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Pixelator Documentation

website·Indexed 33 days ago

https://software.pixelgen.com

Documentation for the Pixelator ecosystem, including the nf-core/pixelator pipeline for processing raw sequencing data (FASTQ) to PXL output files. It provides comprehensive analysis guides for Proximity Network Assay (PNA) and Multiplex Protein Expression (MPX) data using R (via pixelatorR and Seurat) and Python, covering workflows for cell segmentation, quality control, data integration with Harmony, differential abundance, and 2D/3D cell visualization.

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What's inside Pixelator

  1. Overview of the Proxiome Analysis Template (PAT)

    The Proxiome Analysis Template (PAT) is a complete, reproducible Quarto/R workflow designed for analyzing Proximity Network Assay (PNA) data generated by nf-core/pixelator. Built upon the pixelatorR package, the PAT provides a structured pipeline that guides users through quality control, clustering, annotation, abundance and proximity analyses, and optional statistical testing and cell visualization.

  2. Overview of pixelatorR for PNA and MPX data analysis

    pixelatorR is an R package designed for processing, analyzing, and visualizing Proximity Network assay (PNA) and Molecular Pixelation (MPX) single-cell data. It extends the Seurat toolbox by providing specialized S4 classes and tools specifically for PNA and MPX data structures.

  3. Overview of Molecular Pixelation (MPX) Technology

    Molecular Pixelation (MPX) is a first-generation spatial network technology used for single-cell spatial proteomics. It creates spatial networks of proteins on cell surfaces using DNA pixels (large RCA products) that encode spatial barcodes. The process involves fixing cells, binding an antibody panel with oligo conjugates and UMIs, and performing two rounds of pixelation (using DNA pixels A and B) to create spatial neighborhoods. These neighborhoods are then connected to form a single surface proteome map per cell. The resulting library is indexed and sequenced using compatible NGS sequencers.

  4. Overview of Pixelgen spatial network technology assays

    Pixelgen Technologies provides two generations of spatial network technology assays for spatial analysis: Molecular Pixelation (MPX) and Proximity Network Assay (PNA).

  5. Overview of Pixelator software options

    Pixelator is a suite of open-source software solutions designed for data processing and analysis of Molecular Pixelation (MPX) and Proximity Network (PNA) assays. Depending on the user's needs, it can be utilized in two distinct forms:

    1. nf-core/pixelator: A data processing pipeline that transforms initial FASTQ sequencing libraries into ready-to-analyze outputs.
    2. pixelator: A programming library used specifically for the downstream data analysis of MPX and PNA assays.

  6. Overview of Pixelgen software tools

    Pixelgen provides several tools for processing MPX and PNA data:

    • pixelator: The core library containing the logic for processing raw FASTQ reads into PXL files.
    • pixelatorR: The R implementation of the pixelator library for data analysis.
    • nf-core/pixelator: An open-source Nextflow workflow that packages the pixelator library in containers for reproducible, scalable scientific workflows.

  7. Overview of the nf-core/pixelator pipeline

    nf-core/pixelator is an analysis pipeline designed to process Proximity Network data. It converts raw sequencing data into PXL files using the pixelator command-line application, enabling downstream data analysis. The pipeline is built with the Nextflow workflow manager and follows the nf-core community standards for reproducibility and scalability.

  8. Generate Proxiome Summary Reports with PixelatorES

    PixelatorES is an R package designed to generate Proxiome Summary Reports. These reports provide a high-level summary of multi-sample experiments, including quality control (QC) metrics, statistics, and visualizations. It is primarily used for initial data exploration and determining the success of an experiment.

  9. Understand the MPX Edgelist structure

    The edgelist represents a bipartite graph of an MPX experiment, consisting of a list of uniquely identified antibodies per cell. Each row represents an edge identified by a UMI, UPIA (unique identifier for the A pixel), and UPIB (unique identifier for the B pixel). This spatial graph is used to infer spatial relationships between antibody molecules, calculate spatial statistics, and visualize cells.

  10. Understand Proximity Network Assay (PNA) technology

    Proximity Network Assay (PNA) is a spatial network assay used to study the cell surface proteome of over 150 proteins across thousands of cells simultaneously. It works by using barcoded antibodies and linkage oligos to record which proteins are adjacent to one another on a cell surface.

    The process involves:

    1. Fixating cells to immobilize the surface proteome.
    2. Binding a panel of barcoded antibodies to the cells.
    3. Generating Rolling Circle amplification products (RCP) from each antibody.
    4. Using linkage oligos to connect proximate RCPs via a gapfill ligation reaction, which incorporates Unique Molecular Identifiers (UMIs) from two neighboring antibodies into a single DNA linker molecule.
    5. Sequencing these linker molecules to reconstruct an interconnected spatial network of protein neighborhoods for each cell.

  12. Analyze 3D protein interactomics data using pixelator (Python)

    The pixelator Python software library and CLI tool provides methods and algorithms specifically designed for the processing, analysis, and visualization of 3D protein interactomics data, focusing on protein abundance, polarization, and co-localization.