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Abstract Details
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Activity Number:
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559
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Type:
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Topic Contributed
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Date/Time:
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Wednesday, August 1, 2012 : 2:00 PM to 3:50 PM
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Sponsor:
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IMS
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| Abstract - #304868 |
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Title:
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Estimating Gene Expression Levels Using RNA-Seq Short Reads
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Author(s):
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David Dalpiaz*+ and Ping Ma
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Companies:
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and University of Illinois at Urbana-Champaign
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Address:
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612 Breen, Champaign, IL, 61820, United States
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Keywords:
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RNA-Seq ;
Next-generation sequencing ;
gene expression
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Abstract:
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RNA-Seq, which has become a popular tool for transcriptome analysis in cancer research, is a high throughput, next-generation sequencing technology that produces tens of millions of short reads. When mapped to the genome or reference transcripts, RNA-Seq data can be summarized by a very large number of short-read counts. From these read counts, estimating gene expression is important in further analysis such as detecting differentially expressed genes. We compare several estimation methods, including a proposed method using sample second moments. For comparison the methods are applied to several real datasets.
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