PeaKDEck: a kernel density estimator-based peak calling program for DNaseI-seq data.
Bioinformatics
; 30(9): 1302-4, 2014 May 01.
Article
en En
| MEDLINE
| ID: mdl-24407222
Hypersensitivity to DNaseI digestion is a hallmark of open chromatin, and DNaseI-seq allows the genome-wide identification of regions of open chromatin. Interpreting these data is challenging, largely because of inherent variation in signal-to-noise ratio between datasets. We have developed PeaKDEck, a peak calling program that distinguishes signal from noise by randomly sampling read densities and using kernel density estimation to generate a dataset-specific probability distribution of random background signal. PeaKDEck uses this probability distribution to select an appropriate read density threshold for peak calling in each dataset. We benchmark PeaKDEck using published ENCODE DNaseI-seq data and other peak calling programs, and demonstrate superior performance in low signal-to-noise ratio datasets.
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Asunto principal:
Análisis de Secuencia de ADN
/
Secuenciación de Nucleótidos de Alto Rendimiento
Idioma:
En
Revista:
Bioinformatics
Asunto de la revista:
INFORMATICA MEDICA
Año:
2014
Tipo del documento:
Article
Pais de publicación:
Reino Unido