Hello, I am running DIABLO analysis on metabolomics and ASVs data with outcome variable as hypertension (yes, no), and the optimal number of components was suggested to be two. Component 1 seems to be fine (correlation of 0.47 between the two datasets). My question is that the number of variables per component is mentioned below but then when I run the circos plot on component 2, I am getting 48 ASVs on component 2 when in fact the list.keepX shows only 5 ASVs on component 2. Is it possible that while it is suggested that the optimal number of components is 2 based on BER, I should only consider the first component. Also, the correlation between the two dataset on component 2 is 0.21 and the loading plot for ASVs is also looking weird. I would really appreciate receiving some clarification. Thank you!
max.dist centroids.dist mahalanobis.dist
Overall.ER 1 4 2
Overall.BER 1 2 2
$metabolite
[1] 30 30
$asv_clr
[1] 5 5
sgccda.res <- block.splsda(X = X_new, Y = Y3, ncomp = 5,
design = design)
perf.diablo <- perf(sgccda.res, validation = 'Mfold', folds = 5, nrepeat = 50)