Agilent Mass Profiler Professional Software
Brochures and specifications | 2012 | Agilent TechnologiesInstrumentation
Modern mass spectrometry experiments generate vast and complex data sets that require advanced chemometric tools to extract meaningful relationships. Mass Profiler Professional (MPP) addresses this need by integrating multivariate statistics, pattern recognition, and visualization to transform raw spectral data into actionable insights across diverse applications in analytical chemistry.
This document introduces Agilent Mass Profiler Professional, a standalone software package tailored to the processing and interpretation of GC/MS, LC/MS, CE/MS, and ICP-MS data. It aims to streamline classification, comparison, and statistical evaluation of sample groups, and to integrate seamlessly with Agilent MassHunter and OpenLAB ChemStation workstations. The overview highlights MPP’s capabilities in unsupervised and supervised analysis, guided workflows, and advanced visualization.
MPP employs wizard-based guided workflows that simplify data import, normalization, filtering, and statistical testing. Core analytical methods include:
Instrument compatibility covers:
Additional modules include the integrated ID Browser for spectral library and database searches (METLIN, NIST, Fiehn) and empirical formula calculation, plus Pathway Architect for mapping multi-omic data onto curated pathways.
PCA score and loading plots demonstrate clear separation of sample groups (e.g., diet supplements in metabolic profiles). Volcano plots and ANOVA/Venn analyses identify statistically significant compounds affected by variables such as pH or toxin exposure. Clustering dendrograms reveal co-regulated metabolites across experimental conditions. Class prediction models built via PLS-DA accurately assign unknown samples to predefined groups, supporting applications in QC and drug development. Integrated ID Browser annotations accelerate compound identification, while pathway projection highlights impacted biological routes.
MPP delivers:
Emerging directions include tighter integration with R scripting for bespoke analyses, cloud-based collaborative projects, real-time data mining during acquisition, and incorporation of machine-learning pipelines. Expansion of spectral libraries and pathway databases will further enhance compound annotation and network analysis. Stand-alone Sample Class Predictor utilities will support decentralized QC workflows.
Agilent Mass Profiler Professional offers a comprehensive chemometrics environment that balances ease of use with powerful statistical, visualization, and identification capabilities. Its support for multiple MS platforms and modular extensions empowers researchers and laboratories to derive deep understanding from complex spectral data and to drive informed decisions across diverse application areas.
Software
IndustriesManufacturerAgilent Technologies
Summary
Significance of the Topic
Modern mass spectrometry experiments generate vast and complex data sets that require advanced chemometric tools to extract meaningful relationships. Mass Profiler Professional (MPP) addresses this need by integrating multivariate statistics, pattern recognition, and visualization to transform raw spectral data into actionable insights across diverse applications in analytical chemistry.
Objectives and Article Overview
This document introduces Agilent Mass Profiler Professional, a standalone software package tailored to the processing and interpretation of GC/MS, LC/MS, CE/MS, and ICP-MS data. It aims to streamline classification, comparison, and statistical evaluation of sample groups, and to integrate seamlessly with Agilent MassHunter and OpenLAB ChemStation workstations. The overview highlights MPP’s capabilities in unsupervised and supervised analysis, guided workflows, and advanced visualization.
Methodology and Instrumentation
MPP employs wizard-based guided workflows that simplify data import, normalization, filtering, and statistical testing. Core analytical methods include:
- Unsupervised classification: Principal Component Analysis (PCA) to uncover sample group separations and key contributing compounds.
- Statistical testing: t-tests, ANOVA (including one-way, two-way, repeated measures), Kruskal-Wallis, false discovery rate corrections, and post-hoc tests.
- Fold-change and volcano plots: interactive thresholds to highlight biologically relevant abundance changes.
- Clustering: k-means, hierarchical clustering, and self-organizing maps to detect co-varying entities and infer biochemical relationships.
- Supervised class prediction: PLS-DA, support vector machines, decision trees, naïve Bayes, and neural networks for sample classification and pipeline prioritization.
- Unique features: recursive re-mining of data sets and automated inclusion list export for Q-TOF MS/MS follow-up.
Instrument compatibility covers:
- GC/MS and Triple Quadrupole GC/MS – routine and high-speed MS/MS quantitation.
- TOF and Q-TOF LC/MS – high mass accuracy, dynamic range, and sensitivity.
- Triple Quadrupole LC/MS – sub-femtogram sensitivity with fast polarity switching.
- ICP-MS – advanced interference removal for complex matrices.
Additional modules include the integrated ID Browser for spectral library and database searches (METLIN, NIST, Fiehn) and empirical formula calculation, plus Pathway Architect for mapping multi-omic data onto curated pathways.
Main Results and Discussion
PCA score and loading plots demonstrate clear separation of sample groups (e.g., diet supplements in metabolic profiles). Volcano plots and ANOVA/Venn analyses identify statistically significant compounds affected by variables such as pH or toxin exposure. Clustering dendrograms reveal co-regulated metabolites across experimental conditions. Class prediction models built via PLS-DA accurately assign unknown samples to predefined groups, supporting applications in QC and drug development. Integrated ID Browser annotations accelerate compound identification, while pathway projection highlights impacted biological routes.
Benefits and Practical Applications
MPP delivers:
- Reduced training time and operator error through a unified interface for multiple MS platforms.
- Accelerated biomarker discovery in metabolomics and proteomics.
- Enhanced QA/QC workflows in food safety, environmental testing, forensics, petrochemical, toxicology, and biofuels.
- Comprehensive data mining enabling rapid hypothesis generation and validation.
Future Trends and Applications
Emerging directions include tighter integration with R scripting for bespoke analyses, cloud-based collaborative projects, real-time data mining during acquisition, and incorporation of machine-learning pipelines. Expansion of spectral libraries and pathway databases will further enhance compound annotation and network analysis. Stand-alone Sample Class Predictor utilities will support decentralized QC workflows.
Conclusion
Agilent Mass Profiler Professional offers a comprehensive chemometrics environment that balances ease of use with powerful statistical, visualization, and identification capabilities. Its support for multiple MS platforms and modular extensions empowers researchers and laboratories to derive deep understanding from complex spectral data and to drive informed decisions across diverse application areas.
Reference
- Agilent Technologies. Mass Profiler Professional Software User Guide. 2012.
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