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) |
|---|---|
| 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