Skip to content

PlexPipe - Multiplexed Image Analysis Pipeline

Logo Logo

Tests codecov Python Versions DOI

Overview

PlexPipe is a multiplex analysis pipeline that processes images through a series of modular steps, transforming raw whole-slide TIFF images into quantitative single-cell data.

Key Features

  • Input Data: The pipeline accepts sets of individual TIFF files, one per channel. Marker names and imaging rounds are read from Cell DIVE file names, or from a channel manifest CSV for data from any other platform (see Input Data and Channel Selection).
  • Remote Data Sourcing: Seamlessly source and transfer large-scale imaging datasets from institutional endpoints or personal collections using Globus. This ensures secure and reliable data movement directly into your processing environment (see: Globus Integration).
  • Data Integration: Outputs are stored as SpatialData objects, making them ready for downstream analysis within the scverse ecosystem or interactive exploration via the napari-spatialdata plugin.
  • Flexible Execution: PlexPipe can be implemented in two ways based on your needs:
    • Local/Interactive: Utilize the provided Python scripts or Jupyter Notebooks for smaller datasets or pipeline prototyping (see Execution Modes).
    • High-Throughput: For parallel processing and large-scale workflows, use the Nextflow-optimized version: plex-pipe-nextflow.

Used in

  • Yang Y, Bukkuri A, Poe D, McLaughlin J, Hao S, Brown DD, Kedziora KM, Stallaert W. Distinct p21 dynamics drive alternative routes to whole-genome duplication through a common CDK4/6-dependent polyploid G0 state. bioRxiv [Preprint]. 2026 Jan 15:2026.01.15.699545. doi: 10.64898/2026.01.15.699545. PMID: 41648389; PMCID: PMC12871375.