Commit c256ec99 authored by Samuel BERTRAND's avatar Samuel BERTRAND 🐉


parent 02656ca8
......@@ -78,5 +78,15 @@ Then two result tables a provided. One corresponding to the selected features ca
The variables represented in pink in the volcano plot are those listed in the “result$featuresSelection” table. The parameters used for features selection can be modified within the function arguments “lim.FC” and “lim.pVal”.
<h2>Multivariate data analysis using OPLS-DA</h2>
The data analysis strategy corresponds to the direct comparison of samples from pure metabolomes with the mixed metabolome separately by a multivariate method called OPLS-DA (Orthogonal projection of latent structure with discriminant analysis) in a way similar to univariate analysis. In the cases presented here, “Fungi1” is compared to “Fungi1VSFungi2” and “Fungi2” is compared to “Fungi1VSFungi2” separately. Then the two data analysis are merged based on both VIP (variable importance in the projection) values.
Multivariate data analysis is achieved as follow:
`result<-Coculture.analysis(data=data, SampleNames = rowheader, monocultureSamples = c("Fungi1","Fungi2"), cocultureSamples = "Fungi1VSFungi2", scaleC='standard', log10L=TRUE, Method = "OPLS-DA")`
The function provide various results as follow. First a graphical representations of the results as PCA (principal component analysis) and a SUS (share and unique structure) plot.
<img src='' />
<img src='' />
Markdown is supported
0% or
You are about to add 0 people to the discussion. Proceed with caution.
Finish editing this message first!
Please register or to comment