Empirical Bayesian analysis of paired high-throughput sequencing data with a beta-binomial distribution.

ABSTRACT:

Background

Pairing of samples arises naturally in many genomic experiments; for example, gene expression in tumour and normal tissue from the same patients. Methods for analysing high-throughput sequencing data from such experiments are required to identify differential expression, both within paired samples and between pairs under different experimental conditions.

Results

We develop an empirical Bayesian method based on the beta-binomial distribution to model paired data from high-throughput sequencing experiments. We examine the performance of this method on simulated and real data in a variety of scenarios. Our methods are implemented as part of the RbaySeq package (versions 1.11.6 and greater) available from Bioconductor (http://www.bioconductor.org).

Conclusions

SUBMITTER: Hardcastle TJ 

PROVIDER: S-EPMC3658937 | biostudies-literature | 2013 Apr

REPOSITORIES: biostudies-literature