Retention time repository preprint out now

The RepoRT (well, Repository for Retention Times, you guessed it) preprint is available now. It has been a massive undertaking to get to this point; honestly, we did not expect it to be this much work. It is about diverse reference compounds measured on different columns with different parameters and in different labs. At present, RepoRT contains 373 datasets, 8809 unique compounds, and 88,325 retention time entries measured on 49 different chromatographic columns using varying eluents, flow rates, and temperatures. Access RepoRT here.

If you have measured a dataset with retention times of reference compounds (that is, you know all the compounds identities) then please, contribute! You can either upload it to GitHub yourself, or you can contact us in case you need help. In the near future, a web interface will become available that will make uploading data easier. There are a lot of data in RepoRT already, but don’t let that fool you; to reach a transferable prediction of retention time and order (see below), this can only be the start.

If you want to do anything with the data, be our guests! It is available under the Creative Commons License CC-BY-SA.

If you want to use RepoRT for machine learning and retention time or order prediction, then, perfect! That is what we intended it for. 🙂 We have done our best to curate RepoRT: We have searched and appended missing data and metadata; we have standardized data formats; we provide metadata in a form that is accessible to machine learning; etc. For example, we provide real-valued parameters (Tanaka, HSM) to describe the different column models, in a way that allows machine learning to transfer between different columns. Yet, be careful, as not all data are available for all compounds or datasets. For example, it is not possible to provide Tanaka parameters for all columns; please see the preprint on how you can work your way around this issue. Similarly, not all compounds that should have an isomeric SMILES, do have an isomeric SMILES; see again the preprint. If you observe any issues, please let us know.

UMAP plot RP vs HILIC