вторник, 17 декабря 2019 г.

Avalon vs Valhalla revisited


Pictured below is a new version of my Celtic vs Germanic genetic map. It's based on the same Principal Component Analysis (PCA) as the original (which can be seen here), but more focused on Northwestern Europe and produced with a different program.


To see the interactive online version, navigate to Vahaduo Custom PCA and copy paste the text from here into the empty space under the PCA DATA tab. Then press the PLOT PCA button under the PCA PLOT tab. For more guidance, refer to the screen caps here and here.

To include a wider range of populations in the key, just edit the data accordingly. For instance, to break up the ancient grouping into more specific populations, delete the Ancient: prefix in all of the relevant rows. This is what you should see:


Conversely, you can leave the ancient sample set intact and instead reorder the present-day linguistic groupings into, say, geographic groupings. To achieve this just delete all of the linguistic prefixes, such as Celtic:, Germanic:, and so on. You should end up with a datasheet like this and plot like this.

Of course, you can design your own plot by using any combination of the ancient and present-day individuals and populations that I've already run in this PCA. Their coordinates are listed here. Indeed, if you're in the possession of your own Celtic vs Germanic PCA coordinates, you can add yourself to the plot. And if you're not, see here.

It's also possible to re-process PCA data via the SOURCE tab. But I don't recommend doing this with the Celtic vs Germanic data, which are derived from a fine scale analysis and don't pack much variation. On the other hand, Global25 data are ideal for such re-processing. I made the plots below from subsets of Global25 coordinates available in a zip file here. To see how, refer to the screen caps here and here.




See also...

Modeling your ancestry has never been easier

Getting the most out of the Global25

Modeling genetic ancestry with Davidski: step by step



* This article was originally published here

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