Implementation of this software in a diagnostic setting occurs in the sole responsibility of the treating physician. Usage of this software occurs at the risk of the user. The authors may not be held liable for any damage (including hardware) this software might cause. Use is explicitly restricted to academic and non-for-profit organizations.
Tip
The application hosted by the Institute of Pathology of University Hospital Basel is available here:
CQcase
Due to storage space restrictions, the only available preprocessing method is illumina, minimum probes per bin - 20, and the bin size - 50000.
In the app, you can interact with precalculated summary plots generated by the CQall plotter. The available graph options are:
- Select a methylation class to plot: Choose between available summarized cohort plots
- Downsizing target selection: Choose between results with array specific or overlapping probes analysis, whenever the non-array specific results are available
- Select minimum probes per bin:
- Select bin size
- Choose preprocessing method
After configuring your settings:
- A methylation class name and the number of used Sentrix IDs will appear.
- An interactive CNV summary plot will be displayed below the dropdown selections.
Interaction with the plot:
- Hover over segment points to see details.
- Click on data points to view all genes within that segment.
- Use box or lasso tools to view selected genes in the table below.
Genes selection grid:
- This table lists all available data for the selected methylation class, with search and filtering options for ease of use.
- Clicking a gene name opens it on GeneCards in a new tab.
Gene selection:
- Select genes by checking the boxes next to gene names in the table.
- Click "Add to plain text gene submission" to include selected genes in the text field or paste pre-defined HUGO symbols directly into the gene submission box.
- Use the "Plot genes" button to visualize the genes listed in the text box. Note that the text input persists across changes in methylation classes or settings.
Plot toolbar:
- Features include saving plots as PNG, zooming, panning, box/lasso selection, and resetting the view. Double-clicking the plot also resets the view.
Download options:
- Download the current gene selection or the entire CNV data from the bottom table by clicking "Download segment genes" or "Download methylation class CNV table".
- Save the plot in an interactive HTML format with the "Download plot as html" button.
URL sharing:
- At the bottom of the page, a URL is provided that preserves all current settings. Users can share this URL or save it for later use.
This functionality also supports controlling plot settings via URL parameters, for example:
https://epidip.usb.ch/cqall/?methylation_class=GBM_RTK_II?preprocessing_method=illumina?min_probes=20?bin_size=50000?downsize_to=EPIC_v2_EPIC_v1_to_HM450K?plotgenes=BRCA2+BRE
Note
If you prefer to use CQall with Docker, skip to the CQmanager repository or the Running CQall with Docker compose part of this README
Install Python3.11 for your platform (works also with python 3.10 and 3.12). You can find installation guide here or here or here.
The installations depend also on git, which you can install in your terminal (on Ubuntu), if missing, as follows:
sudo apt update && sudo apt install git-all- Install uv if it has not been installed yet.
- Navigate to a directory, where you would like to install CnQuant applications.
- Initiate a new project called, for example cqall, and install CQall:
uv init cqall \
&& cd cqall \
&& uv venv --python 3.11 \
&& uv pip install "git+https://github.com/neuropathbasel-pub/CQall"- Create a directory where you wish to install CQall and enter the directory.
- Create python3.10 or python3.11 or python3.12 virtual environment (you might need to adjust python path below):
/usr/bin/python3.11 -m venv .venvor
python3.11 -m venv .venv- Activate the virtual environment:
source .venv/bin/activate- Install CQall:
pip install --upgrade pip setuptools \
&& pip install git+https://github.com/neuropathbasel-pub/CQallOne-liner
mkdir cqall \
&& cd cqall \
&& /usr/bin/python3.11 -m venv .venv \
&& .venv/bin/python3 -m pip install --upgrade pip setuptools \
&& .venv/bin/python3 -m pip install git+https://github.com/neuropathbasel-pub/CQallNote
All of the CnQuant applications require a filled-out .env and a data annotation file as well as Illumina manifests and gaps.csv.gz file, as described in the CnQuant repository.
Steps:
- Enter the directory where you have installed the app.
- Activate the virtual environment:
source .venv/bin/activate- Run the app in the console:
gunicorn cqall.app:server --workers=1 --bind=0.0.0.0:8050- Access CQall in your browser, by default:
http://localhost:8050/cqall/Instructions on how to use CQmanager for running CnQuant applications are in the CQmanager repository.
Running CQall with Docker compose
Note
This requires a filled-out .env and a data annotation file, as described in the CnQuant repository.
Download the docker-compose.yml to the current directory or adjust its path in the command below.
Following, run the following command in the directory with the docker-compose.yml file:
path_to_your_env_file="/your_env_file_absolute_path.env"
USER_ID=$(id -u) GROUP_ID=$(id -g) docker compose -f docker-compose.yml --env-file $path_to_your_env_file run --rm cqall- Access CQall in your browser (the port depends on your .env file), by default:
http://localhost:8050/cqall/Running CQall with Docker-compose
Note
This requires filled .env file and data annotation file, as described in CnQuant repository.
Download the docker-compose.yml to the current directory or adjust its path in the command below.
Following, run the following command in the directory with your desired settings (you might adjust the preprocessing_method, bin_size and min_probes_per_bin arguments):
Note
The GROUP_ID has to match the file permissions group. You might need to adapt it if you are analyzing data with a different user and group.
USER_ID=$(id -u)
GROUP_ID=$(id -g)
path_to_your_env_file="/your_env_file_absolute_path.env"
USER_ID=$USER_ID GROUP_ID=$GROUP_ID docker compose -f docker-compose.yml --env-file $path_to_your_env_file -p cqall upInstructions on how to use CQmanager for running CnQuant applications are in CQmanager repository.
This step is optional. The viewer applications use Redis for caching. To install Redis, please follow the official installation guide.
Install Python3.11 for your platform (works also with python 3.10 and 3.12). You can find installation guide here or here or here.
- Create a directory where you wish to install CQall and enter that directory.
- Create python3.11 virtual environment (you might need to adjust python3.11 path below):
python3 -m venv .venv- Activate the virtual environment:
source .venv/bin/activate- Install CQall:
pip install --upgrade pip setuptools \
&& pip install git+https://github.com/neuropathbasel-pub/CQall- Enter the directory where you have installed the app.
- Activate the virtual environment:
source .venv/bin/activate- Start CQall with gunicorn (you can change the IP or port in the --bind argument or the number of workers for the application in --workers):
port="8050"
gunicorn cqall.app:server --workers=1 --bind=0.0.0.0:$port- Access CQall in your browser:
http://localhost:port/cqall
where port is the port set up in the .env file for CQall, the same as you have set up for starting the app with gunicorn.