samplePy

Simple Analysis for Multimodal Pipelines of Light and Electron imaging (samplePy)

A pipeline for analyzing and integrating light microscopy (LM) and electron microscopy (EM) data in neuroscience experiments. samplePy is designed to process, analyze, and correlate multi-modal imaging data from neuronal samples. It provides a structured workflow from raw data input to advanced analysis and visualization.

Pipeline Structure

The pipeline is organized into several key stages:

1. LM Data Processing

   • Load experiments and create samples
   • Register LM trials and stacks
   • Segment cells and extract traces
   • Normalize, deconvolve, and correlate traces

2. LM Stack Processing

   • Preprocess LM stacks
   • Register to reference stack
   • Segment with EM-warped masks
   • Extract markers from channels

3. EM Data Processing

   • Segment cells using SOFIMA alignment and Cellpose
   • Segment glomeruli
   • Find landmarks with BigWarp
   • Register to LM stack and trials

4. CLEM (Correlative Light and Electron Microscopy)

   • Register centroids using LUT (Look-Up Table)

5. Analysis

   • Functional-structural analysis (details to be implemented)

Key Features

• Integrated processing of LM trials, LM stacks, and EM stacks
• Advanced cell segmentation and trace extraction
• Cross-modality registration and correlation
• Flexible pipeline with modular steps

Usage