OPLS-DA down

Dear support team,

OPLS-DA functions are all down. Performing these analyses are actually not feasible on the online platform.

Please note that I tried to process my data (two-groups comparison) using MetaboAnalyst 6.0 and MetaboAnalyst 5.0 and in both cases, it dose not work. Blank pages are shown when trying to achieve analyses, despite the fact that PCA is fully operational.

Can I get some help please?

Thanks in advance.

Please read and follow our post guidelines

Here’s my response following the guidelines:

- Which tool and which module:

Statistical Analysis → Statistics → Orthogonal PLS-DA

- Provide a copy of your data:

Cf. attached file: DataMatrix.csv (207.8 KB)

- Document all steps leading to the issue. Sometimes screenshots may be necessary:

  1. Module: Statistical Analysis
  2. Data upload:
    a. Data Type: Peak intensities
    b. Format: Samples in rows (unpaired)
    c. Data File: DataMatrix.csv (207.8 KB)
  3. Data Integrity Check: Proceed (no check done or needed)
  4. Data Filtering: Proceed (no filtering done or needed)
  5. Data Editor:
    a. Edit Groups
    b. Available: GRP1; GRP2
    c. Exclude: BLNK; GRP3; GRP4; GRP5; POOL
    d. Group order matters: no
  6. Normalization:
    a. Sample normalization: none
    b. Data transformation: none
    c. Data scaling: Pareto scaling
  7. Select an analysis path to explore: Orthogonal Partial Least Squares - Discriminant Analysis (orthoPLS-DA)
  8. Orthogonal PLS-DA: Cf. screenshots in attachments (even when clicking on “Update” or “Submit”, no results can be acquired)

- If it is about using R packages, you also need to provide the environment information, such as sessionInfo():

R Command History (online platform):

|1. |mSet<-InitDataObjects(pktable, stat, FALSE)|
|2. |mSet<-Read.TextData(mSet, Replacing_with_your_file_path, rowu, disc);|
|3. |mSet<-SanityCheckData(mSet)|
|4. |mSet<-ReplaceMin(mSet);|
|5. |mSet<-SanityCheckData(mSet)|
|6. |mSet<-FilterVariable(mSet, F, 25, none, -1, mean, 0)|
|7. |mSet<-PreparePrenormData(mSet)|
|8. |mSet<-GetGroupNames(mSet, )|
|9. |feature.nm.vec ← c()|
|10. |smpl.nm.vec ← c()|
|11. |grp.nm.vec ← c(GRP1,GRP2)|
|12. |mSet<-UpdateData(mSet, F)|
|13. |mSet<-PreparePrenormData(mSet)|
|14. |mSet<-Normalization(mSet, NULL, NULL, ParetoNorm, ratio=FALSE, ratioNum=20)|
|15. |mSet<-PlotNormSummary(mSet, norm_0_, png, 72, width=NA)|
|16. |mSet<-PlotSampleNormSummary(mSet, snorm_0_, png, 72, width=NA)|
|17. |mSet<-OPLSR.Anal(mSet, reg=FALSE)|
|18. |mSet<-PlotOPLS2DScore(mSet, opls_score2d_0_, png, 72, width=NA, 1,2,0.95,0,0, na)|
|19. |mSet<-PlotOPLS.Splot(mSet, opls_splot_0_, all, png, 72, width=NA);|
|20. |mSet<-PlotOPLS.Imp(mSet, opls_imp_0_, png, 72, width=NA, vip, tscore, 15,FALSE)|
|21. |mSet<-PlotOPLS.MDL(mSet, opls_mdl_0_, png, 72, width=NA)|
|22. |mSet<-PlotOPLS2DScore(mSet, opls_score2d_1_, png, 72, width=NA, 1,2,0.95,0,0, na)|
|23. |mSet<-UpdateOPLS.Splot(mSet, all);|
|24. |mSet<-PlotOPLS.Splot(mSet, opls_splot_1_, all, png, 72, width=NA);|
|25. |mSet<-UpdateOPLS.Splot(mSet, none);|
|26. |mSet<-PlotOPLS.Splot(mSet, opls_splot_2_, none, png, 72, width=NA);|
|27. |mSet<-PlotOPLS.Imp(mSet, opls_imp_1_, png, 72, width=NA, vip, tscore, 15,FALSE)|
|28. |mSet<-OPLSDA.Permut(mSet, 20)|
|29. |mSet<-PlotOPLS.Permutation(mSet, opls_perm_0_, png, 72, width=NA)|
|30. |mSet<-OPLSDA.Permut(mSet, 1000)|
|31. |mSet<-PlotOPLS.Permutation(mSet, opls_perm_1_, png, 72, width=NA)|

- If it is about raw data processing, please also describe how the data were collected (instrumentation, etc).:

Not applicable

Thank you for the detailed report. The issue should be fixed. The public website will be updated by the end of the week if not earlier