Q2 negative for first component

I have a question regarding a meta analysis (for a number of data sets separately) I am doing; for all datasets I am facing the same problem; an odd first LV value for Q2 total;

I am doing PLSR regression mode and want to select the number of components according to Q2 criteria (mentioned @mixOmics) where the rule of thumbs is that a PLS component should be included in the model if its value is ≤0.0975.

I have read that negative values and bad prediction could be because of low number of samples and/or large number of variables.

In my case I have 171 samples and 17k genes (from a transcriptomics dataset) and a single response variable.

the value of Q2 total of my top PC/LV comes negative; I am stuck on how to deal with this; any help is appreciated.
below is the code and top pcs q2 total ;
pls.GE<-pls(my_predictors,my_response, ncomp=20, mode= “regression”,scale=TRUE)
perf.pls=perf(pls.GE, validation = “Mfold”, folds=10, nrepeat=10)

1 comp -0.3664158
2 comp 0.3304083
3 comp 0.2942803
4 comp 0.2380420
5 comp 0.2939665
6 comp 0.2672010
7 comp 0.3311232
8 comp 0.2078379

Hi @amnah,

Thank you for using mixOmics and letting us know about this behaviour. Is it possible to send us your data and script in confidentiality so that we can diagnose the issue? We have made some changes to the algorithm and I’d like to pinpoint the problem.

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Thank You very much Al J Abadi. I appreciate you time taking on this. I have emailed you now. Please let me know if there is any problem with data accessibility.