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

Documentation:

Reference manual:

DIME.pdf

Downloads:

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, r-oldrel (x86_64): DIME_1.3.0.tgz
Old sources:	DIME archive

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