Ion Mobility-mass spectrometry Dashboard (IMDash): an automated, multi-platform computational pipeline to support production of robust and large-scale experimental collision cross-section libraries Authors

Experimental collision cross-section (CCS) libraries are emerging as critical resources for enabling high-confidence molecular annotation in metabolomics studies and providing ground truth for training models to predict CCS. Multifield drift tube ion mobility spectrometry (DTIMS) is the only accepted method for primary CCS determination, yet large-scale CCS library construction has been impractical due to labor-intensive data processing workflows. To address this, we developed the Ion Mobility Mass Spectrometry Dashboard (IMDash), a flexible and containerized pipeline integrating community-developed tools and that performs data preprocessing, CCS determination, and database generation. IMDash can process data from a variety of IMS-MS platforms and methods including both multifield and calibrated single-field DTIMS and traveling wave IMS (TWIMS) methods like structures for lossless ion manipulations (SLIM). Benchmarking results demonstrate both the flexibility of IMDash across computing platforms, from personal computers to cloud and high-performance computing clusters, and the substantial speedups that are possible on more capable systems. We further demonstrate the real-world functionality of IMDash by building CCS libraries for three commercial compound collections using both multifield and calibrated single field DTIMS methods, producing reference CCS values for thousands of compounds and adducts with high reproducibility and agreement between methods. By supporting edicient processing of large experimental datasets, IMDash provides a scalable solution for building high-quality reference CCS libraries, advancing metabolomics research and empowering the development of machine learning models for chemical property prediction.