These "true" genotypes could then be compared to the imputed markers arrived at using MACH's most likely genotype call, with anchor SNPs in common between the reference population and "observed" sample.
Imputation accuracies are higher when a larger proportion of haplotypes are shared between the reference population and the validation (imputed) populations.
Both predictions assume no direct pedigree relationships between the reference population and selection candidates and probably underestimate the accuracy achieved in practice.
Other factors that affect the accuracy of imputation include levels of linkage disequilibrium (LD) in the population, the degree of similarity between the reference population and the test population and, to some extent, the size of the reference population [ 7- 10].
The value of SNPs effect estimated for populations other than the reference population depends on the persistence of LD phase between the reference population and the other population [ 28].
This indicates that only 80% of the genetic variance in the selection candidates was captured by the markers in the reference population, due to differences in LD and allele frequencies of QTL between the reference population and the selection candidates.
When the congener profiles were compared between the reference population and the construction workers, the serum levels of the more volatile, lighter PCBs (di-, tri-and tetrachloro, sum of IUPAC# 6 74) were substantially higher among the construction workers.
When the congener profiles were compared between the reference population and the construction workers, the serum levels of the lighter PCBs (di-, tri- and tetrachloro, sum of IUPAC# 6 74) were substantially higher among the construction workers.
Using this approach, the two DUSP22 CpG probes retained the highest differences between the reference population and the pooled AD Braak stage III-IV-V-VI group with a 13.5% and 12.7% DNA methylation difference.
