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Abstract Details
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Activity Number:
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507
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Type:
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Contributed
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Date/Time:
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Wednesday, August 3, 2011 : 10:30 AM to 12:20 PM
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Sponsor:
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Biometrics Section
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| Abstract - #303233 |
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Title:
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FDR Control for Discrete Test Statistics
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Author(s):
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Isaac Dialsingh*+
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Companies:
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Penn State University
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Address:
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Department of Statistics, University Park, PA, 16801,
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Keywords:
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Family wide error rate ;
False discovery rate ;
Multiple hypothesis testing ;
Discrete test statistics
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Abstract:
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In this talk I present some ways we can control the false discovery rate (FDR) when the test statistics are discrete. When the test statistics are continuous, the distribution of the p-values under the null distribution is Uniform(0,1). This has made it relatively easy to estimate the proportion of true nulls which is a key parameter in estimating and controlling the FDR. When the test statistics are discrete, the Uniform(0,1) assumption under the null hypothesis does not hold. This makes it difficult to estimate the proportion of true nulls. As well, methods that use the p-values to control FDR will be conservative, because not all p-values are achievable. This talk covers methods for estimating the proportion of true nulls and for estimating FDR when the test statistics are discrete. Examples are given using RNA-seq and SNP data.
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Authors who are presenting talks have a * after their name.
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