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Differential Identification using Mixtures Ensemble DIME

A package for identification of biologically significant differential binding sites between two conditions using ChIP-seq data. DIME considers a collection of finite mixture models combined with a false discovery rate (FDR) criterion to find statistically significant regions. This leads to a more reliable assessment of differential binding sites based on a statistical approach. In addition to ChIP-seq, DIME is also applicable to data from other high-throughput platforms.

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DIME classification

DIME specifications

Software type:
Restrictions to use:
Output data:
The output of DIME is a list containing four elements each corresponding to the results of the overall best model or those of an individual class.
Programming languages:
Computer skills:
Command line interface
Input data:
An R list that contains normalized differences for chromosome(s) that need to be analyzed.
Operating system:
Unix/Linux, Mac OS, Windows
GNU General Public License version 2.0

DIME distribution


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DIME support



  • Cenny Taslim <>


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Department of Molecular Virology, Immunology and Medical Genetics, The Ohio State University, Columbus, OH, USA; Department of Statistics, The Ohio State University, Columbus, OH, USA

Funding source(s)

This work was supported in part by National Cancer Institute (grant U54CA113001) and National Science Foundation (grant DMS-1042946).

Link to literature

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