Dominant loci

For some types of genetic markers, it is not possible to distinguish all the genotypes (eg, genotypes AA and Aa look the same on the gel, while aa is different). I have not implemented anything specific for this type of data, however the program can be applied to such data under the ``no admixture'' model (set NOADMIX=1). This can done by treating each class of genotypes as being, effectively, a haploid allele. Then we might designate an AA/Aa individual in the input file as (1,-9), and an aa individual as (2,-9), where -9 is the value used for missing data. This approach can also be used for more than two genotypic classes. This fix is valid under the no-admixture model, because the updates for $P$ and $Q$ are still correct even though we are treating genotypic classes rather than alleles. Of course, there is less information than if all the genotypes could be distinguished. This fix is not formally correct under the admixture model, however it seems plausible that admixture estimates may be reasonably unbiased in this situation too, especially if there are lots of loci. We have not looked at this.