I have done SSR genotyping in maize and want to perform principal coordinate analysis. Which software can I use for this? Are there any online tutorials?
Hi Lebogang,
You can use ADEGENET (http://adegenet.r-forge.r-project.org/) in R. You first have to build a genuid object that you can then use the PCA function of Adegenet. A well detailled protocol is provided here (p41) : http://cran.r-project.org/web/packages/adegenet/vignettes/adegenet-basics.pdf
Cheers,
Nicolas
Hi Lebogang,
You can use ADEGENET (http://adegenet.r-forge.r-project.org/) in R. You first have to build a genuid object that you can then use the PCA function of Adegenet. A well detailled protocol is provided here (p41) : http://cran.r-project.org/web/packages/adegenet/vignettes/adegenet-basics.pdf
Cheers,
Nicolas
PCA can be performed in NTSyspc software. very user friendly and quoted by number of authors.
You can try GenAlex software. Its very easy add-in excel.
http://biology.anu.edu.au/GenAlEx/Welcome.html
I second the use of GenAlex, as it is very easy and user friendly, and if you are familiar with Excel you can easily make a nice graphic. You can also choose from a number of different distance measures to calculate.
Hi Lebogang,
Have you tried Genetix? this software performs factorial analysis of correspondence (AFC), a similar analysis.
Anyway, to carry out correspondence analysis I've also used GenAlex and NTSyspc.
wow I forgot that we've got Genstat too and it has the functionality. I will try it. I did download R. thank you all
You could run PCA on several analysis platforms. Just ensure you know what you are doing, what you are presenting in the graphics….
I kind of liked GenAlex and had the option of using a priori defined population matrix or individual matrix (distance or similarity between each individual with every other individual in the population under study). It is simple and (so far) free. Ioannis already gave the link! Good luck.
Hi there lebo
PCA can be analysed using GenAIEx software. fist analyse genetic distance and use the distance matrix to analyse PCA. It is user friendly and freely available; it also works in excel.
The R package "pcaMethods" was used in the paper "Genetic variations of F1 tomato cultivars revealed by a core set of SSR and InDel markers" (Phan et al 2016).
(adegenet R package can make a DAPC with SSR markers, which is a bit different than PCA)
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