Mass spectrometry based proteomic experiments generate ever larger datasets and, as a consequence, complex data interpretation challenges. This course focuses on the statistical concepts for peptide identification, quantification, and differential analysis. Moreover, more advanced experimental designs and blocking will also be introduced.
msqrob2 provides a
- robust statistical framework for
- differential analysis of proteomics data with
- simple and compex designs.
The package include workflows that
- protein-level workflows that first summarise the peptide-level data to protein level expression values [@sticker2020]
- peptide-level workflows that immediately model the peptide intensities and provide inference on DE at the protein level [@goeminne2016] and [@sticker2020].
- hurdle workflow to improve the power in the presence of missing peptide intensities which are common in proteomics experiments.
Two group comparison: cptac spike-in study
- Designs with technical and biological repeats:francisella example
- Repeated measures design
- longitudinal design