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config files) must also be mounted in the docker container to be accessible.įor more help, look into the Docker documentation Docker bash alias Note that all files on the command line (eg. title "My amazing report" -b "This was made with docker"
You can also specify additional MultiQC parameters as normal: docker run -t -v `pwd`:`pwd` -w `pwd` ewels/multiqc. You can also specify specific versions, eg: ewels/multiqc:1.9. To use the most recent development code, use ewels/multiqc::dev. For MultiQC, this is set to be the most recent release. To use, call the docker run with your current working directory mounted as a volume and working directory: docker run -t -v `pwd`:`pwd` -w `pwd` ewels/multiqcīy default, docker will use the :latest tag. It's based on czentye/matplotlib-minimal to give the smallest size I could manage (~80MB). Using the Docker containerĪ Docker container is provided on Docker Hub called ewels/MultiQC. Note that support for using the base multiqc command was improved in MultiQC version 1.8. Run using GitHub Actions to check compatibility (see test config
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MultiQC is has primarily been designed for us on Unix systems (Linux, Mac OSX).
The n() function as follows: import multiqc You can import and run MultiQC from within a Python script, using The command line usage and flags are then exactly the same as if you ran just multiqc. If you prefer, you can also run MultiQC with a specific python interpreter. If you downloaded the flat files, just repeat the installation procedure. If you cloned the git repo, just pull the latest changes and install: cd MultiQC
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To update the development version, use: pip install -force git+ Updating MultiQCĪt any time by running the following command: pip install -upgrade multiqc Note that it is not recommended to use the command python setup.py installĪs this has been superseded by pip and does not correctly handle some package
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Git not installed? No problem - just download the flat files: curl -LOk
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If you'd rather not use either of these tools, you can clone the code and install the code yourself: git clone
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pip install -user multiqc Manual installation To use virtual environments, as described above). Your home directory with the -user parameter (though it's probably better Note that if you have problems with read-only directories, you can install to If you would like the development version, the command is: pip install git+ Otherwise you can find installation instructions here. It comes bundled with recent versions of Python, This is the easiest way to install MultiQC. Please see the Bioconda documentation for more details. If you're using conda as described above, you can install MultiQC from the biocondaĬhannel as follows: conda install -c bioconda -c conda-forge multiqc That the environment is loaded every time you load the terminal. You'll want to add the conda activate p圓.7 line to your. Once conda is installed, you can create a Python environment with the following commands: conda create -name p圓.7 python=3.7 You can installation instructions for Miniconda Our favourite is conda, a cross-platform tool to manage Python environments. We recommend using virtual environments to manage your Python installation. MultiQC needs Python version 2.7+, 3.4+ or 3.5+. To see if you have python installed, run python -version on the command line. Step back and think about Python virtual environments / conda instead (see below).
If you find yourself prepending sudo to any MultiQC commands, take a This often causes problems and it's a little risky to mess Installing MultiQC System Pythonīefore we start - a quick note that using the system-wide installation of Python It also saves a directory of dataįiles with all parsed data for further downstream use. Generates a single stand-alone HTML report file. It parses relevant information from these and When you launch MultiQC, it recursively searches through any provided file pathsĪnd finds files that it recognises. It's designed to be placed at the end of analysis pipelines or to be run manually MultiQC doesn't run other tools for you. MultiQC is a reporting tool that parses summary statistics from results and log files
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