The use of family relationships and linkage disequilibrium to impute phase and missing genotypes in up to whole-genome sequence density genotypic data.

A novel method, called linkage disequilibrium multilocus iterative peeling (LDMIP), for the imputation of phase and missing genotypes is developed. LDMIP performs an iterative peeling step for every locus, which accounts for the family data, and uses a forward-backward algorithm to accumulate information across loci. Marker similarity between haplotype pairs is used to impute possible missing genotypes and phases, which relies on the linkage disequilibrium between closely linked markers. After this imputation step, the combined iterative peeling/forward-backward algorithm is applied again, until convergence. The calculations per iteration scale linearly with number of markers and number of individuals in the pedigree, which makes LDMIP well suited to large numbers of markers and/or large numbers of individuals. Per iteration calculations scale quadratically with the number of alleles, which implies biallelic markers are preferred. In a situation with up to 15% randomly missing genotypes, the error rate of the imputed genotypes was <1% and approximately 99% of the missing genotypes were imputed. In another example, LDMIP was used to impute whole-genome sequence data consisting of 17,321 SNPs on a chromosome. Imputation of the sequence was based on the information of 20 (re)sequenced founder individuals and genotyping their descendants for a panel of 3000 SNPs. The error rate of the imputed SNP genotypes was 10%. However, if the parents of these 20 founders are also sequenced, >99% of missing genotypes are imputed correctly.