Hi,

I am working on the expression datasets that has multiple-variables. I am using the `FactoMineR`

and `pca3d`

libraries for this purpose and was able to distinguish two factor levels belonging to a one variable column. However, I am not able to perform the PCA on the two variable columns that has different factor levels. Please let me know how can I do the PCA on multi-variable.

Below is the code I have ran with the one variable column;

```
Neg_Dct
## Column [1-4 and 269-272] of the data set contains variables/categorical data##
df = Neg_Dct[,-c(1:4, 269:272)]
library(FactoMineR)
nb_1 = estim_ncpPCA(df,ncp.max=5)
res.comp_1 = imputePCA(df,ncp=2)
res.pca_1 = PCA(res.comp_1$completeObs)
library(pca3d)
Node <- res.comp_1$completeObs
pca <- prcomp(Node, scale.=TRUE)
gr <- factor(Neg_Dct[,272])
summary(gr)
B_1 B_2
31 132
#2D plot##
pca3d(pca, group=gr)
#2D plot##
pca2d(pca, group=gr)
```

Thank you,

Toufiq

@ Kevin Blighe,

Thank you very much for the suggestions. Can I also perform 3D visualisation using the pcatools?

Sometimes, it does not show the

Replybutton to write back so I had to add the text in thecommentsection.You cannot perform 3-D visualisation using

PCAtools; however, I may implement it in the future. I provide some basic code for a 3-d PCA here: A: PCA plot from read count matrix from RNA-SeqTo respond my original answer, I think that you can use the

`ADD COMMENT`

button alone, no? It looks like you posted a new answer (but I moved it).@ Kevin Blighe ,

Noted. Thank you very much. This is helpful.