Evaluation of proteomic differential expression analysis/modeling on the peptide rather than protein(group) level
Bioinformatics & Data Science
R programming
Statistics
Difficulty: Advanced
Master of Science
The project aims at exploring the differences and advantages of proteomic differential expression analysis on quantified peptide input data rather than pre-aggregated protein(group) information in the context of the autonomics analysis framework and following the work of Lieven Clement (Sticker et al. 2020; Goeminne et al. 2020).
References
Goeminne, Ludger J. E., Adriaan Sticker, Lennart Martens, Kris Gevaert, and Lieven Clement. 2020. “MSqRob Takes the Missing Hurdle: Uniting Intensity- and Count-Based Proteomics.” Analytical Chemistry 92 (9): 6278–87. https://doi.org/10.1021/acs.analchem.9b04375.
Sticker, Adriaan, Ludger Goeminne, Lennart Martens, and Lieven Clement. 2020. “Robust Summarization and Inference in Proteome-Wide Label-Free Quantification.” Molecular & Cellular Proteomics 19 (7): 1209–19. https://doi.org/10.1074/mcp.RA119.001624.