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

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

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/.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Algorithms
  • Binding Sites
  • Cell Line, Tumor
  • Chromatin Immunoprecipitation / methods*
  • DNA-Binding Proteins / analysis
  • Humans
  • Models, Statistical
  • Sequence Analysis, DNA
  • Software*

Substances

  • DNA-Binding Proteins