This is the program for the 2010 Joint Statistical Meetings in Vancouver, British Columbia.
Abstract Details
Activity Number:
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623
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Type:
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Contributed
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Date/Time:
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Thursday, August 5, 2010 : 8:30 AM to 10:20 AM
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Sponsor:
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Biometrics Section
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Abstract - #307259 |
Title:
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Model-Based Clustering for RNA-Seq Data
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Author(s):
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Yaqing Si*+ and Peng Liu
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Companies:
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Iowa State University and Iowa State University
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Address:
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Snedecor 2418, Ames, IA, 50011,
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Keywords:
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Model-Based Clustering ;
RNA-Seq Data ;
Hierarchical Clustering ;
Gene-Expression
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Abstract:
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Next-generation sequencing technology has been exploited to measure the gene expression (mRNA) level and the resulting RNA-seq data set is an ultra-high-dimensional discrete data set. Clustering methods have been helpful in interpreting high-dimensional gene expression data resulting from microarray experiments. Here we evaluate clustering methods for RNA-seq data and also propose a model-based clustering algorithm. Real data analysis shows that the proposed algorithm has more agreement with gene annotations than other commonly used methods. We also show how to build a hierarchical tree for the clusters.
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