1 Introduction

In this tutorial, we’ll walk you through the process of modelling single-cell proteomics (SCP) data using the scplainer approach (Vanderaa and Gatto (2024)). By the end of this vignette, you will be able to:

  • Define and estimate a model suitable for SCP data
  • Filter peptides based on the patterns of missing values
  • Exploring the model output through analysis of variance
  • Exploring the model output through differential abundance analysis
  • Exploring the model output through component analysis
  • Perform batch correction to remove unwanted technical artefacts

The last point will allow you to generate SCP data that is suitable for downstream analysis, such as clustering or trajectory inference. The figure below provides a roadmap of the workflow: