I have a question regarding what method of mixomics I could use for my data. I have metabolomics, proteomics and phosphoproteomics data. This data has been acquired from cells stemming from the same cell line and have been treated similarly (infected/not infected in a timecourse (every timepoint is a separate group of samples)). However, these experiments are independent as they are performed at different times and by different people. My question is whether I should use MINT because the experiments are independent and thus the data is not acquired on exactly the same samples (although the samples are treated similarly), or can I use DIABLO (when I use all three datasets) or PLS (when I use 2 out of 3 datasets) since I have three different types of data and the samples are treated similarly? Additionally, I would like to ask how far the development is of the timecourse extension. Can I already use this extension or is it still in progress? And if it is still in progress, how would you recommend to deal with different time points? Lastly, the metabolomics dataset is relatively small (around 150 metabolites). Can I still perform pls-da on this dataset, or is this dataset too small for pls-da?