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NCSPHD1238  Preprocessing of quantitative NMR data for Chemometric Analysis Volume 2014/2015

Course information

LanguageEnglish
Credit3 ECTS
LevelPh.D.
Duration
Placement
Block 3
Schedule
One week full work onsite with theoretical lectures including examples and exercises finalized with a PCA and an examination. The students will be able to follow all the examples on their own computers and they will work on their own data during exercises
Course capacityMax 20 participants
Continuing and further education
Study boardNatural Sciences PhD Committee
Contracting department
  • Department of Food Science
Course responsibles
  • Søren Balling Engelsen (2-82744f757e7e733d7a843d737a)
  • Francesco Savorani (4-7783847251778080753f7c863f757c)
Lecturers
Associate Professors Francesco Savorani and Flemming Hofmann Larsen
Saved on the 02-02-2015
Content

Quantitative nuclear magnetic resonance (qNMR) is becoming an integral part of many scientific areas, especially within metabolomics, and the handling of the data for the results to be quantitatively reliable is an important issue. This 5-day course has as main objective to introduce tools for pre-processing quantitative NMR data for subsequent multivariate data analysis (chemometrics).

Through lectures and exercises, the course will introduce the participants to important pre-processing methods used within NMR - normalization and alignment (referencing, icoshift) of data - and discuss problems, pitfalls and tricks of the trade in relation to quantitative use of NMR spectroscopy. The course will begin with an introduction to quantitative NMR, including possible artifacts which can occur during acquisition and transformation and possibly spoil quantitative features, and the course will end with the participants doing a principal component analysis (PCA) on their own pre-processed NMR data.
The content of the course is:
Day 1 - Introduction to quantitative NMR, together with Matlab and importing NMR data
Day 2 - Dataset structure, cleaning and Normalization
Day 3 - Alignment 1
Day 4 - Alignment 2 together with basic chemometrics in LatentiX and advanced chemometrics in Matlab
Day 5 - PCA on own NMR dataset and final examination

Learning Outcome

 

After completing the course the student should be able to:

KNOWLEDGE
-How to measure and transform NMR spectra for them to be quantitative
-How to import Bruker NMR spectra into Matlab
-How to install new functions or toolboxes into matlab
-Reflections about raw NMR data (do I need them all?)
-Scripts setup and check (the help function)
-Automatic peak referencing
-Peak alignment: icoshift
-Normalization methods
-Importing processed data into LatentiX and some useful LatentiX tips
-Basic chemometrics in Latentix
-Advanced chemometrics in Matlab: Hints on interval based tools

SKILLS
-Suggest and apply pre-processing tools on quantitative NMR data

COMPETENCES
-Carry out chemometrics on proper pre-processed quantitative NMR spectra

 

Literature

Handouts and scientific papers provided during the course; scripts and source code provided during the course

Teaching and learning methods
Lectures and theoretical exercises.
Academic qualifications
Knowledge of chemometrics/exploratory data analysis and basic Matlab beforehand. Basic knowledge of 1H liquid-state NMR spectroscopy.
Remarks
For the project work (doing PCA) the participants should bring their own quantitative NMR data set but if not available a training NMR dataset will be provided.
Sign up

Contact Francesco Savorani frsa@food.ku.dk within Feruary the 20th, 2015

Exam
Credit3 ECTS
Type of assessment
Oral examination
In order to pass the course, all participants must perform a PCA on own data and present and discuss the result at an examination on site with the evaluation pass or fail
Marking scalepassed/not passed
Censorship formNo external censorship
Workload
CategoryHours
Lectures20
Theory exercises20
Preparation20
Project work20
Total80
Saved on the 02-02-2015