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A python-based pipeline for analyzing whole-slide imaging mass cytometry (WS-IMC) data from pancreatic ductal adenocarcinoma (PDAC).

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sophiamjiali/whole-slide-imc-pipeline

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Whole-slide IMC Pipeline

A python-based pipeline for analyzing whole-slide imaging mass cytometry (WS-IMC) data from pancreatic ductal adenocarcinoma (PDAC).

Completed on behalf of Campbell Lab at the Lunenfeld-Tanenbaum Research Institute, Mount Sinai Hospital.

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Project Overview

This repository contains an end-to-end pipeline for analyzing whole-slide imaging mass cytomegry (IMC-WS) images in pancreatic ductal adenocarcinoma (PDAC) datasets.

  • single-cell segmentation is not possible, pixel-level data
  • trained CNN on (insert stats) WS-IMC and (insert stats) TMA-IMC images for feature extraction of sliding windows
  • evaluate information gain/adequacy of TMA-based approaches for assessing spatial heterogeneity

...

Workflow

The pipeline consists of the following main steps:

1. Configuration:

2. Preprocessing:

3. Feature Extraction

4. Clustering:

5. Downstream Analysis:

6. Evaluation of TMA-IMC:

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A python-based pipeline for analyzing whole-slide imaging mass cytometry (WS-IMC) data from pancreatic ductal adenocarcinoma (PDAC).

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