This is the program for the 2010 Joint Statistical Meetings in Vancouver, British Columbia.

Abstract Details

Activity Number: 269
Type: Other
Date/Time: Tuesday, August 3, 2010 : 8:30 AM to 10:20 AM
Sponsor: ASA
Abstract - #306396
Title: Statistical Methods for RNA-seq
Author(s): Wing Hung Wong*+
Companies: Stanford University
Address: 390 Serra Mall, Stanford, CA, 94305,

Recently, ultra high-throughput sequencing of RNA (RNA-Seq) has been developed as an approach for transcriptome analysis. By obtaining tens of millions of short reads from the transcript population of interest and by mapping these reads to the genome, RNA-Seq produces digital (counts) rather than analog signals and offers the chance to detect novel transcripts. Because of these desirable features, not shared by qRT-PCR or microarray-based methods, RNA-Seq is widely regarded as an attractive approach to measure transcription in an unbiased and comprehensive manner. However, challenges remain in understanding the source and distribution of the reads, modeling the transcript abundance and developing efficient computational methods for detecting novel splice junctions and isoforms. In this talk, I will discuss some methods that were recently developed to meet these challenges.

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