[adegenet-forum] DAPC axes
Said D.
said_wali at hotmail.com
Wed Sep 30 12:43:25 CEST 2020
Dear Thibaut, dear Cathy,
thank you for the quick reply.
Now it is clear to me.
With respect to "grid = TRUE", it is only showing the grid but not the labels of the axis ticks.
Till now I was not able to find it.
Thank you.
Said
________________________________
Von: Thibaut Jombart <thibautjombart at gmail.com>
Gesendet: Mittwoch, 30. September 2020 11:21
An: Said D. <said_wali at hotmail.com>
Cc: adegenet-forum at lists.r-forge.r-project.org <adegenet-forum at lists.r-forge.r-project.org>
Betreff: Re: [adegenet-forum] DAPC axes
Dear Said,
both terminologies are correct: LDs are merely PCs of a discriminant analysis. But as DAPC has 2 sets of PCs, one of the initial PCA, then one for the follow-up discriminant analysis, LDs will be less ambiguous.
As for the scale on scatterplots of DAPC: it is disabled by default as not usually used, but you can add a grid using grid = TRUE. See ?scatter.dapc for further options.
Best
Thibaut
--
Dr Thibaut Jombart
Associate Professor in Outbreak Analytics, London School of Hygiene and Tropical Medicine
Senior Lecturer in Genetic Analysis, Imperial College London
UK Public Health Rapid Support Team
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On Wed, 30 Sep 2020 at 09:29, Said D. <said_wali at hotmail.com<mailto:said_wali at hotmail.com>> wrote:
Hi everyone,
I googled a lot (Maybe I was not lucky enough) but I could not find a real explanation out the axes of the DAPC scatter plot.
Should I call them PC1 and PC2 or LD1 and LD2?
Here they call the axes LD1 and LD2
https://grunwaldlab.github.io/Population_Genetics_in_R/clustering_plot.html<https://nam11.safelinks.protection.outlook.com/?url=https%3A%2F%2Fgrunwaldlab.github.io%2FPopulation_Genetics_in_R%2Fclustering_plot.html&data=02%7C01%7C%7Ca0a7b1e41e334029916408d8652242c0%7C84df9e7fe9f640afb435aaaaaaaaaaaa%7C1%7C0%7C637370545101720582&sdata=ott8hyt8zedQ1OGkSD80DV3tbjjxg55q%2BVyLXs0G%2BMA%3D&reserved=0>
It is also a pity that the original DAPC scatter plot is not showing the scale.
Thank you.
Said
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