SC00039_project_NB

New project repo for python course with added license,

The purpose of this project is to make a python script that takes nd2 files from confocal microscope as input. Applies filter to the image to remove background noise and then count the number of nuclei. The nuclei are stained with a flourescent marker called DAPI. The nuclei should have some distance from one another, which means it should work to count the number of nuclei.

Data

The data to the the script is found in the folder called ICC_TEST_FOR_PYTHON. It contains the nd2 files called Figure1, FIgure2, Figure3. Each nd2 file contains 3 channels, but we will only focus on the first channel, channel0 since it contains the DAPI.

Packages needed for the script

import argparse
import os
import numpy as np
import matplotlib.pyplot as plt
import nd2
from skimage.filters import gaussian, threshold_otsu
from skimage.measure import label, regionprops_table
from skimage.segmentation import clear_border
from skimage.morphology import area_opening
import pandas as pd

How to run the script

Download the folder from github

Download the project files to your computer. You can do this by cloning the repository or downloading it as a zip file.

git clone https://github.com/Niklas-bb/SC00039_project_NB.git

Activate the environment

I used miniconda3 to run script. DOwnload if you do not already have.

Environment Setup

Conda environment is used. The provided environment.yml should include all packages required.

Step 1: To create the environment that will be used to install Jupyter Lab.

conda create -y -n Dapicount-env -c conda-forge python=3.9

Step 2: Activate environment

Activate the environment named Dapicount environment:

conda activate Dapicount

Running the code

I run the code using the following command in Git bash:

python DAPIcountfinal.py --folder "C:\path\to\your\nd2\files"

In my case the command to run the script is:

python DAPIcountfinal.py --folder "C:\Users\Niklas\OneDrive\Dokument\Sahlgrenska\Courses\python_for_biologists_SC00039\SC00039_project_NB\ICC_TEST_FOR_PYTHON"

But make sure you change the path to your folder.

Output

The output from the script is a number of images of the different stages of filtering steps. As the script is now you will get 3 images for each nd2 file. You can uncomment some lines in the python scipt to see more images of filtering stages. There is also an histogram of the sizes of the nuclei and then a table showing for example the nuclei count, area and mean instensity.

Niklas-bb / SC00039_project_NB

readme