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 <taslim.2@osu.edu>, with contributions from Dustin Potter, Abbasali Khalili and Shili Lin <shili@stat.osu.edu>.
MaintainerCenny Taslim <taslim.2@osu.edu>
LicenseGPL (>= 2)
Package repositoryView on CRAN
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DIME documentation built on May 2, 2019, 5:27 a.m.