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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:
Package/Module
Restrictions to use:
None
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:
R
Computer skills:
Advanced
Stability:
Stable
Interface:
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
License:
GNU General Public License version 2.0
Version:
1.2
Maintained:
Yes

DIME distribution

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DIME support

Documentation

Maintainer

  • Cenny Taslim <>

Credits

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Publications

Institution(s)

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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