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Abstract Details

Activity Number: 559
Type: Topic Contributed
Date/Time: Wednesday, August 1, 2012 : 2:00 PM to 3:50 PM
Sponsor: IMS
Abstract - #304868
Title: Estimating Gene Expression Levels Using RNA-Seq Short Reads
Author(s): David Dalpiaz*+ and Ping Ma
Companies: and University of Illinois at Urbana-Champaign
Address: 612 Breen, Champaign, IL, 61820, United States
Keywords: RNA-Seq ; Next-generation sequencing ; gene expression

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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