The views expressed here are those of the individual authors and not necessarily those of the JSM sponsors, their officers, or their staff.
Online Program Home
Abstract Details
Activity Number:
|
224
|
Type:
|
Topic Contributed
|
Date/Time:
|
Monday, July 30, 2012 : 2:00 PM to 3:50 PM
|
Sponsor:
|
Section on Statistical Computing
|
Abstract - #304759 |
Title:
|
Normalization and Differential Expression in RNA-Seq
|
Author(s):
|
Davide Risso*+ and Sandrine Dudoit
|
Companies:
|
University of California at Berkeley and University of California at Berkeley
|
Address:
|
, , ,
|
Keywords:
|
RNA-Seq ;
Normalization ;
Differential expression ;
Bioconductor
|
Abstract:
|
This talk concerns statistical methods and software for the analysis of RNA abundance by sequencing (RNA-Seq). We first present exploratory data analysis (EDA) approaches for quality assessment/control (QA/QC) of RNA-Seq reads. Next, we propose within-lane normalization methods to adjust for sample-specific gene-level effects such as length and GC-content. We also provide between-lane normalization procedures to account for distributional differences such as sequencing depth. Finally, we consider the quantitation of (differential) gene expression levels using generalized linear models (GLM). This work was motivated by a collaboration with the Sherlock Lab on transcriptome analysis in Saccharomyces. Our exploratory data analysis and normalization methods are implemented in the open-source Bioconductor R package EDASeq (http://www.bioconductor.org).
|
The address information is for the authors that have a + after their name.
Authors who are presenting talks have a * after their name.
Back to the full JSM 2012 program
|
2012 JSM Online Program Home
For information, contact jsm@amstat.org or phone (888) 231-3473.
If you have questions about the Continuing Education program, please contact the Education Department.