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After imputing the missing genotypes using iBLUP, those genotyped SNPs were phased by fastphase (Scheet & Stephens 2006) for further positive selection analysis.
Prior to running GERMLINE we phased the genotype data and imputed missing genotypes using BEAGLE [ 38].
We impute the missing genotypes using the LD information and the haplotype probabilities calculated in the previous section.
Therefore, we imputed missing genotypes using fastphase software [ 20] and obtained complete genotype data for multiple SNPs analysis.
Genome-wide association was performed using GEMMA [ 20] after imputation of missing genotypes using ShapeIT v2 [ 21].
iBLUP is a genotype imputation method that imputes missing genotypes using identity-by-descent and linkage disequilibrium information.
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For multiple QTL mapping, we first calculated genotype probabilities for any missing genotype using the calc.genoprob function before performing the forward/backward model selection function implemented in stepwiseqtl.
The inclusion of the HapMap phase III Mexican American sample as a reference sample, in addition to the HapMap phase II combined sample, produced a marginal improvement both in concordance rate and proportion of non-missing genotypes (99.4% vs. 99.1% for concordance, and 85.9% vs. 85.5% for the proportion of non-missing genotypes, using the single-step approach).
We estimate missing genotypes probabilistically using the Lander-Green or Elston-Stewart algorithms and combine high-resolution SNP genotypes for a subset of individuals in each pedigree with sparser marker data for the remaining individuals.
To obtain this information for all missing genotypes, we used SAMtools v.0.1.12a [ 36].
A random sample of unrelated 100 men and 100 women, excluding individuals with the highest rates of missing genotypes, was used to estimate parameters that were then applied to the remaining subjects.
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