Generation of Synthetic Transcriptome Data with Defined Statistical Properties for the Development and Testing of New Analysis Methods


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We have previously developed a combined signal/variance distribution model that accounts for the particular statistical properties of datasets generated on the Applied Biosystems AB1700 transcriptome system. Here we show that this model can be efficiently used to generate synthetic datasets with statistical properties virtually identical to those of the actual data by aid of the JAVA application ace.map creator 1.0 that we have developed. The fundamentally different structure of AB1700 transcriptome profiles requires re-evaluation, adaptation, or even redevelopment of many of the standard microarray analysis methods in order to avoid misinterpretation of the data on the one hand, and to draw full benefit from their increased specificity and sensitivity on the other hand. Our composite data model and the ace.map creator 1.0 application thereby not only present proof of the correctness of our parameter estimation, but also provide a tool for the generation of synthetic test data that will be useful for further development and testing of analysis methods.
机译:我们之前已经开发了一种组合的信号/方差分布模型,该模型说明了Applied Biosystems AB1700转录组系统上生成的数据集的特殊统计属性。在这里,我们证明了借助我们开发的JAVA应用程序ace.map creator 1.0,该模型可以有效地用于生成统计属性与实际数据几乎完全相同的合成数据集。 AB1700转录组图谱的根本不同结构要求重新评估,改编或什至重新开发许多标准微阵列分析方法,以便一方面避免对数据的误解,并从其更高的特异性和敏感性中获得最大收益另一方面。因此,我们的复合数据模型和ace.map creator 1.0应用程序不仅提供了我们参数估计正确性的证明,而且还提供了用于生成综合测试数据的工具,这对于进一步开发和测试分析方法很有用。


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