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DIME: R-package for Identifying Differential ChIP-seq Based on an Ensemble of Mixture Models.
Bioinformatics. 2011 Apr 5;
Authors: Taslim C, Huang T, Lin S
SUMMARY: DIME (Differential Identification using Mixtures Ensemble) 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/. CONTACT: [email protected], [email protected].
PMID: 21471015 [PubMed - as supplied by publisher]
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DIME: R-package for Identifying Differential ChIP-seq Based on an Ensemble of Mixture Models.
Bioinformatics. 2011 Apr 5;
Authors: Taslim C, Huang T, Lin S
SUMMARY: DIME (Differential Identification using Mixtures Ensemble) 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/. CONTACT: [email protected], [email protected].
PMID: 21471015 [PubMed - as supplied by publisher]
More...