title: A population model for genotyping indels from next-generation sequence data.
abstract: 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.
authors.affiliation: BGI-Shenzhen, Shenzhen 518083, China.
authors.forename: Haojing
authors.initials: H
authors.lastname: Shao
authors.forename: Evangelos
authors.initials: E
authors.lastname: Bellos
authors.forename: Hanjiudai
authors.initials: H
authors.lastname: Yin
authors.forename: Xiao
authors.initials: X
authors.lastname: Liu
authors.forename: Jing
authors.initials: J
authors.lastname: Zou
authors.forename: Yingrui
authors.initials: Y
authors.lastname: Li
authors.forename: Jun
authors.initials: J
authors.lastname: Wang
authors.forename: Lachlan J M
authors.initials: LJ
authors.lastname: Coin
mesh_terms: D000465:Algorithms; D059472:Exome; D060005:Genotyping Techniques; D059014:High-Throughput Nucleotide Sequencing / Q000379:methods*; D054643:INDEL Mutation; D008957:Models, Genetic; D011153:Population / Q000235:genetics