/ABBA_PQA

Pipeline for image preprocessing, quantification, and analysis using ABBA registrations

Primary LanguagePython

Overview This python package contains a complete workflow and data managment suite to bring raw images of brain sections all the way through network analysis using ABBA/QuPath to align to a reference atlas.

Stages

  1. Preprocessing - prepare raw image for ABBA
    • Configure data organization scheme
    • Extract downsampled images apply order, rotate, flip, proofread, and rename images to unified format
    • Extract/convert raw fullsize images to OME-TIFF + apply formatting
  2. Alignment
    • create Qupath projects for each animal, align in ABBA, export back to QuPath, then run QuPath scripts to export registrations to open format
  3. Nuclei detection
    • Nuclei quantification using StarDist, perform colocalization across image channels, and localize nuclei to atlas coordinates
  4. Data compilation
    • Threshold nuclei based on morphological properties, reduce nuclei detections to counts per region/hemisphere
  5. Analysis
    • Graph nuclei species per region across conditions (treatment, sex, etc.)
    • PCA analysis to isolate differences between conditional groups
    • Network analysis and interactive visualization - battery of graph analytics using NetworkX and Bokeh
    • Volumetric renderings of aggregated nuclei counts