Proteomics Data Analysis
Proteomikdataanalys

KIM065F, 3 credits

Valid from: Autumn 2016
Decided by: Mats Ohlin
Date of establishment: 2016-11-30

General Information

Division: Immunotechnology
Course type: Third-cycle course
Teaching language: English

Aim

Mass spectrometry-based proteomics is showing great potential for giving new biological insight and for discovery of biomarkers. However, the utility of results from proteomics experiments is highly dependent on data analysis and experimental design. The aim of the course is to give the attendants insight into the different steps of data analysis associated with mass spectrometry-based quantitative proteomics experiments, to allow for selection of workflow and to perform basic data analysis.

Goals

Knowledge and Understanding

For a passing grade the doctoral student must

• be able to describe basic principles of mass spectrometry-based identification of peptides and proteins.
• be able to describe advantages and disadvantages of different quantitative mass spectrometry-based workflows for proteomics.

Competences and Skills

For a passing grade the doctoral student must

• be able to handle mass spectrometry files in different formats.
• be able to perform protein identification from MS/MS data.
• be able to generate quantitative peptide reports from LC-MS/MS data.
• be able to select mass spectrometry-based workflows for protein measurements in different biological contexts

Judgement and Approach

For a passing grade the doctoral student must

• be able to critically evaluate quantitative proteomics studies.
• evaluate consequences of small or large sample groups, as well as of multiple hypothesis testing.

Course Contents

In this post-graduate course, properties of data from quantitative mass spectrometry-based proteomics will be discussed, based on hands-on examples with practical data analysis. The course attendants will get an overview of existing solutions for analysis of proteomics data. Lectures in the course will cover 1) proteomics experimental planning, encompassing selection of workflow and sample selection, 2) raw data handling and analysis using informatic tools, including validation of peptide and protein identifications, 3) formatting of data for publication and deposition in public repositories, and 4) basic statistical analysis of results, and functional annotation. The exercises will encompass planning of experiments and evaluation of data from two different quantitative proteomics workflows, and discussion of significance and interpretation of the results.

Course Literature

Slides and articles will be distributed

Instruction Details

Types of instruction: Lectures, seminars, exercises

Examination Details

Examination formats: Written assignments, seminars given by participants. Active participation in lectures, exercises and discussion seminar.
Grading scale: Failed, pass
Examiner:

Admission Details

Further Information

The course is given each autumn through the Postgraduate Courses in the Life Sciences (http://www.cmps.lu.se/life_sciences) if at least 6 students are accepted.

Course Occasion Information

Contact and Other Information

Course coordinators: