Description
Mass spectrometry-based proteomics is showing great potential for giving new biological insight and for discovery of biomarkers. However, the usability of results from proteomics experiments is highly dependent on data analysis and experimental design. 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.
Goals
After completion of this course, students are expected to be able to plan quantitative proteomics experiments based on project goals. Factors to consider include possible workflows, time, samples and replicates. An important goal is also to gain insight into how to handle and evaluate data from proteomics experiments. This includes data management, significance evaluation, putting the data into biological context and formatting for publication.
Content:
Lectures in the course will cover: Proteomics experimental planning, encompassing selection of workflow and sample selection. Raw data handling and analysis using informatic tools, including validation of peptide and protein identifications. Formatting of data for publication and deposition in public repositories. 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 (isobaric labels and label free), and discussion of significance and interpretation of the results.
Recommended qualifications:
Basic knowledge of mass spectrometry-based proteomics. For students that are new to proteomics, it is recommended to attend the SCIBLU proteomics courses first: http://www.lth.se/sciblu/proteomics_services/courses/
Contact: Fredrik Levander fredrik.levander (AT) immun.lth.se
