cellsnake
Project description
cellsnake
A command line tool for easy and scalable single cell analysis
Installation
Method for installing directly from the GitHub repo:
git clone https://github.com/sinanugur/cellsnake.git
cd cellsnake
pip install .
Check if the installation works by calling the main script:
cellsnake --help
then install and check if all the R packages are installed by typing:
cellsnake --install-packages
You should see this message if all the packages are available:
[1] "All packages were installed...OK"
Note: You have to install dependencies if you prefer Github installation. We strongly recommend Bioconda and Mamba.
--install-packages
argument must be always called to check if the R packages are available and installed correctly.
Quick start examples
Run cellsnake
in a clean directory and cellsnake
will create the required directories while running. You may download publicly available fetal brain dataset to test your cellsnake
installation. The link is here.
After downloading the dataset, just point the data folder which contains the two dataset folders, this will trigger a standard cellsnake workflow:
cellsnake data
After the pipeline finishes, you may also integrate these two samples:
cellsnake data --option integration
To determine a manual resolution parameter, you can also create only a ClusTree:
cellsnake data --option integration --option clustree
Let's say you want a resolution of 0.1, then you can trigger a run with this resolution:
cellsnake data --option integration --resolution 0.1
It is also possible to use automatic resolution selection, however this might be very slow in large datasets:
cellsnake data --option integration --resolution auto
See our documentation for detailed explanations and to read full features: https://cellsnake.readthedocs.io/
Options and Arguments
Usage:
cellsnake <INPUT> [--resolution <text>] [--percent_mt <text>] [--configfile <text>] [--gene <text>] [--jobs <integer>] [--option <text>]... [--release-the-kraken <text>] [--taxa <text>] [--unlock|--remove] [--dry]
cellsnake <INPUT> [--unlock|--remove] [--dry]
cellsnake --generate-template
cellsnake --install-packages
cellsnake (-h | --help)
cellsnake --version
cellsnake --init
Arguments:
INPUT Input directory or a file to process (if a directory given, batch mode is ON).
-c <text>, --configfile <text> Config file name (if not supplied, it will use default settings, you may generate a template, change it and use it in your runs).
--resolution <text> Resolution for cluster detection, write "auto" for auto detection [default: 0.8].
--percent_mt <text> Maximum mitochondrial gene percentage cutoff, for example, 5 or 10, write "auto" for auto detection [default: 10].
--gene <text> Create publication ready plots for a gene or a list of genes from a text file.
--option <text> cellsnake run options: "minimal", "standard", "clustree", "advanced" [default: standard]. "integration" is to integrate and run on integrated samples.
--release-the-kraken <text> Kraken database folder.
--taxa <text> Microbiome taxonomic level collapse to "domain", "kingdom", "phylum", "class", "order", "family", "genus", "species" [default: genus]
-j <integer>, --jobs <integer> Total CPUs. [default: 2]
Options:
--generate-template Generate config file template in the current directory.
--install-packages Install, reinstall or check required R packages.
-u, --unlock Rescue stalled jobs (Try this if the previous job ended prematurely or currently failing).
-r, --remove Delete all output files (this won't affect input files).
-d, --dry Dry run, nothing will be generated.
-h, --help Show this screen.
--version Show version.
Output
The cellsnake
main executable will generate two main folders: analyses and results.
If an integrated dataset available, analyses_integrated and results_integrated.
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