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A two-stage normalization method for partially degraded mRNA microarray data.

机译:对于部分降解的mRNA基因芯片数据的两步标准化方法。

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MOTIVATION: The goal of the study is to obtain genetic information from exfoliated colonocytes in the fecal stream rather than directly from mucosa cells within the colon. The latter is obtained through invasive procedures. The difficulties encountered by this procedure are that certain probe information may be compromised due to partially degraded mRNA. Proper normalization is essential to obtaining useful information from these fecal array data. RESULTS: We propose a new two-stage semiparametric normalization method motivated by the features observed in fecal microarray data. A location-scale transformation and a robust inclusion step were used to roughly align arrays within the same treatment. A non-parametric estimated non-linear transformation was then used to remove the potential intensity-based biases. We compared the performance of the new method in analyzing a fecal microarray dataset with those achieved by two existing normalization approaches: global median transformation and quantile normalization. The new method favorably compared with the global median and quantile normalization methods. AVAILABILITY: The R codes implementing the two-stage method may be obtained from the corresponding author.
机译:动机:这项研究的目的是从粪便流中脱落的结肠细胞获得遗传信息,而不是直接从结肠内的粘膜细胞获得遗传信息。后者是通过侵入性程序获得的。该程序遇到的困难是某些探针信息可能由于mRNA的部分降解而受到损害。正确的规范化对于从这些粪便阵列数据中获得有用的信息至关重要。结果:我们提出了一种新的两阶段半参数归一化方法,该方法受粪便芯片数据中观察到的特征的影响。位置尺度转换和鲁棒的包含步骤用于在同一处理中大致对齐阵列。然后使用非参数估计的非线性变换来消除潜在的基于强度的偏差。我们将这种新方法在分析粪便微阵列数据集时的性能与通过两种现有的归一化方法实现的性能进行了比较:全局中值变换和分位数归一化。与全局中位数和分位数归一化方法相比,该新方法具有优势。可用性:可以从相应的作者处获得实现两阶段方法的R代码。

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