title: Genotype imputation via matrix completion.
abstract: Most current genotype imputation methods are model-based and computationally intensive, taking days to impute one chromosome pair on 1000 people. We describe an efficient genotype imputation method based on matrix completion. Our matrix completion method is implemented in MATLAB and tested on real data from HapMap 3, simulated pedigree data, and simulated low-coverage sequencing data derived from the 1000 Genomes Project. Compared with leading imputation programs, the matrix completion algorithm embodied in our program MENDEL-IMPUTE achieves comparable imputation accuracy while reducing run times significantly. Implementation in a lower-level language such as Fortran or C is apt to further improve computational efficiency.
authors.affiliation: Department of Human Genetics, University of California, Los Angeles, CA 90095, USA. ecchi@ucla.edu
authors.forename: Eric C
authors.initials: EC
authors.lastname: Chi
authors.forename: Hua
authors.initials: H
authors.lastname: Zhou
authors.forename: Gary K
authors.initials: GK
authors.lastname: Chen
authors.forename: Diego Ortega
authors.initials: DO
authors.lastname: Del Vecchyo
authors.forename: Kenneth
authors.initials: K
authors.lastname: Lange
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D003198:Computer Simulation; D015894:Genome, Human; D005838:Genotype; D060148:HapMap Project; D006801:Humans; D046228:Microarray Analysis; D008957:Models, Genetic; D020641:Polymorphism, Single Nucleotide; D012984:Software