This repository contains the supporting materials for the manuscript "The National Phenome Centre’s Open Platform for LC-MS-Based Metabolomics".

Contents:

• LC-MS Metabolite annotations: Metabolite annotations (retention time and m/z values) for 5 NPC LC-MS profiling assays.
  • Reversed phase positive ion mode (RPOS)
  • Reversed phase negative ion mode (RNEG)
  • HILIC positive ion mode (HPOS)
  • Lipidomic reversed phase positive ion mode (LPOS)
  • Lipidomic reversed phase negative ion mode (LNEG)
• Protocols: Standard operating procedures (SOPs) and corresponding proformas (PRO) to document the outlined procedures in pdf format.
  • NPC.SOP.CC004_v1.1: Sample sorting and LIMS logging
  • NPC.SOP.CC005_v2.1: Formatting and replication of samples
  • NPC.SOP.MS001_v2.1: Calibration and LockMass
  • NPC.SOP.MS002_v2.1 and NPC.PRO.MS002_v2.1: UPLC, sample manager and Q-ToF system performance check
  • NPC.SOP.MS003_v2.1 and NPC.PRO.MS003_v2.1: RPC UPLC-QTOF analysis of lipids in human plasma and serum
  • NPC.SOP.MS004_v2.1 and NPC.PRO.MS004_v2.1: HILIC UPLC-QTOF analysis of small molecules in human plasma and serum
  • NPC.SOP.MS005_v2.1 and NPC.PRO.MS005_v2.1: RPC UPLC-QTOF analysis of small molecules in human urine
  • NPC.SOP.MS006_v2.1 and NPC.PRO.MS006_v2.1: HILIC UPLC-QTOF analysis of small molecules in human urine
  • NPC_ExampleTraces.pfg: Representative gradient and system pressure traces for each chromatographic method (RPC and HILIC for small molecule profiling, and RPC for lipid profiling).
    
         

                   NPC LC-MS metabolic profiling workflow

Additional Links:

• Targeted Extraction of Annotated Metabolites (PeakPantheR): Comprehensive training materials and documentation for the targeted extraction of annotated metabolites from LC-MS global profiling data, including vignettes and exemplar data.
• Data Pre-processing and Quality Control (nPYc-Toolbox): A Python implementation of the NPC toolchain for the import, pre-processing and quality control of metabolic profiling datasets.
• Data Pre-processing and Quality Control Tutorials (nPYc-Toolbox): Comprehensive training materials and documentation for data pre-processing and QC, including Jupyter notebooks, full documentation and exemplar data.