This repository contains Python scripts for the analysis of Tissue Microarray (TMA) core images, specifically designed to support the work published in the publication titled: "GASP-1 overexpression is involved in the development of BPH and progression of early-stage prostatic malignant diseases to prostate cancer." (Manuscript is currently under review.)
The scripts in this repository are organized as follows:
-
TMA-dearray.py: This script extracts individual cores from a TMA and saves them to a specified location as PNG. It takes a text file with positions as input, generated using Qupath. (https://qupath.github.io/) -
color_separate_functions.py: This module contains functions for the analysis of TMA core images. It includes functions for color separation, nuclei segmentation, and intensity analysis. -
color_separate.py: This script performs batch color separation and nuclei segmentation on multiple TMA core images. Results are saved in separate directories labeled inside the 'results' directory.
The code has been tested on Python 3.9.18
Before running the scripts, ensure you have the required dependencies installed. You can install them using the following:
pip install -r requirements.txtPlease note that openslide installation requires additional steps.
Ensure OpenSlide is installed by executing the following commands: (It should be already installed if you've executed the above pip command).
- Install openslide-python:
pip install openslide-python - Download the latest Windows binaries from https://openslide.org/download/.
- Extract the contents to a location for easy reference, preferably in the openslide directory in site-packages On our system: "C:/Users/Admin/Anaconda3/envs/Py39_base/Lib/site-packages/openslide/openslide-win64-20231011/bin"
In case you are unsure of your site packages directory, use the following script to find the location:
import sys
for p in sys.path:
print(p)
