Design matrix between omics datasets?

I don’t know how to get the design matrix by using PLS method mentioned in “The latter approach uses PLS method implemented in mixOmics that models pair-wise associations between omics datasets.”

The plot is below.

It coms from this artile:“DIABLO-an integrative, multi-omics, multivariate method for multi-group classification (https://www.biorxiv.org/node/18589)”

Hi @XiaoFie,

Thanks for using mixOmics.

You can use the plotDiablo function from mixOmics to produce a similar visualisation for each component. See example below.

library(mixOmics)
data('breast.TCGA')
Y = breast.TCGA$data.train$subtype

data = list(mrna =  breast.TCGA$data.train$mrna,
            mirna =  breast.TCGA$data.train$mirna, prot =  breast.TCGA$data.train$protein)

# set number of component per data set
ncomp = 3
# set number of variables to select, per component and per data set (arbitrarily set)
list.keepX = list(mrna = rep(20, 3), mirna = rep(10,3), prot = rep(10,3))

# set up a full design where every block is connected
design = matrix(1, ncol = length(data), nrow = length(data),
                dimnames = list(names(data), names(data)))
diag(design) =  0
design

BC.diablo = block.splsda(X = data, Y = Y, ncomp = ncomp, keepX = list.keepX, design = design)
## Look at pairwise correlations of component 1
plotDiablo(BC.diablo, ncomp = 1)

Please let us know if you have any other questions.

Best wishes,

Al