Valkenborg/SAILED

On this page we collect a series of R Markdown scripts that represent different analysis strategies for isobaric-label spectra for quantitative proteomics. Each script is a manual that illustrate how a certain strategies performs on a benchmark data set. Performance metrics and a dashboard with relevant visualizations are provided.

In this notebook series, we explore how different data analysis strategies affect the outcome of a proteomics experiment based on isobaric labeling and mass spectrometry. Start by reading the intro, and then pick a notebook of your interest!

If you wish to see the notebooks' underlying R code, visit the GitHub source repository.

Links to model-based-normalization workflows

• Unit scale strategy comparison
• Summarization strategy comparisons
• Normalization strategy comparisons
• Differential Expression Analysis (DEA) strategy comparisons

Links to data-driven-normalization workflows

• Unit scale strategy comparison
• Summarization strategy comparisons
• Normalization strategy comparisons
• Differential Expression Analysis (DEA) strategy comparisons

Extra analyses

• CONSTANd and median sweeping normalization methods applied to data on the appropriate scales