An integrative probabilistic model for identification of structural variation in sequencing data.
Genome Biol
; 13(3): R22, 2012.
Article
en En
| MEDLINE
| ID: mdl-22452995
ABSTRACT
Paired-end sequencing is a common approach for identifying structural variation (SV) in genomes. Discrepancies between the observed and expected alignments indicate potential SVs. Most SV detection algorithms use only one of the possible signals and ignore reads with multiple alignments. This results in reduced sensitivity to detect SVs, especially in repetitive regions. We introduce GASVPro, an algorithm combining both paired read and read depth signals into a probabilistic model which can analyze multiple alignments of reads. GASVPro outperforms existing methods with a 50-90% improvement in specificity on deletions and a 50% improvement on inversions.
Texto completo:
1
Colección:
01-internacional
Banco de datos:
MEDLINE
Asunto principal:
Variación Genética
/
Genoma Humano
/
Modelos Estadísticos
Tipo de estudio:
Diagnostic_studies
/
Risk_factors_studies
Límite:
Humans
Idioma:
En
Revista:
Genome Biol
Asunto de la revista:
BIOLOGIA MOLECULAR
/
GENETICA
Año:
2012
Tipo del documento:
Article
País de afiliación:
Estados Unidos