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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 |
DOI: | 10.32614/CRAN.package.DIME |
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, r-oldrel (x86_64): DIME_1.3.0.tgz |
Old sources: | DIME archive |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.