I am new to metabolomics and I have been using MS dial for the past months now. I initially only had one run, then decided to run more samples in a separate LCMS run. Now I am attempting to merge and batch correct run 1 and run 2 in R having QCs that include different samples.
Is there a way to align samples to two different QC files in MS dial? Or is there a way to merge abf QC files from the two runs somehow?
Otherwise, does anyone have any suggestions for how I could merge these runs and batch correct them using e.g R packages?
So far I have tried: 1) running them separately on MS dial, aligning them to the QC used for each run, then importing into R, processing them separately, then merging on common features between runs, and batch correct (pmp package and QCRSC function). 2) Running both runs in MS dial, aligning to the QC from the second run, then importing into R and batch correct as above.
As you can imagine, because of the different QCs none of these have worked so far, on my pca plot, samples in each run are clustering with their run QCs in separate clusters.
Any suggestions you might have would be greatly appreciated! Thank you.
Thanks so much for developing MS-dial, it is such a great program!
I am currently analysing metabolomics data using version 4.6.
After processing the raw data and scrolling through the ion table I opened up the chromatogram and visualised the individual peaks for each sample. I noticed that lots of those samples had a peak intensity of 0, despite there being a clear clean peak there (right top table, picture 1). I learned then that I can manually modify those peaks by following what is indicated on the left table (picture 1). So after updating I then got an intensity for all peaks (picture 2).
I was wondering: - Why are so many peaks not detected and assigned an intensity of 0? I unticked the gap-filling option so I wondered if this was the reason?
- If that was not the reason, should I perform this manual adjustment for all metabolites detected? Prior to this I would replace all values by 1/10 of the minimum peak intensity during the export option. However, I can really see how this could bias my results, especially when that 1/10 assigned would not approximate the actual intensity of those peaks. On the other side, I could never manually change all of them as I detected over 19'000, so if I only did it for a subset of more interesting ones, I would also be biasing my final result. What do you suggest?
I couldn't find any reference to this functionality on the tutorial page, so I wanted to check directly with you.
