A hybrid method for the imputation of genomic data in livestock populations

Abstract

BackgroundThis paper describes a combined heuristic and hidden Markov model (HMM) method to accurately impute missing genotypes in livestock datasets. Genomic selection in breeding programs requires high-density genotyping of many individuals, making algorithms that economically generate this information crucial. There are two common classes of imputation methods, heuristic methods and probabilistic methods, the latter being largely based on hidden Markov models. Heuristic methods are robust, but fail to impute markers in regions where the thresholds of heuristic rules are not met, or the pedigree is inconsistent. Hidden Markov models are probabilistic methods which typically do not require specific family structures or pedigree information, making them very flexible, but they are computationally expensive and, in some cases, less accurate.ResultsWe implemented a new hybrid imputation method that combined heuristic and HMM methods, AlphaImpute and MaCH, and compared the computation time and imputation accuracy of the three methods. AlphaImpute was the fastest, followed by the hybrid method and then the HMM. The computation time of the hybrid method and the HMM increased linearly with the number of iterations used in the hidden Markov model, however, the computation time of the hybrid method increased almost linearly and that of the HMM quadratically with the number of template haplotypes. The hybrid method was the most accurate imputation method for low-density panels when pedigree information was missing, especially if minor allele frequency was also low. The accuracy of the hybrid method and the HMM increased with the number of template haplotypes. The imputation accuracy of all three methods increased with the marker density of the low-density panels. Excluding the pedigree information reduced imputation accuracy for the hybrid method and AlphaImpute. Finally, the imputation accuracy of the three methods decreased with decreasing minor allele frequency.ConclusionsThe hybrid heuristic and probabilistic imputation method is able to impute all markers for all individuals in a population, as the HMM. The hybrid method is usually more accurate and never significantly less accurate than a purely heuristic method or a purely probabilistic method and is faster than a standard probabilistic method.Electronic supplementary materialThe online version of this article (doi:10.1186/s12711-017-0300-y) contains supplementary material, which is available to authorized users.

Potential of Low‐Coverage Genotyping‐by‐Sequencing and Imputation for Cost‐Effective Genomic Selection in Biparental Segregating Populations

“…The low‐coverage GBS data had many data points with no or few sequence reads. To increase the quantity and quality of this data, we used the modified Hidden Markov Model of Li et al (2010) as implemented in the AlphaImpute program version 1.3 (Hickey et al, 2012b; Antolin et al, 2017), available at http://www.alphagenes.roslin.ed.ac.uk/AlphaSuite/AlphaImpute. Each family and chromosome was imputed independently.…”

Siccuracy: An R-package for executing genotype imputation strategy simulations with AlphaImpute

“…The main motivation for this R-package was to provide a standardized and tested set of routines in R 28 for genotype imputation with AlphaImpute (Hickey et al 2011;Hickey, Kinghorn, et al 2012;29 4 / 33 Browning 2007), SHAPE-IT (Delaneau et al 2011), Impute2 (Howie et al 2009), MaCH (Li et al 52 2010), MERLIN (Abecasis et al 2002), cnF2freq (Nettelblad et al 2009), and AlphaImpute (Hickey 53 et al 2011;Hickey, Kinghorn, et al 2012; Antolín et al 2017). These rely on heuristic or 54 probabilistic models to infer the missing genotypes by identifying the most probable haplotype (i.e.…”

“…This paper will however not 60 discuss the advantages and performances of the available imputation software packages, but refer to 61 e.g. Ma et al (2013) or Antolín et al (2017) for this. 62…”

Accuracy of genotype imputation in Labrador Retrievers

“…Pedigree‐based methods make inferences between closely related individuals to identify shared haplotypes (Antolín et al . ) and thus provide an alternative source of information when the genotyped SNPs are not sufficiently informative.…”