[user via email]

We have developed an omic integration tool to find clusters in extensive data sets, as a way to complement current methods that work very well in smaller sample sizes. We wish to describe similar tools available to highlight the best context to use the different existing statistical tools. We also want to determine if our tool has adequate performance by evaluating it in comparison with mixOmics.

However, to be fair and acknowledge current methods capabilities, we want to ensure we are using the adequate version and combination of arguments (parameters) that give your package the highest possible performance.

Below are the version and arguments we have so far used.

The idea here is to do sparse PCA on a matrix **x** representing concatenate omic blocks and assuming 479 â€śsignalâ€ť features.

out_spca <- spca(X = x, ncomp = 2, keepX = c(479,479))

mixOmics_6.13.11

We would appreciate it if you could give us feedback on the above.

Thank you very much,

Agustin