Possible bug in block.splsda + various questions

Dear mixOmics community

The latest month I’v been working on data integration of several metabolomics/lipidomics datasets with microbiome (16S) data. Lately I encoutered this strange behaviour of the block.splsda function. When I create a model using this list.keepX object:
$Pol_Met_Feces
[1] 17 6

$Pol_Met_Urine
[1] 14 5

$Lip_Met_Feces
[1] 20 12

$Otu
[1] 6 5

The list indicates my otu (microbiome) dataset should have 6 & 5 variables for comp 1 & 2 respectivly in the model. However, when looking at the resulting model we can see that there are 51 & 5 variables for the otu dataset! In another try, with the same input, it resulted in 52 & 6 variables!

Any idea on why this might be the case, or what is happening here?

While I’m at it, I have some other (not as important) questions:

  1. For all my datasets, both in multi omic & single omic analyses, the optimal number of components is always = 1. Is this erratic behaviour, or should this be no problem? For visualization purposes I always construct models with ncomp = 2. Also the error rate of my models stays high, even after tuning, so I guess my data is not suited for prediction, but can be used for pathway analysis / search for biologically relevant correlations?

  2. Is there a way to disregard “within block correlations” when plotting the circosplot or networks?

Many thanks in advance if someone takes the time to read and answer this!

Kind regards
Pablo
PhD Student @ Laboratory for Chemical Analysis, Faculty of Veterinary Medicine, Ghent University