I have binomial data representing the frequency of a trait (genetic marker) from 98 sites in Sweden. This allele is associated with populations living in the mountainous NW part of the country. These mountains run north to south along the Norwegian border. Sites in the mountains are nearly fixed for this allele and sites in the lowlands and coast to the east lack the allele. At the south end of the mountains is a hybrid zone and a region of low abundance for the species. Despite the mountains continuing south through the hybrid zone, the allele frequency shifts from nearly fixed for the allele to becoming nearly absent. This suggests that despite the assumed strong selection for this trait in the mountains, that there is a barrier for it in the hybrid zone preventing its spread south along the mountains.

I have used a simple glm approach in R to identify that yes, altitude is an extremely significant predictor of the allele frequency north of (and excluding) the hybrid zone. If I include the hybrid zone sites in the model the altitude remains significant, but less so. I added a dummy variable to the model for hybrid zone/no hybrid zone. Running the model it is also very significant along with altitude.

  I would like to find a statistical approach to identify sites (most likely in the hybrid zone) that has a lower than "predicted" allele frequency for this trait. This would support my hypothesis that a barrier to expansion of this presumably beneficial trait occurs in the hybrid zone (where we find low abundance).

I am happy to rephrase my question, provide sample data or just take suggestions for approaching this problem of identifying these "outlier" sample sites.

I have binomial frequency data for an allele associated with populations living in mountainous. These mountains run north to south where sites are nearly fixed for this allele and lowland sites to the east that lack the allele. At the south end of the mountains is a hybrid zone. Despite the mountains continuing south through the hybrid zone, the allele frequency shifts from nearly fixed to nearly absent. This suggests that despite the assumed benefit for this trait in the mountains, that there is a barrier for it in the hybrid zone preventing its spread south in the mountains.

I have used a simple glm approach in R to identify that altitude is a significant predictor of the allele frequency north of the hybrid zone. If I include hybrid zone sites in the model, altitude is less significant. If I add a hybrid zone dummy variable to the model and it is also significant. I would like to find a statistical approach to identify these "outlier" mountain sites in the hybrid zone both statistically and graphically.