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Introduction to pixelatorR

pixelatorR is an R package designed for processing, analyzing, and visualizing Proximity Network assay (PNA) and Molecular Pixelation (MPX) single-cell data. This package extends the capabilities of the Seurat toolbox, providing specialized tools and data structures for working with PNA and MPX data in R.

Multiple tutorials are provided to help users get started with the package, covering steps from data loading to advanced analyses. For MPX data, you can refer to MPX analysis tutorials and for PNA data, refer to PNA analysis tutorials.

Key Features​

  1. Data Structures: pixelatorR introduces specialized S4 classes for handling PNA and MPX single-cell data, seamlessly integrating with the Seurat ecosystem.

  2. Data Processing:

    • Loading and processing PNA/MPX data
    • Cell graph analysis
    • Differential analysis (abundance, colocalization, polarity, and proximity)
    • Graph layout and visualization

  3. Visualization:

    • Cell count plots
    • Colocalization heatmaps
    • Density scatter plots
    • Graph layouts
    • Molecule rank plots
    • Tau plots

Integration and Dependencies​

pixelatorR is built to work harmoniously with:

  • Seurat v5 for single-cell analysis
  • Various visualization packages (ggplot2, plotly, ggraph)
  • Data manipulation tools (dplyr, tidyr)
  • Graph analysis libraries (igraph, tidygraph)

Use Cases​

The package is particularly valuable for:

  • Single-cell spatial proteomics analysis
  • Cell graph analysis and visualization
  • Differential analysis of protein abundance and colocalization
  • Processing and analyzing PNA and MPX data

Development and Support​

pixelatorR is actively supported with regular updates and comprehensive documentation. The package is open-source and available under the GPL license, accessible through github repository: https://github.com/PixelgenTechnologies/pixelatorR. We welcome community contributions and improvements.