I have performed sPLS-DA on a gene expression dataset with 5 sample classes. I got a 4 component model with number of variables selected along the 4 components being 357,357,357 and 179 respectively. The sample plots, loading plots and clustered image maps have been attached here.

I wish to find features that can discriminate ‘TNBC’ samples from others. Similarly, I wish to find features that can discriminate ‘Normal’ samples from others. As these classes are not getting segregated well in one particular component, I am finding it difficult to interpret the result. Any help is highly appreciated.

Thanks!

Sample space on component 1 and 2:

Sample space on component 2 and 3:

Loading plot on component 1 with contrib = “max”:

Loading plot on component 1 with contrib = “min”:

Loading plot on component 2 with contrib = “max”:

Loading plot on component 2 with contrib = “min”:

Clustered image map on component 1:

Clustered image map on component 2: