Please check the following things and very likely: 1. Ensure that your LC-MS instrument acquired the data in MS/MS 2. While converting the data you are converting in a way that MS2 level data is retained and not lost. 3. More info on the instrument used and file converted used and sharing a downloadable link to the file help. 4. Another culprit could be too stringent filters set for RT matches (put it to 100 mins) or MS1 resolution could be impacting analysis.
"In the main viewer of MS-DIAL, the detected peak information is shown in the central window by double clicking the file name in the File navigator. In the bottom-center window (Peak spot viewer), each spot denotes the detected peak (precursor ion) information: blue spots describe peaks of lower abundance in the sample, red spots describe peaks of higher abundance, and green spots describe peaks of middle abundance." In a lipidomics project, the spot color will mean a specific lipid class such as PC, PE, and TAG etc.
On Alignment spot viewer of the bottom-center window, each spot shows an aligned spot including all retention time, accurate mass, intensity, and MS/MS spectrum of all samples. As described above, in the Peak spot viewer, red, blue, and green “alignment” spot denotes higher, lower, and middle abundance (on average) in the alignment, respectively.
It simply means the Reference (Matching) spectra does not have CCS and Mobility values/ data, if you are dealing with Ion Mobility data- if not then ignore altogether! Its possible and need to be filtered out after exporting the alignment results.
RT, m/z, MS1 matches and MS/MS spectra overlap is what matters if your data is of non-IMS origin.
If you go to Option - > File Property Setting and then just try to click on the table and sort it works for sorting for all of them: Batches, Analytical order and so on.
Yes, you can type and make them alphabets or numbers or hybrid ones such as 1, 2, 3, or A, B, C or 1A, 1B, 1C and so on! Worked for me just now.
I see MSDIAL only adopted for Thermo .RAW files and .WIFF files from Sciex; not sure if other Vendor formats are supported yet! Feel free to use https://proteowizard.sourceforge.io/download.html (msconvert) to convert to .cdf or .mzML for your .qgd files!
Excellent question, but it takes a more foolish person like me to take a stab at it.
I would say, all 3 citations are good to go, and NONE are helpful. These are good findings.
Unfortunately, I have not come across any such criteria recommended by Metabolomics Society, or do not think it will be ever possible.
Throwing a few thoughts back to you:
1. If the reference spectrum has only 2 fragments, and the query spectrum has 12 of which the 2 overlap, would you take it as a "confident match"? it could be MS instrument level differences.
2.If two spectra are generated using different instruments, then the spectra might be different enough to show a 500 DP score, and would be acceptable, right? Same compound, same RT but different spectra due to different mass analyzers.
3. What if the older library spectra came from a low resolution instrument and scanned from 100-600 m/z and you are comparing it with a query spectra obtained from a newer high resolution instrument with fragments obtained from a 30-800 scan range: same compound, same MS1, different fragments and search space ??
4. If you are dealing with LC-MS/MS data where Rt, and RI are non-existent and non-interoperable, its very murky out there to just have "ANY Cut-off" to get "any confidence" based on MS1, and MS2 alone- esp. with different set ups! LC-MS/MS community NOT leveraging RT is quite painful and unhelpful in the longer run.
I feel the convention of 500, 50% cosine/ DP, and > 0.5 cosine/ DP are all comparable. MS-DIAL's total score is a weighted DP, if I recall but their FAQ explains some of it.
Thanks for following up! And doing a good job actually. I can comment if I see the .text paramters file" and if you can share that small .msp file (this would be essential) over here or email!
These 2 files will tell me the story and I can cross check with a quick run at my end....
Most likely the problem is coming from "alignment" of all ran files/ compounds together! Its a forced alignment error for RT and m/z dimensions both thats resulting in this mass shift and also RT shift that you can see.
Only trick, laborious one: Do it one by one on MS-DIAL. Do not run them all together or align! If not, then learn to live with that mass-shift which does not affect MS/MS similarity matching or even MS1 based matching as it does not affect much, plus you got RT dimension to give you confidence.
Did you do the GNPS analysis (Under "Data visualization -> Molecular Spectrum Networking) first after the alignment was done? if not then those would not show up. Do you have plans to do GNPS analysis (https://gnps.ucsd.edu/ProteoSAFe/static/gnps-splash.jsp) from this data, if not then you need not bother about it. Yes, you can do so! Thanks, Biswa
Most columns in the .text output file are 'self-explanatory' and for the annotation confidence level codes in the later columns refer: http://prime.psc.riken.jp/compms/msdial/annotationcode.html Post-curation results are from: an exercise that relies on https://msflo.fiehnlab.ucdavis.edu/#/ for peak redundancy MS/MS asssigned: if there were spectral or MS/MS level matches or not between the dataset and spectral library used Reference RT/ M/z refer to : if matches with the spectral library are true or not, and if matched what value of m/z etc.
Absolutely you can merge the in house .msp file and the open source spectral .msp files into a single .msp file and use just one file for your annotation purposes!
Follow steps something like this : Steps for Building an Open Source EI-MS Mass Spectral Library for GC-MS -based Metabolomics:https://www.protocols.io/view/steps-for-building-an-open-source-ei-ms-mass-spect-8txhwpn and get it done!
To differentiate between spectra that will be from your "in house" library vs the "OS" for say, "glucose", just "tag them differently in the "NAME" field in the individual spectra in the .msp files:
NAME: Glucose_inhouse NAME: Glucose
But if you need an automated R or Python based solution then check out here:http://www.metabolomics-forum.com/index.php?topic=1686.0 Hope it helps!
The GCXGC field is such monopolized by vendors and their expensive solutions, its a pity! Any other stand alone solutions are SUPER EXPENSIVE and not so user friendly at all. Such as: GCImage https://www.gcimage.com/gcxgc/ or Decodon https://www.decodon.com/ that are excruciatingly expensive!
