PROFILE ANALYSIS

LC-MS-based metabolomics applications in drug discovery and development, clinical research, proteomics and food science all share the need for quick analysis of a large number of highly complex samples. These techniques require pattern recognition techniques that filter the relevant information from different sample groups and detect compounds that differentiate samples. ProfileAnalysis enables smooth and easy analysis using fully unsupervised methods like Principal Component Analysis (PCA) and supervised methods such as PLS or student’s t-test. It provides a complete set of tools for data pre-processing, in-depth statistical analysis, identification and feedback experiments. ProfileAnalysis has been designed to give beginners a head start in metabolomics and also to meet the needs of expert users. TECHNICAL DETAILS: ProfileAnalysis directly links statistical results with the original LC-MS data, enabling fast on-the-fly identification of potential biomarkers by SmartFormula. SmartFormula combines unique accurate mass and True Isotopic Pattern Analysis (TIP™) information, provided by Bruker´s ESI-TOF or FT-ICR mass spectrometers. • Feature extraction: The sophisticated peak detection algorithm “Find molecular features” extracts all relevant information when mining LC-MS data, even from complex metabolomics datasets. It combines the ions belonging to the same compound into one feature, i.e. isotopes, charge states, adducts or common neutral losses. • Retention time alignment: Metabolic profiling projects can use hundreds or even thousands of samples. An RT alignment algorithm in ProfileAnalysis corrects for possible retention time changes, even for non-linear retention time shifts. • Statistical analyses: The relevant information from complex Metabolomics datasets can be extracted by applying statistical analyses like PCA, PLS, hierarchical clustering, t-test or ANOVA. Implemented result plots like volcano plots, scores and loadings or Receiver operating characteristic (ROC) curves facilitate pinpointing possible biomarkers. ProfileAnalysis also enables easy export of data to statistical software packages like Matlab™, R™ or SIMCA-P™ (Umetrics). • Biomarker identification: SmartFormula enables straightforward identification of potential biomarkers within ProfileAnalysis. Using exact mass and isotopic pattern information, SmartFormula generates elemental formulae that can be queried in public databases like ChemSpider, KEGG* or Metlin via the CompoundCrawler module. APPLICATIONS: • Metabolic Profiler: System Solution • oTOF and qTOF Instruments: The high performance molecular formula solution • EVOQ GC-TQ: Performance and Reliability in an Easy to Use Platform • amaZon: Modern Ion Trap Systems • Metabolite Tools: Software for Metabolite Identification • TargetAnalysis: Software for Multitarget Screening.