Jun 182016
 

baySeq 2.6.0

:: DESCRIPTION

baySeq identifies differential expression in high-throughput ‘count’ data, such as that derived from next-generation sequencing machines, calculating estimated posterior likelihoods of differential expression (or more complex hypotheses) via empirical Bayesian methods.

::DEVELOPER

Thomas J. Hardcastle

:: SCREENSHOTS

N/A

:: REQUIREMENTS

:: DOWNLOAD

 baySeq

:: MORE INFORMATION

Citation

Bioinformatics. 2015 Oct 1. pii: btv569.
Generalised empirical Bayesian methods for discovery of differential data in high-throughput biology.
Hardcastle TJ

BMC Bioinformatics. 2010 Aug 10;11:422. doi: 10.1186/1471-2105-11-422.
baySeq: empirical Bayesian methods for identifying differential expression in sequence count data.
Hardcastle TJ, Kelly KA.

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