HTC-15 Short Course - Statistical analysis of chromatographic data: a practical guide

Course Overview

This introductory course covers all main aspects of analysis of chromatographic data. As data analysis lays at the interface between statistics and chromatography, both backgrounds are necessary. In light of this, I will review the range of techniques that are be available for extracting quantitative and qualitative information from chromatography, with emphasis on understanding the do's and don'ts.

Who Should Attend

This course is addressed to those currently involved in any chromatographic sub-discipline, interested in obtaining the maximum information out of the data generated. The audience should have a basic background in statistical analysis. All those working in disciplines in which the data treatment is critical (e.g. forensics, pharma and food) are specially encouraged to attend.

Course Outline

  • 1. Introduction.
  •    1.1. Why do we need statistics to deal with chromatographic data?
  • 2. Pre-processing methods
  •    2.1. Base-line correction
  •    2.2. Noise filtering
  •    2.3. Peak detection
  •    2.4. Peak detection in two-dimensional chromatography
  •    2.5. Peak tracking
  •    2.6. Chromatographic alignment
  •    2.7. Special topics with high-resolution mass spectrometry.
  • 3. Curve resolution methods
  •    3.1. Raw data vs. peak tables.
  •    3.2. Curve resolution & peak fitting. Chromatographic peak models.
  •    3.3. Second-order methods: AMDIS, MCR-ALS.
  •    3.4. Third-order methods: PARAFAC, PARAFAC2
  •    3.5. Advanced methods.
  • 4. Modelling & pattern recognition
  •    4.1. Exploration: PCA & HCA.
  •    4.2. Classification: SIMCA, PLS-DA, LDA, SVM.
  •    4.3. Multivariate modelling: PLS, RSVM.
  • 5. Applications
  •    5.1. Food & pharma
  •    5.2. Oil & gas
  •    5.3. Forensics
  •    5.4. Chemicals & polymers
  •    5.5. Omics
  • 6. Open discussion

Course Timings

  • 10:00 - 10:30 Coffee and Registration
  • 10:30 - 12:30 Session 1 (2hrs)
  • 12:30 - 13:15 Lunch
  • 13:15 - 14:30 Session 2 (1.25hrs)
  • 14:30- 14:45 Coffee Break
  • 14:45 - 16:00 Session 3 (1.25hrs)

About the instructor

Gabriel Vivo-Truyols (1975) studied analytical chemistry at the University of Balearic Islands (Spain) and graduated with honours in 1998. In 2004 he obtained his PhD with honours from University of Valencia (Spain) on chemometrics methods for optimisation and data treatment of HPLC. His PhD dealt with the development of novel methods for optimization and data treatment in HPLC, and was awarded with the D.L. Massart award in chemometrics from the Belgian Chemometrics society in 2006, given every two years to the best PhD thesis in chemometrics, world-wide. In 2004 he joined the team of Peter Schoenmakers (University of Amsterdam), where he developed a research program focused on chemometric techniques for optimisation, calibration and data-treatment of two-dimensional chromatographic methods. In 2007 he joined the analytical chemistry team at BP in Sunbury (London area). He worked as chemometric specialist developing algorithms and software for GCxGC analysis of petroleum subproducts, as well as developing chemometrics methods for on-line infra-red analysis. In 2009 he re-joined the analytical-chemistry group of Peter Schoenmakers at University of Amsterdam as assistant professor. He left in 2017, keeping a position as guest researcher. He is currently scientific consultant for several multinationals in the area of data analysis, including BP, BASF and Agilent technologies, among others. Gabriel Vivo-Truyols has co-authored more than 60 papers and he has conducted successfully 5 PhDs in the area of data treatment in chromatography.