Question About Optimizing ROI Extraction Speed in MetaboAnalystR

[jeff.xia]

I’ve encountered with the ROIExtraction step in MetaboAnalystR.
I currently have 25 datasets mzML files (1800s/30min acquisition time each).
Issue: ROI extraction takes significantly longer than expected.
Attempted solution: Tested RStudio’s parallel processing but instability occurs during large batches.
Is there any recommended strategies to accelerate processing for large time-series datasets? Or any best practices for configuring stable parallelization in MetaboAnalystR?

Thank you for the query. The ROI is only related to parameter optimization step which is typically performed on the spectra from the pooled QC samples (usually 3~5). The QCs are a pooled mixture of all patients’ samples usually with better signals for training / tuning. The optimized parameters will then be applied to all the spectra for peak picking. If your data do not have pooled QCs, you can choose a few reference spectra for each groups for parameter tuning. Using ALL spectra is unnecessary and will be very resource / time consuming.

[MenghengLi]

Thanks for confirmation. I have 5 different subfolder which one of folder is QC which contains 5 mzML samples I left data run on R overnight and returns:
In MulticoreParam(4L) :
MulticoreParam() not supported on Windows, use SnowParam()
I suspected it is not processing parallel because CPU usage only about 10% of total performance. But seems like it is not.
New updates: Actually I reduced sample to only QC folder and its working.