A highly efficient and effective motif discovery method for ChIP-seq/ChIP-chip data using positional information.
Nucleic Acids Res
; 40(7): e50, 2012 Apr.
Article
em En
| MEDLINE
| ID: mdl-22228832
ABSTRACT
Identification of DNA motifs from ChIP-seq/ChIP-chip [chromatin immunoprecipitation (ChIP)] data is a powerful method for understanding the transcriptional regulatory network. However, most established methods are designed for small sample sizes and are inefficient for ChIP data. Here we propose a new k-mer occurrence model to reflect the fact that functional DNA k-mers often cluster around ChIP peak summits. With this model, we introduced a new measure to discover functional k-mers. Using simulation, we demonstrated that our method is more robust against noises in ChIP data than available methods. A novel word clustering method is also implemented to group similar k-mers into position weight matrices (PWMs). Our method was applied to a diverse set of ChIP experiments to demonstrate its high sensitivity and specificity. Importantly, our method is much faster than several other methods for large sample sizes. Thus, we have developed an efficient and effective motif discovery method for ChIP experiments.
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Fatores de Transcrição
/
Software
/
Imunoprecipitação da Cromatina
/
Elementos Reguladores de Transcrição
Tipo de estudo:
Evaluation_studies
/
Prognostic_studies
Limite:
Animals
Idioma:
En
Ano de publicação:
2012
Tipo de documento:
Article