Guides users on the initial steps, including system requirements, downloading Musta, installation instructions, and verifying the installation.
To install and run Musta, it is essential to have Docker installed on your computer. Docker is a containerization platform that ensures consistency and compatibility in running Musta across different computing environments.
If you do not have Docker installed, you can download and install it by following the instructions provided in the official Docker documentation: Docker Installation Guide.
Please ensure that Docker is properly configured and running on your system before proceeding with the installation of Musta.
To obtain Musta, you can clone the official Musta repository using Git. Open a terminal or command prompt and use the following Git command:
git clone https://github.com/next-crs4/musta.git
This command will download the latest version of Musta to your local system. Once the repository is cloned, you can proceed with the installation and configuration steps to set up Musta for your somatic mutation analysis tasks.
The installation could require several minutes
cd musta
make bootstrap
This command will initiate the installation and configuration process, ensuring that Musta is ready for use.
[+] Building 384.6s (20/20) FINISHED
=> [internal] load build definition from Dockerfile 0.1s
=> => transferring dockerfile: 1.37kB 0.0s
=> [internal] load .dockerignore 0.1s
=> => transferring context: 2B 0.0s
=> [internal] load metadata for docker.io/library/python:3.8 0.0s
=> [internal] load build context 0.2s
=> => transferring context: 1.18MB 0.0s
=> [ 1/15] FROM docker.io/library/python:3.8 0.3s
=> [ 2/15] RUN mkdir /code 0.2s
=> [ 3/15] WORKDIR /code 0.1s
=> [ 4/15] COPY . /code 0.1s
=> [ 5/15] RUN mkdir /config 0.4s
=> [ 6/15] ADD /config/* /config/ 0.1s
=> [ 7/15] RUN apt-get -qq update &&
apt-get install --no-install-recommends -y dialog apt-utils software-properties-common git wget curl bzip2 &&
apt-get autoremove -y && apt-get clean && rm -rf /var/lib 18.4s
=> [ 8/15] RUN groupadd -g 1000 appuser && useradd -m -u 1000 -g appuser appuser 0.5s
=> [ 9/15] RUN curl -L https://repo.anaconda.com/miniconda/Miniconda3-py38_4.12.0-Linux-x86_64.sh >
miniconda.sh && sh miniconda.sh -b -p /opt/conda && rm miniconda.sh 16.2s
=> [10/15] RUN conda update -n base -c defaults conda 54.1s
=> [11/15] RUN conda config --set channel_priority strict 0.6s
=> [12/15] RUN conda create -q -y -c conda-forge -c bioconda -n musta python=3.8 snakemake=7.15 &&
conda clean --all -y 282.0s
=> [13/15] RUN sh /config/create_paths.sh 0.4s
=> [14/15] RUN cd /code/src && make install && cd /code 4.7s
=> [15/15] RUN echo "source activate musta" > ~/.bashrc 0.4s
=> exporting to image 5.7s
=> => exporting layers 5.7s
=> => writing image sha256:bb170cfc65469c4a3445a04c3b21c843c5151e84ac8276107323325da973c901 0.0s
=> => naming to docker.io/library/musta:Dockerfile 0.0s
Ready to start. Try:
musta --help
Following these steps, you will have successfully installed Musta on your system, and it will be ready for somatic mutation analysis. You can now proceed to configure and use Musta for your specific research needs.
To confirm that the Musta Docker image has been successfully built, you can use the docker images command.
Open a terminal or command prompt and enter the following command:
docker images
After running this command, you should see an output that resembles the following:
REPOSITORY TAG IMAGE ID CREATED SIZE
musta Dockerfile bb170cfc6546 2 hours ago 2.48GB
The output should display the “musta” repository, “Dockerfile” tag, image ID, creation date, and image size. If you see similar information in your output, it indicates that the Musta Docker image has been successfully built and is ready for use in your environment.
To confirm that the Musta Command Line Interface (CLI) is correctly installed,
you can use the musta --help command. Open a terminal or command prompt and enter the following command:
musta --help
When you run this command, you should see an output similar to the following:
usage: musta [-h] [--config_file PATH] [--logfile PATH]
[--loglevel {DEBUG,INFO,WARNING,ERROR,CRITICAL}]
{detect,classify,interpret} ...
End-to-end pipeline to detect, classify and interpret mutations in cancer
optional arguments:
-h, --help show this help message and exit
--config_file PATH, -c PATH
configuration file
--logfile PATH log file (default=stderr)
--loglevel {DEBUG,INFO,WARNING,ERROR,CRITICAL}
logger level.
subcommands:
valid subcommands
{detect,classify,interpret}
sub-command description
detect Somatic Mutations Detection.
1. Multiple Variant Calling: mutect, lofreq, varscan,
vardict, muse, strelka.
2. Ensemble consensus approach to combine results and
to improve the performance of variant calling
classify Variant Annotation
Functional annotation of called somatic variants
interpret Somatic Mutations Interpretation:
1. Identification of cancer driver genes
2. Check for enrichment of known oncogenic pathways.
3. Infer tumor clonality by clustering variant allele frequencies.
4. Deconvolution of Mutational Signatures
If you receive this output, it indicates that the Musta CLI is correctly installed and ready for use. You can now proceed with using Musta for somatic mutation analysis in cancer research.
The Musta command structure is as follows:
musta COMMAND --workdir WORKING-DIR --samples-file SAMPLES-FILE [options]
Here’s an overview of these components:
detect: Somatic Mutations Detection.
classify: Variant Annotation.
interpret: Somatic Mutations Interpretation.
To remove Musta from your system, you can use the following command:
make clean
This command will clean up and remove any installed Musta components, ensuring that Musta is no longer present on your system.