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Thread: Detecting outlier sample sites

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    Detecting 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.

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    Re: Detecting outlier sample sites


    If I include latitude in the model I find a positive significant effect, suggesting that there is a gradient from south to north. Assuming the allele has had time to spread to the full extent of the mountains, this would suggest a barrier. But I am still left with finding a method to identify sites with lower than "expected" or "outlier" allele frequencies in the mountains to the south.

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