sPLSDA SRBCT Case Study()

The R script used for all the analysis in this case study is available here.

For background information on the (s)PLS-DA method, refer to the PLS-DA Methods Page.

More information on Plots

For a more in depth explanation of how to use and interpret the plots seen, refer to the following pages:

• plotIndiv() – Sample Plot
• plotVar() – Correlation Circle Plot
• cim() – Cluster Image Maps

References

1. Khan, J., Wei, J.S., Ringner, M., Saal, L.H., Ladanyi, M., Westermann, F., Berthold, F., Schwab, M., Antonescu, C.R., Peterson, C. and Meltzer, P.S., 2001. Classification and diagnostic prediction of cancers using gene expression profiling and artificial neural networks. Nature medicine, 7(6), pp.673-679.