Is outlier detection the right choice for determining if a value lies singificantly away from the mean in a population in gene frequency?
I agree you have the right idea because that data doesn't look at all linear, so regression analysis looks really complicated. Your approach a straight comparison keeps it simple and is within the biological question you are asking, 

However, I would use a non-parametric such as Wilcoxon instead of a T-test. I don't fully know the null distribution you are comparing it against. Wilcoxan doesn't require an assumption of normality. T-tests invariably require a transformation to normality and that gets complicated, but a log or sqrt transformation might be okay. If Wilcoxan produces a no significant difference you report it and move onto a T-test.

It is difficult to use outlier analysis with 9(?) observations, thats used if you have a way-out result and can afford to exclude it (>3 standard deviations). Outlier analysis is to remove a single result that is messing up your analysis and doesn't affect the bulk of the data. You alot of observations to be considering outlier analysis.