🐊 Getting Started with CSPOT¶
Kindly note that CSPOT is not a plug-and-play solution. It's a framework that requires significant upfront investment of time from potential users for training and validating deep learning models, which can then be utilized in a plug-and-play manner for processing large volumes of similar multiplexed imaging data.
There are two ways to set it up based on how you would like to run the program
- Using an interactive environment like Jupyter Notebooks
- Using Command Line Interface
Before we set up CSPOT, we highly recommend using a environment manager like Conda. Using an environment manager like Conda allows you to create and manage isolated environments with specific package versions and dependencies.
Download and Install the right conda based on the opertating system that you are using
Create a new conda environment¶
# use the terminal (mac/linux) and anaconda promt (windows) to run the following command
conda create --name cspot -y python=3.9
conda activate cspot
Install cspot
within the conda environment.
pip install cspot
Interactive Mode¶
Using IDE or Jupyter notebooks
pip install notebook
# open the notebook and import CSPOT
import cspot as cs
# Go to the tutorial section to follow along
Command Line Interface¶
wget https://github.com/nirmalLab/cspot/archive/main.zip
unzip main.zip
cd cspot-main/cspot
# Go to the tutorial section to follow along
Docker Container¶
docker pull nirmallab/cspot:cspot
# Go to the tutorial section to follow along