JSM 2014 Home
Online Program Home
My Program

Abstract Details

Activity Number: 338
Type: Contributed
Date/Time: Tuesday, August 5, 2014 : 10:30 AM to 12:20 PM
Sponsor: Section on Bayesian Statistical Science
Abstract #312135 View Presentation
Title: HmmSeq: A Hidden Markov Model for Detecting Differentially Expressed Genes from RNA-Seq Data
Author(s): Shiqi Cui*+ and Subharup Guha and Marco A.R. Ferreira and Allison Tegge
Companies: University of Missouri-Columbia and University of Missouri and University of Missouri and University of Missouri-Columbia
Keywords: Bayesian hierarchical model ; first order dependence ; next-generation sequencing ; overdispersion ; serial correlation
Abstract:

We introduce hmmSeq, a model-based hierarchical Bayesian technique for detecting differentially expressed genes from RNA-seq data. Our novel hmmSeq methodology uses hidden Markov models to account for potential co-expression of neighboring genes. In addition, hmmSeq employs an integrated approach to studies with technical or biological replicates, automatically adjusting for any extra-Poisson variability. Moreover, for cases when paired data are available, hmmSeq includes a paired structure between treatments that incoporates subject-specific effects. To perform parameter estimation for the hmmSeq model, we develop an efficient Markov chain Monte Carlo algorithm. Further, we develop a procedure for detection of differentially expressed genes that automatically controls false discovery rate. A simulation study shows that the hmmSeq methodology performs better than competitors in terms of receiver operating characteristic curves. Finally, the analyses of three publicly available RNA-Seq datasets demonstrate the power and flexibility of the hmmSeq methodology. An R package implementing the hmmSeq framework is provided upon request.


Authors who are presenting talks have a * after their name.

Back to the full JSM 2014 program




2014 JSM Online Program Home

For information, contact jsm@amstat.org or phone (888) 231-3473.

If you have questions about the Professional Development program, please contact the Education Department.

The views expressed here are those of the individual authors and not necessarily those of the JSM sponsors, their officers, or their staff.

ASA Meetings Department  •  732 North Washington Street, Alexandria, VA 22314  •  (703) 684-1221  •  meetings@amstat.org
Copyright © American Statistical Association.