Showcase your success in compound identification for up to 500 new unknowns, using raw LC-MS/MS data

In untargeted assays, approximately 80% of all MS/MS spectra remain unidentified. Yet, the last CASMI contest was performed five years ago. As molecules of former CASMI contests are now well known, new datasets must be provided for testing compound ID strategies in 2022. A new CASMI comparative assessment of small molecule identifications is overdue. Hence, the UC Davis West Coast Metabolomics Center is spearheading such a workshop to take place for the Metabolomics Society 2022 Conference in Valencia, Spain.

To make this new CASMI 2022 similar to an actual metabolomics study, we here provide raw LC-accurate mass MS/MS data in both +ESI and - ESI mode, with a list of 500 compounds and their retention times and accurate m/z values. Compounds are not included in public libraries but comprise both metabolites and exposome chemicals. If participants would be interested to participate but would struggle to extract mass spectra from these raw files, please contact us to receive the target MS/MS spectra as an .MSP files. If participants would like to receive .RAW instead of .mzml files for the full chromatograms, please contact us.

As these are many compounds, perhaps too many for some, feel free to only use a select number of targets. We will prioritize 250 of these 500 compounds, but certainly would be curious to see if automated processes could work on all of them or at least some of them?

Results will be discussed based on four different categories:

1. Correct annotation of adducts

2. Correct elemental formulas

3. Correct compound structure classes

4. Correct 2D chemical structures

Please, feel free and invited to test your skills, your workflows, your software, or your databases on any or all of these tasks!

Anyone can utilize this data and submit results. Submitters will be notified, and we will then select six submitters to showcase their results and approaches at the Metabolomics Society meeting (if necessary, even remotely or via recorded contributions - but preferred 'in person', of course!). All submitters will be invited to participate in manuscript writing afterward about this CASMI 2022 exercise.


*NEW* Check out the Frequently Asked Questions page: here

*NEW* Solutions & results are up now! 

Download workshop data + solutions here: https://drive.google.com/drive/folders/1h3Hf8vxDQUhDN9aIRKIOBKGR91qgg3cL?usp=sharing

Download the list of challenges, RT, and precursor m/z here:

*UPDATE* Errors on Challenges 81, 282, 432, & 476 have been fixed. Click on the links above to find Excel with corrected information. These challenges will not count in the evaluation.

  • Challenge 81 the correct precursor is m/z 408.2592, please use file A_M24_posPFP_01
  • Challenge 282 the correct precursor is m/z 384.2381
  • Challenge 432 please use the correct file A_M16_posPFP02
  • Challenge 476 the correct precursor is m/z 315.2278

Results will need to be submitted back to us by June 06, 2022. 

Instructions to submit results:

1. Please provide an Excel or CSV document, you can download these templates for either Priority Challenges or Bonus Challenges.

2. For the fourth category listed above, please provide either InChIKey or SMILES. We will count the first block of the InChIKey when assessing the results.

3. Please provide a short abstract about your approach (150 words max.) & a method section detailing your approach (i.e., the format of data used, how data was handled, software parameters, etc.).

To upload your results and other documents click here: https://ucdavis.app.box.com/f/c842f7871478487a8ad66ffeeb9ea56d


 

Contact Information: Arpana Vaniya

 


Additional Information:

  • Who is the intended audience for this workshop: Anyone, but mainly advanced users in metabolomics with 2+ years of experience.
  • Objectives for your workshop:
    • Enable comparison of the current performance in compound ID approaches from raw data – generate new public datasets and write a manuscript
    • Understand the advantages and pitfalls of different compound identification approaches
    • Advance expertise across disciplines toward compound identification
  • Learning Outcomes for participants:
    • Learn about current tools, software, and compound identification approaches.
    • Ask panel experts how to use tools, including pitfalls or barriers to applying tools for your own research.
    • Understand the different levels and hierarchies in compound identification, from determining adducts to elemental formulas, and structure classes to structure isomers.