joyling93/sc10x_wf
None
Overview
Topics:
Latest release: None, Last update: 2025-01-16
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Deployment
Step 1: Install Snakemake and Snakedeploy
Snakemake and Snakedeploy are best installed via the Mamba package manager (a drop-in replacement for conda). If you have neither Conda nor Mamba, it is recommended to install Miniforge. More details regarding Mamba can be found here.
When using Mamba, run
mamba create -c conda-forge -c bioconda --name snakemake snakemake snakedeploy
to install both Snakemake and Snakedeploy in an isolated environment. For all following commands ensure that this environment is activated via
conda activate snakemake
Step 2: Deploy workflow
With Snakemake and Snakedeploy installed, the workflow can be deployed as follows. First, create an appropriate project working directory on your system and enter it:
mkdir -p path/to/project-workdir
cd path/to/project-workdir
In all following steps, we will assume that you are inside of that directory. Then run
snakedeploy deploy-workflow https://github.com/joyling93/sc10x_wf . --tag None
Snakedeploy will create two folders, workflow
and config
. The former contains the deployment of the chosen workflow as a Snakemake module, the latter contains configuration files which will be modified in the next step in order to configure the workflow to your needs.
Step 3: Configure workflow
To configure the workflow, adapt config/config.yml
to your needs following the instructions below.
Step 4: Run workflow
The deployment method is controlled using the --software-deployment-method
(short --sdm
) argument.
To run the workflow with automatic deployment of all required software via conda
/mamba
, use
snakemake --cores all --sdm conda
Snakemake will automatically detect the main Snakefile
in the workflow
subfolder and execute the workflow module that has been defined by the deployment in step 2.
For further options such as cluster and cloud execution, see the docs.
Step 5: Generate report
After finalizing your data analysis, you can automatically generate an interactive visual HTML report for inspection of results together with parameters and code inside of the browser using
snakemake --report report.zip
Configuration
The following section is imported from the workflow’s config/README.md
.
目前流程仅支持转录组、空间转录组和gex+vdj测序,后续会逐步增加其他类型的数据流程。 物种仅支持homo_sapiens和mus_musculus,后续会逐步增加其他物种。
Linting and formatting
Linting results
The flag 'directory' used in rule rmd_report is only valid for outputs, not inputs.
Lints for rule get_cellranger (line 3, /tmp/tmpfqq0ttr2/workflow/rules/resources.smk):
* Specify a conda environment or container for each rule.:
This way, the used software for each specific step is documented, and the
workflow can be executed on any machine without prerequisites.
Also see:
https://snakemake.readthedocs.io/en/latest/snakefiles/deployment.html#integrated-package-management
https://snakemake.readthedocs.io/en/latest/snakefiles/deployment.html#running-jobs-in-containers
Lints for rule get_reference (line 16, /tmp/tmpfqq0ttr2/workflow/rules/resources.smk):
* Specify a conda environment or container for each rule.:
This way, the used software for each specific step is documented, and the
workflow can be executed on any machine without prerequisites.
Also see:
https://snakemake.readthedocs.io/en/latest/snakefiles/deployment.html#integrated-package-management
https://snakemake.readthedocs.io/en/latest/snakefiles/deployment.html#running-jobs-in-containers
Lints for rule clean_names (line 30, /tmp/tmpfqq0ttr2/workflow/rules/resources.smk):
* Specify a conda environment or container for each rule.:
This way, the used software for each specific step is documented, and the
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Formatting results
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[DEBUG] In file "/tmp/tmpfqq0ttr2/workflow/rules/report.smk": Formatted content is different from original
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[DEBUG] In file "/tmp/tmpfqq0ttr2/workflow/rules/qc_reads.smk": Formatted content is different from original
[DEBUG]
[WARNING] In file "/tmp/tmpfqq0ttr2/workflow/Snakefile": Keyword "input" at line 49 has comments under a value.
PEP8 recommends block comments appear before what they describe
(see https://www.python.org/dev/peps/pep-0008/#id30)
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