DIME: DIME (Differential Identification using Mixture Ensemble)

A robust differential identification method that considers an ensemble of finite mixture models combined with a local false discovery rate (fdr) to analyze ChIP-seq (high-throughput genomic)data comparing two samples allowing for flexible modeling of data.

Version: 1.0
Published: 2011-03-10
Author: Cenny Taslim, with contributions from Dustin Potter, Abbasali Khalili and Shili Lin.
Maintainer: Cenny Taslim <taslim.2 at osu.edu>
License: GPL (≥ 2)
CRAN checks: DIME results

Downloads:

Package source: DIME_1.0.tar.gz
MacOS X binary: DIME_1.0.tgz
Windows binary: DIME_1.0.zip
Reference manual: DIME.pdf