A population model for genotyping indels from next-generation sequence data

Insertion and deletion polymorphisms (indels) are an important source of genomic variation in plant and animal genomes, but accurate genotyping from low-coverage and exome next-generation sequence data remains challenging. We introduce an efficient population clustering algorithm for diploids and po...

Descripción completa

Detalles Bibliográficos
Autores principales: Shao, Haojing, Bellos, Evangelos, Yin, Hanjiudai, Liu, Xiao, Zou, Jing, Li, Yingrui, Wang, Jun, Coin, Lachlan J. M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2013
Materias:
Methods Online
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3562001/
https://www.ncbi.nlm.nih.gov/pubmed/23221639
http://dx.doi.org/10.1093/nar/gks1143
Descripción
Sumario:Insertion and deletion polymorphisms (indels) are an important source of genomic variation in plant and animal genomes, but accurate genotyping from low-coverage and exome next-generation sequence data remains challenging. We introduce an efficient population clustering algorithm for diploids and polyploids which was tested on a dataset of 2000 exomes. Compared with existing methods, we report a 4-fold reduction in overall indel genotype error rates with a 9-fold reduction in low coverage regions.

Ejemplares similares