DIME: Differential Identification using Mixture Ensemble

A robust identification of differential binding sites method for analyzing ChIP-seq (Chromatin Immunoprecipitation Sequencing) comparing two samples that considers an ensemble of finite mixture models combined with a local false discovery rate (fdr) allowing for flexible modeling of data. Methods for Differential Identification using Mixture Ensemble (DIME) is described in: Taslim et al., (2011) <doi:10.1093/bioinformatics/btr165>.

Version: 1.3.0
Published: 2022-05-09
Author: Cenny Taslim, with contributions from Dustin Potter, Abbasali Khalili and Shili Lin.
Maintainer: Cenny Taslim <taslim.2 at osu.edu>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: yes
CRAN checks: DIME results


Reference manual: DIME.pdf


Package source: DIME_1.3.0.tar.gz
Windows binaries: r-devel: DIME_1.3.0.zip, r-release: DIME_1.3.0.zip, r-oldrel: DIME_1.3.0.zip
macOS binaries: r-release (arm64): DIME_1.3.0.tgz, r-oldrel (arm64): DIME_1.3.0.tgz, r-release (x86_64): DIME_1.3.0.tgz
Old sources: DIME archive


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