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: |
1.2 |
Published: |
2013-12-09 |
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 |
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