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Bioinformatics. 2011 Jun 1;27(11):1569-70. doi: 10.1093/bioinformatics/btr165. Epub 2011 Apr 5.

DIME: R-package for identifying differential ChIP-seq based on an ensemble of mixture models.

Author information

  • 1Department of Molecular Virology, Immunology and Medical Genetics and Department of Statistics, The Ohio State University, Columbus, OH 43210, USA.

Abstract

SUMMARY:

Differential Identification using Mixtures Ensemble (DIME) is a package for identification of biologically significant differential binding sites between two conditions using ChIP-seq data. It 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.

AVAILABILITY AND IMPLEMENTATION:

DIME is implemented as an R-package, which is available at http://www.stat.osu.edu/~statgen/SOFTWARE/DIME. It may also be downloaded from http://cran.r-project.org/web/packages/DIME/.

PMID:
21471015
[PubMed - indexed for MEDLINE]
PMCID:
PMC3102220
Free PMC Article

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