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Topic: Data from waters - mass measure in centroid mode (Read 356 times) previous topic - next topic

Data from waters - mass measure in centroid mode

Dear all

We work with a synapt G2, Waters, drived with masslynx software. We work in profile mode currently and we apply the correction along the run.

When I convert my data with MS convert, and I check with insilico viewer the peak picking, I observe that the value is the value corresponding to the profile value in masslynx but not to the centroid value. This induces an error of 10 to 15 ppm compared to the exact mass value, instead of 2 to 5 ppm.

Do anyone have a solution to this problem? I checked the filter lockmass refiner but it didn’t work (first filter lockmass refiner then filter peak picking with CWT algorithm).

Thanks

Re: Data from waters - mass measure in centroid mode

Reply #1
What values are you comparing? How do you get a single m/z value from the profile mode data to compare to?
So there is the profile mode data, Waters centroided m/z and the msconvert centroided m/z. The last two will be different due to different centroiding algorithms. The documentation says the CWT method is not very good. You could use Waters centroiding (if that is the one that is good?) if you centroid in masslynx first (to new raw file) and then convert without any additional processing.

Alternatively the R package MSnbase might have more advanced alternatives: https://github.com/lgatto/MSnbase/blob/11c336ebdc3e78cfa404803eb907346b046cd38b/vignettes/v03-MSnbase-centroiding.Rmd
Blog: stanstrup.github.io

 

Re: Data from waters - mass measure in centroid mode

Reply #2
An update to this: Latest version of msconvert should support the vendor centroiding. So the above method going through masslynx should no longer be necessary.
Blog: stanstrup.github.io

Re: Data from waters - mass measure in centroid mode

Reply #3
We have AB Sciex data and so far I used proteowizard centroiding (with vendor option). This turned out to be a poor choice. What I am doing now is to export all data from Sciex as mzML in profile mode and perform the centroiding in R using MSnbase.

Have also a look at https://github.com/jotsetung/metabolomics2018 where I describe the centroiding with MSnbase (specifically https://jotsetung.github.io/metabolomics2018/xcms-preprocessing.html#23_centroiding_of_profile_ms_data).