Kratzcomycete/Fungal-Genome-Processing-Snakemake

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Overview

Latest release: None, Last update: 2025-04-11

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/Kratzcomycete/Fungal-Genome-Processing-Snakemake . --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/tmp1ngazpkd/workflow/Snakefile:
 2    * Mixed rules and functions in same snakefile.:
 3      Small one-liner functions used only once should be defined as lambda
 4      expressions. Other functions should be collected in a common module, e.g.
 5      'rules/common.smk'. This makes the workflow steps more readable.
 6      Also see:
 7      https://snakemake.readthedocs.io/en/latest/snakefiles/modularization.html#includes
 8
 9Lints for rule fastqc (line 35, /tmp/tmp1ngazpkd/workflow/Snakefile):
10    * Param dir is a prefix of input or output file but hardcoded:
11      If this is meant to represent a file path prefix, it will fail when
12      running workflow in environments without a shared filesystem. Instead,
13      provide a function that infers the appropriate prefix from the input or
14      output file, e.g.: lambda w, input: os.path.splitext(input[0])[0]
15      Also see:
16      https://snakemake.readthedocs.io/en/stable/snakefiles/rules.html#non-file-parameters-for-rules
17      https://snakemake.readthedocs.io/en/stable/tutorial/advanced.html#tutorial-input-functions
18
19Lints for rule fastp (line 90, /tmp/tmp1ngazpkd/workflow/Snakefile):
20    * Param dir is a prefix of input or output file but hardcoded:
21      If this is meant to represent a file path prefix, it will fail when
22      running workflow in environments without a shared filesystem. Instead,
23      provide a function that infers the appropriate prefix from the input or
24      output file, e.g.: lambda w, input: os.path.splitext(input[0])[0]
25      Also see:
26      https://snakemake.readthedocs.io/en/stable/snakefiles/rules.html#non-file-parameters-for-rules
27      https://snakemake.readthedocs.io/en/stable/tutorial/advanced.html#tutorial-input-functions
28
29Lints for rule spades (line 125, /tmp/tmp1ngazpkd/workflow/Snakefile):
30    * Param outdir is a prefix of input or output file but hardcoded:
31      If this is meant to represent a file path prefix, it will fail when
32      running workflow in environments without a shared filesystem. Instead,
33      provide a function that infers the appropriate prefix from the input or
34      output file, e.g.: lambda w, input: os.path.splitext(input[0])[0]
35      Also see:
36      https://snakemake.readthedocs.io/en/stable/snakefiles/rules.html#non-file-parameters-for-rules
37      https://snakemake.readthedocs.io/en/stable/tutorial/advanced.html#tutorial-input-functions
38
39Lints for rule bowtie2_mapping (line 169, /tmp/tmp1ngazpkd/workflow/Snakefile):
40    * Param outdir is a prefix of input or output file but hardcoded:
41      If this is meant to represent a file path prefix, it will fail when
42      running workflow in environments without a shared filesystem. Instead,
43      provide a function that infers the appropriate prefix from the input or
44      output file, e.g.: lambda w, input: os.path.splitext(input[0])[0]
45      Also see:
46      https://snakemake.readthedocs.io/en/stable/snakefiles/rules.html#non-file-parameters-for-rules
47      https://snakemake.readthedocs.io/en/stable/tutorial/advanced.html#tutorial-input-functions

Formatting results

1[DEBUG] 
2[DEBUG] In file "/tmp/tmp1ngazpkd/workflow/Snakefile":  Formatted content is different from original
3[INFO] 1 file(s) would be changed 😬
4
5snakefmt version: 0.10.2