Abstract Details
Activity Number:
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159
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Type:
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Topic Contributed
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Date/Time:
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Monday, August 4, 2014 : 10:30 AM to 12:20 PM
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Sponsor:
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Biometrics Section
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Abstract #312656
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Title:
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A Robust Method for Correlated RNA Sequence Data
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Author(s):
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Jinfeng Xu*+ and Hong Zhang
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Companies:
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and Fudan University
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Keywords:
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Count data ;
RNA ;
Poisson
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Abstract:
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We propose a model for analyzing correlated RNA sequence data by specifying a general mean-variance formula. It naturally extends the existing models and provides a more flexible tool. Fast algorithms are developed for its numerical implementation. Extensive simulation studies show that the approach exhibits superior robustness properties and perform favorably under a variety of settings. However, the competing approaches perform well only when their restrictive assumptions are met. In the real data applications, the new method also yields more interesting results.
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Authors who are presenting talks have a * after their name.
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