Downstream quantitative analysis/statistics
Trainer: Lieven Clement
Overview: This session focuses on the statistical concepts for peptide identification, quantification, and differential analysis. Moreover, more advanced experimental designs and blocking will also be introduced. The course will rely exclusively on free and user-friendly open-source tools in R/Bioconductor. The session will provide a solid basis for beginners, but will also bring new perspectives to those already familiar with standard data interpretation procedures in proteomics.
You can sharpen your background knowledge on Mass Spectrometry, Proteomics & Bioinformatics for Proteomics here: Mass Spectrometry and Bioinformatics for Proteomics
Notice that the materials on “Downstream quantitative analysis/statistics” include all R-code that is used to do all data-analyses and plots. You are not expected to learn and review the code as we will do all analyses using a Graphical User Interface. Note, that it is also not necessary to view the clips on the R-code. They are added for your reference and for participants that would like to start to develop and automate their proteomics data analysis in R/Rmarkdown scripts.
Learning outcomes
By the end of this session you will be able to:
- Shotgun proteomics data, and quantification using label-free precursor peptide (MS1) ion intensities
Lectures and materials:
- 2024 Lectures and practical materials page
- 2024 datasets for practicals
- 2023 Lectures and practical materials page
- Statistical Methods for Quantitative MS-based Proteomics: Part I – Preprocessing:
- Statistical Methods for Quantitative MS-based Proteomics: Part II – Differential Abundance Analysis
*Note, that the pdf also includes the R code needed for each plot. This code is hidden on the website and you do not have to learn to understand the code because we will use a GUI in the tutorials.
Tutorials for hands-on:
- Preprocessing and statistical analysis wit msqrob2 for experiments with simple designs
- Statistical analysis with msqrob2 for experiments with more complex designs
Video material
The video material of the course can be found on https://statomics.github.io/PDA21/ where the clips are embedded in the online learning materials. The clips are also available as two YouTube playlists: