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.

Package details

AuthorCenny Taslim <[email protected]>, with contributions from Dustin Potter, Abbasali Khalili and Shili Lin <[email protected]>.
MaintainerCenny Taslim <[email protected]>
LicenseGPL (>= 2)
Package repositoryView on CRAN
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DIME documentation built on May 29, 2017, 6:25 p.m.