matinnuhamunada/interproscan_helper
A snakemake pipeline to run interproscan locally
Overview
Topics:
Latest release: None, Last update: 2023-01-20
Linting: linting: failed, Formatting: formatting: failed
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/matinnuhamunada/interproscan_helper . --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
.
Describe how to configure the workflow (using config.yaml and maybe additional files). All of them need to be present with example entries inside of the config folder.
Linting and formatting
Linting results
1Lints for snakefile /tmp/tmpcp1u4j4f/workflow/Snakefile:
2 * Absolute path "/home/matinnu/datadrive/glyco_halo_mining/output/interproscan_per_region/{sample}.faa.tsv" in line 21:
3 Do not define absolute paths inside of the workflow, since this renders
4 your workflow irreproducible on other machines. Use path relative to the
5 working directory instead, or make the path configurable via a config
6 file.
7 Also see:
8 https://snakemake.readthedocs.io/en/latest/snakefiles/configuration.html#configuration
9 * Absolute path "/home/matinnu/datadrive/glyco_halo_mining/output/interproscan_per_region/{sample}.faa.json" in line 22:
10 Do not define absolute paths inside of the workflow, since this renders
11 your workflow irreproducible on other machines. Use path relative to the
12 working directory instead, or make the path configurable via a config
13 file.
14 Also see:
15 https://snakemake.readthedocs.io/en/latest/snakefiles/configuration.html#configuration
16
17Lints for snakefile /tmp/tmpcp1u4j4f/workflow/rules/interproscan.smk:
18 * Absolute path "/home/matinnu/datadrive/glyco_halo_mining/output/interproscan_per_region/{sample}.faa.tsv" in line 5:
19 Do not define absolute paths inside of the workflow, since this renders
20 your workflow irreproducible on other machines. Use path relative to the
21 working directory instead, or make the path configurable via a config
22 file.
23 Also see:
24 https://snakemake.readthedocs.io/en/latest/snakefiles/configuration.html#configuration
25 * Absolute path "/home/matinnu/datadrive/glyco_halo_mining/output/interproscan_per_region/{sample}.faa.json" in line 6:
26 Do not define absolute paths inside of the workflow, since this renders
27 your workflow irreproducible on other machines. Use path relative to the
28 working directory instead, or make the path configurable via a config
29 file.
30 Also see:
31 https://snakemake.readthedocs.io/en/latest/snakefiles/configuration.html#configuration
32
33Lints for rule interproscan (line 1, /tmp/tmpcp1u4j4f/workflow/rules/interproscan.smk):
34 * Specify a conda environment or container for each rule.:
35 This way, the used software for each specific step is documented, and the
36 workflow can be executed on any machine without prerequisites.
37 Also see:
38 https://snakemake.readthedocs.io/en/latest/snakefiles/deployment.html#integrated-package-management
39 https://snakemake.readthedocs.io/en/latest/snakefiles/deployment.html#running-jobs-in-containers
Formatting results
1[DEBUG]
2[DEBUG] In file "/tmp/tmpcp1u4j4f/workflow/Snakefile": Formatted content is different from original
3[DEBUG]
4[DEBUG] In file "/tmp/tmpcp1u4j4f/workflow/rules/interproscan.smk": Formatted content is different from original
5[INFO] 2 file(s) would be changed 😬
6
7snakefmt version: 0.8.0