[adegenet-forum] Fwd: Significance of allelic contribution to discriminant functions

[Caitlin Collins]

Yeah, it's new!

I might as well note, in case you decide only to try a subset of the
methods available:
- Ward's method is most likely to select a very large number of variables
to get the most complete picture
- Single linkage hierarchical clustering will probably select the fewest
- Centroid clustering will probably select a useful middle-ground.

You can always check to see what proportion of the variance is contained in
the subset of variables retained, or you could even try running a DAPC/ PCA
with just those variables to compare the discriminatory power of the entire
set with that of the subset selected.

Good luck.

Cheers,
Caitlin.


On Tue, Aug 26, 2014 at 4:31 PM, Charlie Waters <cwaters8 at uw.edu> wrote:

> Thanks Caitlin! I've never come across the snpzip function so I'll give
> those clustering methods a try.
>
> Thanks,
> Charlie
>
>
> On Tue, Aug 26, 2014 at 3:49 AM, Caitlin Collins <caitiecollins at gmail.com>
> wrote:
>
>> Hi Charlie,
>>
>> Good question. Technically, there is no one "correct" statistical
>> solution to your problem. But, there *are *a number of ways of
>> approaching the problem with more statistical rigour than simply using an
>> arbitrary threshold as you have done.
>>
>> Have you taken a look at the snpzip function in the adegenet packge? If
>> not, just type "?snpzip" into R with the adegenet package loaded. With this
>> function, you can apply one of seven different hierarchical clustering
>> formulas to the allelic contributions generated by dapc. Essentially, each
>> hierarchical clustering method uses a unique approach to determine where
>> the threshold should be drawn. I should note, however, that this
>> descriptive approach will not have an associated p-value. You may want to
>> try out a few different methods before deciding which variables you want
>> to consider "most significant".
>>
>> I hope that helps!
>>
>> Best,
>> Caitlin
>>
>
>
>
> --
> Charlie Waters
> Box 355020
> School of Aquatic and Fishery Sciences
> University of Washington
> Seattle, WA 98105
>
>
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