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A Survey and Comparative Study of Statistical Tests for Identifying Differential Expressionfrom Microarray Data

机译：从微阵列数据识别差异表达的统计测试的调查和比较研究

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摘要

DNA microarray is a powerful technology that can simultaneously determine the levels of thousands of transcripts (generated, for example, from genes/miRNAs) across different experimental conditions or tissue samples. The motto of differential expression analysis is to identify the transcripts whose expressions change significantly across different types of samples or experimental conditions. A number of statistical testing methods are available for this purpose. In this paper, we provide a comprehensive survey on different parametric and non-parametric testing methodologies for identifying differential expression from microarray data sets. The performances of the different testing methods have been compared based on some real-life miRNA and mRNA expression data sets. For validating the resulting differentially expressed miRNAs, the outcomes of each test are checked with the information available for miRNA in the standard miRNA database PhenomiR 2.0. Subsequently, we have prepared different simulated data sets of different sample sizes (from 10 to 100 per group/population) and thereafter the power of each test have been calculated individually. The comparative simulated study might lead to formulate robust and comprehensive judgements about the performance of each test in the basis of assumption of data distribution. Finally, a list of advantages and limitations of the different statistical tests has been provided, along with indications of some areas where further studies are required.
机译：DNA微阵列是一项强大的技术，可以同时确定不同实验条件或组织样品中成千上万个转录本的水平（例如，从基因/ miRNA生成）。差异表达分析的座右铭是鉴定在不同类型的样品或实验条件下其表达发生显着变化的转录本。为此目的，可以使用多种统计测试方法。在本文中，我们提供了有关不同参数和非参数测试方法的综合调查，以从微阵列数据集中识别差异表达。基于一些现实生活中的miRNA和mRNA表达数据集，比较了不同测试方法的性能。为了验证产生的差异表达的miRNA，使用标准miRNA数据库PhenomiR 2.0中可用于miRNA的信息检查每个测试的结果。随后，我们准备了不同样本量（每组/每组10到100）的不同模拟数据集，然后分别计算了每个测试的功效。对比模拟研究可能会导致在假设数据分布的基础上对每种测试的性能做出可靠而全面的判断。最后，提供了各种统计测试的优缺点的清单，以及一些需要进一步研究的领域的迹象。

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