BACKGROUND: An approach to the determination of day-to-day analytical robustness of LC-MS-based methods for global metabolic profiling using a pooled QC sample is presented for the evaluation of metabonomic/metabolomic data. A set of 60 urine samples were repeatedly analyzed on five different days and the day-to-day reproducibility of the data obtained was determined. Multivariate statistical analysis was performed with the aim of evaluating variability and selected peaks were assessed and validated in terms of retention time stability, mass accuracy and intensity. RESULTS: The methodology enables the repeatability/reproducibility of extended analytical runs in large-scale studies to be determined, allowing the elimination of analytical (as opposed to biological) variability, in order to discover true patterns and correlations within the data. CONCLUSION: The day-to-day variability of the data revealed by this process suggested that, for this particular system, 3 days continuous operation was possible without the need for maintenance and cleaning. Variation was generally based on signal intensity changes over the 7-day period of the study, and was mainly a result of source contamination.
BACKGROUND: An approach to the determination of day-to-day analytical robustness of LC-MS-based methods for global metabolic profiling using a pooled QC sample is presented for the evaluation of metabonomic/metabolomic data. A set of 60 urine samples were repeatedly analyzed on five different days and the day-to-day reproducibility of the data obtained was determined. Multivariate statistical analysis was performed with the aim of evaluating variability and selected peaks were assessed and validated in terms of retention time stability, mass accuracy and intensity. RESULTS: The methodology enables the repeatability/reproducibility of extended analytical runs in large-scale studies to be determined, allowing the elimination of analytical (as opposed to biological) variability, in order to discover true patterns and correlations within the data. CONCLUSION: The day-to-day variability of the data revealed by this process suggested that, for this particular system, 3 days continuous operation was possible without the need for maintenance and cleaning. Variation was generally based on signal intensity changes over the 7-day period of the study, and was mainly a result of source contamination.
Authors: Chandresh Nanji Ladva; Rachel Golan; Roby Greenwald; Tianwei Yu; Stefanie Ebelt Sarnat; W Dana Flanders; Karan Uppal; Douglas I Walker; ViLinh Tran; Donghai Liang; Dean P Jones; Jeremy A Sarnat Journal: J Breath Res Date: 2017-12-06 Impact factor: 3.262
Authors: Marissa G Baker; Yvonne S Lin; Christopher D Simpson; Laura M Shireman; Susan Searles Nielsen; Brad A Racette; Noah Seixas Journal: J Trace Elem Med Biol Date: 2018-11-03 Impact factor: 3.849
Authors: Lynn B Bailey; Patrick J Stover; Helene McNulty; Michael F Fenech; Jesse F Gregory; James L Mills; Christine M Pfeiffer; Zia Fazili; Mindy Zhang; Per M Ueland; Anne M Molloy; Marie A Caudill; Barry Shane; Robert J Berry; Regan L Bailey; Dorothy B Hausman; Ramkripa Raghavan; Daniel J Raiten Journal: J Nutr Date: 2015-06-03 Impact factor: 4.798
Authors: Katrice A Lippa; Juan J Aristizabal-Henao; Richard D Beger; John A Bowden; Corey Broeckling; Chris Beecher; W Clay Davis; Warwick B Dunn; Roberto Flores; Royston Goodacre; Gonçalo J Gouveia; Amy C Harms; Thomas Hartung; Christina M Jones; Matthew R Lewis; Ioanna Ntai; Andrew J Percy; Dan Raftery; Tracey B Schock; Jinchun Sun; Georgios Theodoridis; Fariba Tayyari; Federico Torta; Candice Z Ulmer; Ian Wilson; Baljit K Ubhi Journal: Metabolomics Date: 2022-04-09 Impact factor: 4.747