title: DIME: R-package for identifying differential ChIP-seq based on an ensemble of mixture models.
abstract: CONCLUSIONS
  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.
  
  
  METHODS
  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/.
authors.affiliation: Department of Molecular Virology, Immunology and Medical Genetics and Department of Statistics, The Ohio State University, Columbus, OH 43210, USA.
authors.forename: Cenny
authors.initials: C
authors.lastname: Taslim
authors.forename: Tim
authors.initials: T
authors.lastname: Huang
authors.forename: Shili
authors.initials: S
authors.lastname: Lin
mesh_terms: D000465:Algorithms; D001665:Binding Sites; D045744:Cell Line, Tumor; D047369:Chromatin Immunoprecipitation / Q000379:methods*; D004268:DNA-Binding Proteins / Q000032:analysis; D006801:Humans; D015233:Models, Statistical; D017422:Sequence Analysis, DNA; D012984:Software
chemical_list: D004268:DNA-Binding Proteins