Resumen
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.
Idioma original | English (US) |
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Número de artículo | btr165 |
Páginas (desde-hasta) | 1569-1570 |
Número de páginas | 2 |
Publicación | Bioinformatics |
Volumen | 27 |
N.º | 11 |
DOI | |
Estado | Published - jun 2011 |
Publicado de forma externa | Sí |
ASJC Scopus subject areas
- Computational Mathematics
- Molecular Biology
- Biochemistry
- Statistics and Probability
- Computer Science Applications
- Computational Theory and Mathematics