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Project/Package Idea: Multivariate outliers in genome scans #9
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I would certainly be interested in something like this and haven't really seen anything that attempts it. It would be nice to have some way of summarizing the various genetic statistics (Fst, Tajima's D, etc.) we use in sliding-window analyses (usually you'll see numerous plots for each one, which grows fast with Fst between multiple populations). |
Is there a link to the description of the method? |
Cool stuff. I have had request for exactly that kind of thing on the Cheers On Mon, Mar 9, 2015 at 1:35 AM, Zhian N. Kamvar [email protected]
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I just wrote a blog post outlining two approaches to identify multivariate outliers. Thibaut - I am an intermediate R user and really have no idea about data classes. I'm all about compatibility though! |
Katie - I like the material you put on the blog! On Mon, Mar 9, 2015 at 1:06 PM, Katie Lotterhos [email protected]
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I can provide real data to test it (already on the wiki) or in collaboration. Also happy to dicuss more. |
I have some code that can be used to identify outliers in multivariate space. I could see this as a way to combine results from multiple test statistics in genome scans (i.e. FST, genetic-environment association, genotype-phenotype association) to get multivariate outliers, rather than relying on outliers from individual statistics (note that I also think there are some caveats to this approach). I can see this feasibly developed into a package during the hackathon, and would love to try it on some simulated or real datasets. If anyone thinks this is a good idea, let me know.
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