Retention Time STandardization and Registration
Alexandre P. Blanchard, Yun Wang, Graeme P. Taylor, Matt Granger, Stephen Fai, Daniel Figeys, Tomas Paus, SYS Consortium, Hongbin Xu, Zdenka Pausova, and Steffany A.L. Bennett. Version 1.0.0
ABSTRACTMotivation: Bioinformatic tools capable of registering, rapidly and reproducibly, large numbers of liquid chromatography-electrospray ionization-mass spectrometry (LC-ESI-MS) lipidomic spectra are limited. We provide here a freely available Retention Time Standardization and Registration (RTStaR) algorithm that aligns the LC-ESI-MS spectra of biological replicates within a single dataset and then compares this alignment to the RTStaR-standardized retention times (RT) of multiple datasets. This two-step calibration matches corresponding and identifies unique lipid molecular species in different lipidomes. RTStaR was developed using a population-based study of 1001 human serum samples composed of 71 distinct glycerophosphocholine metabolites aligning a total of 68,572 analytes across subjects. Platform and matrix independence were validated using different MS instruments, LC methodologies, and glycerophospholipidomes. We show that RTStaR can reliably align multiple LC-ESI-MS spectra in a single study and can register unique and corresponding lipid features in lipidomes of different sample origins or organisms as long as profiles are captured using the same method and spectra meet the defined criteria for registering different system-level variations. The complete algorithm is packaged in two modular ExcelTM workbook templates for easy implementation.