) model for CNA detection where much contextual cues are explored to suppress the noise and improve CNA detection accuracy. Both simulated and the real data are used to evaluate the proposed model, and the validation results show that the CRP model is more robust and reliable in the presence of noise for CNA detection using high density SNP array data, compared to a number of widely used software packages. The proposed conditional random pattern (CRP) model could effectively detect the CNA regions in the presence of noise.
登录
查看更多内容
影响因子：
9.8
作者：
Friedman, J. M.;Baross, Agnes;Marra, Marco A.
通讯作者：
Marra, Marco A.
影响因子：
2.1
作者：
Olshen, AB;Venkatraman, ES;Wigler, M
通讯作者：
Wigler, M
影响因子：
2.7
作者：
Germing, U;Gattermann, N;Aul, C
通讯作者：
Aul, C
DOI：
10.1073/pnas.162471999
发表时间：
2002-10-01
影响因子：
11.1
作者：
Pollack, JR;Sorlie, T;Brown, PO
通讯作者：
Brown, PO
影响因子：
9.8
作者：
Assie, Guillaume;LaFramboise, Thomas;Eng, Charis
通讯作者：
Eng, Charis