A population model for genotyping indels from next-generation sequence data
Haojing Shao, Evangelos Bellos, Hanjiudai Yin, Xiao Liu, Jing Zou, Yingrui Li, Jun Wang, Lachlan JM Coin
NUCLEIC ACIDS RESEARCH | OXFORD UNIV PRESS | Published : 2013
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.
Awarded by Major State Basic Research Development Program of China-973 Program
Awarded by National Natural Science Foundation of China
Awarded by Shenzhen Key Laboratory of Transomics Biotechnologies
Awarded by BBSRC
Awarded by Biotechnology and Biological Sciences Research Council
Major State Basic Research Development Program of China-973 Program [2011CB809201, 2011CB809202, 2011CB809203]; Major Program of National Natural Science Foundation of China ; Shenzhen Key Laboratory of Transomics Biotechnologies [CXB201108250096A]; the BBSRC research grant [award number BB/H024808/1 to L.J.M.C. and E. B.]. Funding for open access charge: Imperial College open access fund.