PredRet: Prediction of Retention Time by Direct Mapping between Multiple Chromatographic Systems
Poster Nov 27, 2015
Jan Stanstrup, Steffen Neumann, Urška Vrhovšek
Demands in metabolomics research have been a key motivator for the development of repositories for MS spectra1,2 and automated tools to aid compound identification3–5. But utilizing only fragmentation is ignoring half of the available information in LC-MS. The retention time (RT) is equally important.
For LC systems there are currently no coordinated efforts to share and exploit information regarding RT. The reason RT information has been neglected is that the RT is specific to the chromatographic system (CS) and there exist no agreed upon RT references.
A database of compound RTs in different CSs was therefore developed. For each pair of CSs, the RTs are used to construct a projection model between the RTs in the two CSs. Building these models between all CSs allowed the prediction of RTs for a high number of compounds in CSs where they had not been experimentally determined.
With the current small database it was possible to predict up to 400 RTs with a median error between 0.01 and 0.11 min depending on the CS. The median width of the confidence interval for predictions ranged from 0.1 to 0.8 min.
The free, open source and web-based tool is available at predret.org.
Sport Doping Screening in Biological Matrices by Multi-Dimensional LC-QToFPoster
This work evaluated the performance of 2D LC variant using a QToF setup instead of a triple quadrupole mass spectrometer for the analysis of drug of abuse in urine targeting low and sub ppb level.READ MORE
Analysis of Doping and Forensic Drugs in Urine Using High-Resolution GC/Q-TOFPoster
In this study, we are examining the potential for high resolution accurate mass 7250 GC/Q-TOF equipped with low energy EI source, for both quantitative and screening aspects of doping control and forensic drugs applications.READ MORE
Automation of Sample Preparation for Metabolomic Analysis Using Robotic PlatformPoster
We developed an automated sample preparation protocol based on a robotic platform PAL RTC (CTC Analytics AG, Zwingen Switzerland), which represent a modified Bligh and Dyer method producing samples for both hydrophilic metabolomics using GC-MS and lipidomics using SFC-MS simultaneously.READ MORE