Quantitative Proteomics: Case Studies

Two-day Short Course, ASMS 2023, 2023


In Case study 1, we analyzed an SRM proteomics dataset from a case-control study of heart failure using a salt-sensitive rat model, which included biological and technical replicates. Participants explored the importance of study design (in particular of normalization and randomization), the importance of visualizing chromatograms (and signal interferences), and setting up, conducting and interpreting the results of statistical analyses in MSstats.

In Case study 2, we analyzed a modern Orbitrap DIA dataset from the MacCoss lab proteomics dataset of cerebrospinal fluid from a Parkinson’s and Alzheimer’s cohort with healthy age-matched controls. Participants learned how to handle and analyze DIA data in Skyline and in MSstats, and explored how data collection and processing can influence our statistical analysis; including batching, filtering, normalization, and missing values.