E5020 Analysis of Nontarget MS Data

Faculty of Science
Spring 2023
Extent and Intensity
2/0/0. 2 credit(s) (plus extra credits for completion). Type of Completion: zk (examination).
Teacher(s)
Helge Hecht, M.Sc. (lecturer)
Elliott James Price, PhD (lecturer)
Mgr. Eva Budinská, Ph.D. (lecturer)
Žiga Tkalec, PhD (lecturer)
Kapil Mandrah, PhD (lecturer)
Guaranteed by
prof. RNDr. Ladislav Dušek, Ph.D.
RECETOX – Faculty of Science
Contact Person: Mgr. Eva Budinská, Ph.D.
Supplier department: RECETOX – Faculty of Science
Timetable
Tue 10:00–11:50 F01B1/709
Prerequisites
Knowledge of advanced statistics; multivariable analysis; Basic R skills; Fundamentals of Separation Methods; Fundamentals of Mass Spectrometry
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
The capacity limit for the course is 30 student(s).
Current registration and enrolment status: enrolled: 1/30, only registered: 0/30, only registered with preference (fields directly associated with the programme): 0/30
fields of study / plans the course is directly associated with
Course objectives
The aim of this course is to teach students (i) the fundamentals of mass spectrometry data acquired for non-target studies, (ii) how to use existing software tools and (iii) how to use the knowledge gained to choose algorithms & methods for optimal processing of their data.
Learning outcomes
At the end of this course, the students: - know the principles of mass spectrometry - know different approaches to separation and detection of molecules with a focus on liquid and gas chromatography - know basic data formats used in MS data processing - based on data type, methodology used and molecule type, select methods and algorithms for data pre-processing (normalization, filtering of signal, deconvolution, peak detection,...) and apply it to the data - are able to work with specialized SW and platforms for MS data analysis (MZmine,OpenMS, R packages, galaxy, ...) - perform statistical analysis of the pre-processed data - group comparison, group discovery, biomarker detection, pathway analysis
Syllabus
  • 1. Fundamentals of Instrumental Analysis (Chromatography, Mass Spectrometry); 2. Fundamentals of applications and experiment design (-omics, sample specifics, hypothesis); 3. Instrumental methods & data characteristics (acquisition methods, terminology, data characteristics); 4. Introduction to MS Data Processing; 4.1 Centroiding; Noise detection; filtering; mass accuracy; 4.2 Peak Detection + Integration; 4.3 Peak Deconvolution & Alignment; 4.4 Compound Identification; 5. Software for MS Data processing; 5.1 GUI tools (MSDial); 5.2 Package based workflows (R/Python); 5.3 Cloud Solutions (XCMSOnline, GNPS, MetaboAnalyst, Galaxy); 6. Detection of biomarkers, group comparison, clustering, pathway analysis.
Literature
    recommended literature
  • MILLER, Gary W. The exposome : a new paradigm for the environment and health. Second edition. Amsterdam: Academic Press, An imprint of Elsevier, 2020, xxii, 275. ISBN 9780128140796. info
  • PETERS, K, J BRADBURY, S BERGMANN, M CAPUCCINI, M CASCANTE, Atauri P DE, TMD EBBELS, C FOGUET, R GLEN, A GONZALEZ-BELTRAN, UL GUNTHER, E HANDAKAS, T HANKEMEIER, K HAUG, S HERMAN, Petr HOLUB, M IZZO, D JACOB, D JOHNSON, F JOURDAN, N KALE, I KARAMAN, B KHALILI, PE KHONSARI, K KULTIMA, S LAMPA, A LARSSON, C LUDWIG, P MORENO, S NEUMANN, JA NOVELLA, O Donovan C, JTM PEARCE, A PELUSO, ME PIRAS, L PIREDDU, MAC REED, P ROCCA-SERRA, P ROGER, A ROSATO, R RUEEDI, C RUTTKIES, N SADAWI, RM SALEK, SA SANSONE, V SELIVANOV, O SPJUTH, D SCHOBER, EA THEVENOT, M TOMASONI, M VAN RIJSWIJK, M VAN VLIET, MR VIANT, RJM WEBER, G ZANETTI and C STEINBECK. PhenoMeNal: processing and analysis of metabolomics data in the cloud. GIGASCIENCE. OXFORD: OXFORD UNIV PRESS, 2019, vol. 8, No 2, 12 pp. ISSN 2047-217X. Available from: https://dx.doi.org/10.1093/gigascience/giy149. URL info
  • Mass spectrometry in metabolomics : methods and protocols. Edited by Daniel Raftery. New York: Humana Press, 2014, xvi, 360. ISBN 9781493912575. info
    not specified
  • SKOOG, Douglas A., F. James HOLLER and Stanley R. CROUCH. Principles of instrumental analysis. Seventh edition. Boston: Cengage Learning, 2018, xx, 959. ISBN 9781305577213. info
  • GROSS, Jürgen H. Mass spectrometry : a textbook. Edited by Peter Roepstorff. 2nd ed. Berlin: Springer, 2011, xxiv, 753. ISBN 9783642107092. info
Teaching methods
The course is taught in English. The form of the lecture will be determined on individual agreement.
Assessment methods
The exam will be oral.
Language of instruction
Czech
Further Comments
Study Materials
The course is taught annually.
The course is also listed under the following terms Spring 2024, Spring 2025.
  • Enrolment Statistics (Spring 2023, recent)
  • Permalink: https://is.muni.cz/course/sci/spring2023/E5020