How to avoid filtering during data normalization

I have a dataset with more than 5000 features. I would like to use the MetaboAnalyst Statistical Analysis function to normalize all features of my dataset for the downstream GSEA analysis. However, MetaboAnalyst filtered out many features and only returned 2500 features of my dataset. There is no way for me to turn off the filter function. I remember I once could do this on the MetaboAnalyst website before Aug 2021. Now, I can’t. I guess if I can install MetaboAnalystR locally, I may be able to skip the filtering. But I don’t know the R language and have no idea how to install even after reading the instructions on the MetaboAnalyst website. I wonder whether someone can help me. Many thanks in advance.

MetaboAnalyst website aims to provide the best practice for metabolomics data analysis.
I assume your data is LC-MS untargeted metabolomics which contains a high proportion of noise,

  • If you choose no-filtering, you will have top 5000 features, not 2500. After minimal data cleaning (blank subtraction and removing low repeatability peaks based on QC), the peaks are already below this number in most time based on our own experience.
  • Please read this post on data filtering for PCA
  • Our recent benchmark study shows that GSEA does not perform well, and ~30% annotation rate can achieve high recall (~90%) on pathway activity prediction using mummichog

For R package installation, have you tried to follow our instructions, and what are the issues?