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This allows quick estimation of the Q-matrix underpinning a marker dataset as well as the number of founders of that dataset.
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When QTL were simulated using single SNPs dropped from the marker dataset, a simple sliding window performed as well or better than single SNPs or the more sophisticated methods of blocking SNPs into haplotypes.
This marker dataset (359 polymorphic bands) was scored as present (1) or absent (0) and treated as dominant markers.
One hundred SNPs, chosen to minimize pairwise LD and to maximize genetic map coverage, were designated as quantitative trait nucleotides (QTLs) and removed from the marker dataset, leaving 2098 markers for the association mapping analysis.
As before, single SNPs were used to simulate QTL, but in this case the causal SNPs were left in the marker dataset so a marker in complete LD with the QTL always existed.
After this filtering process, the marker dataset comprised 44 809 markers.
In order to conduct the molecular dating analyses we used the same 12-marker molecular dataset as [ 33].
Therefore, these RSMs are considered as LD-free marker datasets.
These results confirm the robustness of admixture-based approach and its usability for datasets as small as 500 ancestry informative markers (markers whose frequencies are significantly different, between two or more populations).
The analysis of these studies requires merging across GWAS datasets as well as patient and marker selection.
Furthermore, we want to demonstrate the specificity as well as sensitivity of iLOCi for detecting multiple interacting disease marker pairs as would be present in a real dataset.
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