This repository contains a jupyter notebook and scripts to take you through an example ContactTracing analysis, as described in: Non-cell-autonomous cancer progression from chromosomal instability by Li, J et al , 2023: https://www.nature.com/articles/s41586-023-06464-z.
The code can all be run within a docker image. Commands to get started:
WORKDIR=/local/workdir # set this to directory where you keep your input files
mkdir -p $WORKDIR # create directory if doesn't exist
cd $WORKDIR
git clone https://github.com/LaughneyLab/ContactTracing_tutorial.git
docker pull docker.io/biohpc/scrna2023
docker run --rm -d -v $WORKDIR:/data -p 8888:8888 docker.io/biohpc/scrna2023 /root/scripts/startJupyter.sh /data
This should output a container ID (or you can retrieve it with docker ps). You can use this container ID to get the notebook token using the command: docker exec <containerID> jupyter server list. This should provide the URL/token you need to log into the jupyter notebook.
Use your browser to go to this URL, or you can go to localhost:8888 and enter the token.
Then, open the notebook, which will be stored in /data/ContactTracing_tutorial/tutorial.ipynb. You will need input files including an anndata file and an interactions file -- these are described in more detail in the notebook. You can place the files in $WORKDIR on your machine, and they will be found in /data within in the notebook.
A notebook focused on interactive visualization of ContactTracing results can be found here: https://github.com/LaughneyLab/ContactTracing-Viz/blob/master/interactive_notebook.ipynb