Efficient imputation of missing markers in low-coverage genotyping-by-sequencing data from multiparental crosses

B Emma Huang; Chitra Raghavan; Ramil Mauleon; Karl W Broman; Hei Leung

doi:10.1534/genetics.113.158014

Efficient imputation of missing markers in low-coverage genotyping-by-sequencing data from multiparental crosses

Genetics. 2014 May;197(1):401-4. doi: 10.1534/genetics.113.158014. Epub 2014 Feb 28.

Authors

B Emma Huang¹, Chitra Raghavan, Ramil Mauleon, Karl W Broman, Hei Leung

Affiliation

¹ Computational Informatics and Food Futures Flagship, Commonwealth Scientific and Industrial Research Organization, Dutton Park, Queensland, Australia 4102.

Abstract

We consider genomic imputation for low-coverage genotyping-by-sequencing data with high levels of missing data. We compensate for this loss of information by utilizing family relationships in multiparental experimental crosses. This nearly quadruples the number of usable markers when applied to a large rice Multiparent Advanced Generation InterCross (MAGIC) study.

Keywords: GBS; HMM; MAGIC; MPRIL.

Publication types

Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't

MeSH terms

Biostatistics / methods*
Genetic Markers / genetics*
Genomics
Genotyping Techniques*
Hybridization, Genetic*
Oryza / genetics
Sequence Analysis*

Substances

Genetic Markers

Grants and funding

R01 GM074244/GM/NIGMS NIH HHS/United States