Optimal transport for automatic alignment of untargeted metabolomic data

arXiv:2306.03218v3 Announce Type: replace-cross
Abstract: Untargeted metabolomic profiling through liquid chromatography-mass spectrometry (LC-MS) measures a vast array of metabolites within biospecimens, advancing drug development, disease diagnosis, and risk prediction. However, the low throughput of LC-MS poses a major challenge for biomarker discovery, annotation, and experimental comparison, necessitating the merging of multiple datasets. Current data pooling methods encounter practical limitations due to their vulnerability to data variations and hyperparameter dependence. Here we introduce GromovMatcher, a flexible and user-friendly algorithm that automatically …

abstract alignment annotation array arxiv challenge comparison cs.lg data development diagnosis discovery disease disease diagnosis drug development experimental low major merging multiple prediction profiling q-bio.qm risk through transport type vast