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首页> 外文期刊>BMC Bioinformatics >Probe-specific mixed-model approach to detect copy number differences using multiplex ligation-dependent probe amplification (MLPA)
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Probe-specific mixed-model approach to detect copy number differences using multiplex ligation-dependent probe amplification (MLPA)

机译:使用多重连接依赖探针扩增(MLPA)的探针特异性混合模型方法来检测拷贝数差异

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摘要

Background MLPA method is a potentially useful semi-quantitative method to detect copy number alterations in targeted regions. In this paper, we propose a method for the normalization procedure based on a non-linear mixed-model, as well as a new approach for determining the statistical significance of altered probes based on linear mixed-model. This method establishes a threshold by using different tolerance intervals that accommodates the specific random error variability observed in each test sample. Results Through simulation studies we have shown that our proposed method outperforms two existing methods that are based on simple threshold rules or iterative regression. We have illustrated the method using a controlled MLPA assay in which targeted regions are variable in copy number in individuals suffering from different disorders such as Prader-Willi, DiGeorge or Autism showing the best performace. Conclusion Using the proposed mixed-model, we are able to determine thresholds to decide whether a region is altered. These threholds are specific for each individual, incorporating experimental variability, resulting in improved sensitivity and specificity as the examples with real data have revealed.
机译:背景MLPA方法是一种潜在有用的半定量方法,用于检测目标区域中的拷贝数变化。在本文中,我们提出了一种基于非线性混合模型的标准化过程的方法,以及一种基于线性混合模型确定变化探针统计意义的新方法。此方法通过使用不同的容差间隔来建立阈值,以适应每个测试样本中观察到的特定随机误差可变性。结果通过仿真研究,我们发现我们提出的方法优于基于简单阈值规则或迭代回归的两种现有方法。我们已经说明了使用受控MLPA分析的方法,其中在患有不同疾病(例如表现出最佳性能的Prader-Willi,DiGeorge或Autism)的个体中,目标区域的拷贝数可变。结论使用提出的混合模型,我们能够确定阈值,以决定区域是否被更改。这些阈值对每个人都是特定的,并结合了实验的可变性,从而提高了灵敏度和特异性,如具有真实数据的实例所揭示的那样。

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