A modified two-sample t-test based on permutation method for large-scale data |
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Authors: | Mohsen Salehi Mohammad Mohammadi Mina Aminghafari |
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Affiliation: | 1. Department of Statistics, Faculty of Mathematics and Computer Science, Amirkabir University of Technology (Tehran Polytechnic), Tehran, Iran;2. Department of Statistics, Faculty of Basic Science, Behbahan Khatam Alanbia University of Technology, Iran |
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Abstract: | In large-scale data, for example, analyzing microarray data, which includes hypothesis testing for equality of means in order to discover differentially expressed genes, often deals with a large number of features versus a few number of replicates. Furthermore, some genes are differentially expressed and some others not. Thus, a usual permutation method, which is applied facing these situations, estimates the p-value poorly. This is because two types of genes are mixed. To overcome this obstacle, the null permutation samples are suggested in the literatures. We propose a modified uniformly most powerful unbiased test for testing the null hypothesis. |
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Keywords: | Microarray Data Null Statistic Permutation Test Uniformly Most Powerful Unbiased Test |
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