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Activity Number:
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76
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Type:
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Contributed
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Date/Time:
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Sunday, August 6, 2006 : 8:00 PM to 9:50 PM
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Sponsor:
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Biometrics Section
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| Abstract - #307181 |
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Title:
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Estimating p-Values in Small Microarray Experiments
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Author(s):
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Hyuna Yang*+ and Gary Churchill
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Companies:
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The Jackson Lab and The Jackson Lab
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Address:
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600 Main Street, Box 303, Bar Harbor, ME, 04609,
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Keywords:
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permutation method ; p-value ; microarray experiments
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Abstract:
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Microarray data typically have small numbers of observations per gene. This can result in low power for statistical tests and also presents challenges in assessing significance. Testing procedures that borrow information from all of the genes can improve power but these statistics have non-standard distributions and their significance must be assessed using permutation analysis. When sample sizes are small, the number of distinct permutations can be severely limited and pooling the permutation-derived test statistics across all genes has been proposed. However, this method is not appropriate because the null distribution of the test statistics under permutation is not the same. We propose a permutation based method for estimating p-values using a selected subset of data. This method is shown to have correct type I error rates and to provide accurate estimates of the FDR.
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