DIME (1.1)

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.

Maintainer: Cenny Taslim
Author(s): Cenny Taslim <taslim.2@osu.edu>, with contributions from Dustin Potter, Abbasali Khalili and Shili Lin <shili@stat.osu.edu>.

License: GPL (>= 2)

Uses: Does not use any package
Reverse depends: BOG

Released about 7 years ago.