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Topics - semo519

1
MS-DIAL / MS-DIAL (version 4.16) MSP database selection and mass tolerance
Dear users,

I encounter an issue of the MSP database selection in metabolomics in MS-DIAL as follow,

I performed the plasma metabolomics test and followed the MS-DIAL paper (nature method, DOI:10.1038/NMETH.3393). The polar metabolites extraction and LC-MS conditions were similar to the paper description.

My MS data (Waters, Mse data)  was processed by MS-DIAL and the MSP database file was chosen All Public (please see the attached figures). The ref. matched metabolites are around 400. However, the ref. matched metabolites are 0 when I chose the Fiehn HILIC database. (Because I used HILIC column and follow similar LC-gradient). Why is so large difference by using two databases and at least some metabolites should be overlap?

In addition, another important value is Accurate mass tolerance (MS1). When I put 0.025 Da (follow tutorial), the ref. matched metabolites are 0 but I put 0.05 Da, the ref. matched metabolites are around 400. I checked my MS raw data, the mass accuracy could be 0.025Da tolerance but not sure why the MS-DIAL can't recognize it well.

Any comments and suggestions are all welcome and hope the experienced user could help me solve them.

Thanks for your attention

Best,

Bingpeng
2
MS-DIAL / Why is not accuracy when MS-DIAL process from raw data to alignment results
Dear users,

I recently encountered a problem, some of the features in alignment results appeared a lot of zero values but the features could detect well in MS raw data (please see the attached file). Here we take a DAG (18:1/18:1) as an example, the mass of DAG (18:1/18:1) could be observed in all 6 replicated data but in final alignment list, M-1 and M-5 peak height changed obviously compared with other four data. From MS-Dial, it seemed to mislabel it as isotope (M+1) in M-1 and M-5.

So could anyone tell me what's the reason and how to correct it by setting the proper MS-DIAL parameters?

Thank you very much.

Best,

Bingpeng
3
MS-DIAL / Could MS-DIAL handle with the data of large retention time drift?
Dear users,

My MS raw data were collected recently but it exhibited large retention time drift. My QC4 to QC 10 were distributed regularly in the sample list but expressed large retention time drift, as shown in the attached figure. The Rt decreased gradually as time passed.

So could MS-DIAL correct the retention time drift and how to set the alignment parameters correctly?

Hope the users have similar experience could give me some useful suggestions. Thank you very much.

Best,

Bingpeng
4
MS-DIAL / Mass tolerance and final alignment result (version 4.16)
Dear users,

I recently processed my raw data (waters Q-Tof) using MS-DIAL 4.16. But I encounter some problems as follow,

1. My MS data exhibited a little large mass accuracy, I totally had 14 samples but the mass window should be +- 0.04da during all samples (1-2 sample had large mass variation).

2. So if I set the MS1 tolerance as 0.02 under mass accuracy in data collection of the MS-DIAL panel, some spike standards in these large mass variation samples have no peak height in the final alignment results list (please see the attached figure 1).

3. So I set MS1 tolerance as 0.035 and 0.05, respectively. It could find the correct peak height of these spike standards in the peak list including large mass variation samples. However, the spike standards mass features never be in the alignment results even I modified my alignment parameters (please see attached figure2 ).

4. I am not sure whether have other users encounter a similar issue ( spike standards in peak list but not appear in alignment list).

Please give me some suggestions or solutions in your available time.

5
XCMS / How to evaluate different software? XCMS and Progenesis QI
Dear all:

  I believe that many people encounter such kind of question, XCMS and Progenesis QI, two kind of softwares who is better or more accuracy? Now I have a project, it contains  many cell samples, the samples were analyzed in waters synapt G2 Si and the raw data was converted into the netCDF format by databridge software. Then the CDF files were processing by XCMS and QI, Finally, the table list had a large difference. the table list of XCMS is about 17000 features and the QI only is about 7000 features. So I am not sure who is better ? Maybe many nosie features go into the XCMS table list or maybe the QI lost the important features? Base on the example, I hope we may discuss the data processing workflow , how to ensure that the real difference existing in the raw data could be dig accurately by our data processing step ? If necessary, I can upload my R scripts command for everybody check. Thank  you

Bset regards!

Bingpeng Yan