mdondrup/divergence_time
None
Overview
Latest release: None, Last update: 2025-05-31
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/mdondrup/divergence_time . --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/tmpc66vlp8m/workflow/Snakefile:
2 * Absolute path "/|" in line 129:
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 * Path composition with '+' in line 24:
10 This becomes quickly unreadable. Usually, it is better to endure some
11 redundancy against having a more readable workflow. Hence, just repeat
12 common prefixes. If path composition is unavoidable, use pathlib or
13 (python >= 3.6) string formatting with f"...".
14 * Path composition with '+' in line 8:
15 This becomes quickly unreadable. Usually, it is better to endure some
16 redundancy against having a more readable workflow. Hence, just repeat
17 common prefixes. If path composition is unavoidable, use pathlib or
18 (python >= 3.6) string formatting with f"...".
19 * Path composition with '+' in line 24:
20 This becomes quickly unreadable. Usually, it is better to endure some
21 redundancy against having a more readable workflow. Hence, just repeat
22 common prefixes. If path composition is unavoidable, use pathlib or
23 (python >= 3.6) string formatting with f"...".
24
25Lints for rule degenotate (line 45, /tmp/tmpc66vlp8m/workflow/Snakefile):
26 * No log directive defined:
27 Without a log directive, all output will be printed to the terminal. In
28 distributed environments, this means that errors are harder to discover.
29 In local environments, output of concurrent jobs will be mixed and become
30 unreadable.
31 Also see:
32 https://snakemake.readthedocs.io/en/stable/snakefiles/rules.html#log-files
33
34Lints for rule rename_chromosomes (line 60, /tmp/tmpc66vlp8m/workflow/Snakefile):
35 * No log directive defined:
36 Without a log directive, all output will be printed to the terminal. In
37 distributed environments, this means that errors are harder to discover.
38 In local environments, output of concurrent jobs will be mixed and become
39 unreadable.
40 Also see:
41 https://snakemake.readthedocs.io/en/stable/snakefiles/rules.html#log-files
42 * Shell command directly uses variable rule from outside of the rule:
43 It is recommended to pass all files as input and output, and non-file
44 parameters via the params directive. Otherwise, provenance tracking is
45 less accurate.
46 Also see:
47 https://snakemake.readthedocs.io/en/stable/snakefiles/rules.html#non-file-parameters-for-rules
48
49Lints for rule index_vcf (line 79, /tmp/tmpc66vlp8m/workflow/Snakefile):
50 * No log directive defined:
51 Without a log directive, all output will be printed to the terminal. In
52 distributed environments, this means that errors are harder to discover.
53 In local environments, output of concurrent jobs will be mixed and become
54 unreadable.
55 Also see:
56 https://snakemake.readthedocs.io/en/stable/snakefiles/rules.html#log-files
57
58Lints for rule filter_vcf (line 93, /tmp/tmpc66vlp8m/workflow/Snakefile):
59 * No log directive defined:
60 Without a log directive, all output will be printed to the terminal. In
61 distributed environments, this means that errors are harder to discover.
62 In local environments, output of concurrent jobs will be mixed and become
63 unreadable.
64 Also see:
65 https://snakemake.readthedocs.io/en/stable/snakefiles/rules.html#log-files
66
67Lints for rule make_genotype_matrix (line 116, /tmp/tmpc66vlp8m/workflow/Snakefile):
68 * No log directive defined:
69 Without a log directive, all output will be printed to the terminal. In
70 distributed environments, this means that errors are harder to discover.
71 In local environments, output of concurrent jobs will be mixed and become
72 unreadable.
73 Also see:
74 https://snakemake.readthedocs.io/en/stable/snakefiles/rules.html#log-files
75
76Lints for rule difference_matrix (line 134, /tmp/tmpc66vlp8m/workflow/Snakefile):
77 * Shell command directly uses variable rule from outside of the rule:
78 It is recommended to pass all files as input and output, and non-file
79 parameters via the params directive. Otherwise, provenance tracking is
80 less accurate.
81 Also see:
82 https://snakemake.readthedocs.io/en/stable/snakefiles/rules.html#non-file-parameters-for-rules
83 * Shell command directly uses variable rule from outside of the rule:
84 It is recommended to pass all files as input and output, and non-file
85 parameters via the params directive. Otherwise, provenance tracking is
86 less accurate.
87 Also see:
88 https://snakemake.readthedocs.io/en/stable/snakefiles/rules.html#non-file-parameters-for-rules
89 * Shell command directly uses variable rule from outside of the rule:
90 It is recommended to pass all files as input and output, and non-file
91 parameters via the params directive. Otherwise, provenance tracking is
92 less accurate.
93 Also see:
94 https://snakemake.readthedocs.io/en/stable/snakefiles/rules.html#non-file-parameters-for-rules
Formatting results
1[DEBUG]
2[DEBUG] In file "/tmp/tmpc66vlp8m/workflow/Snakefile": Formatted content is different from original
3[INFO] 1 file(s) would be changed 😬
4
5snakefmt version: 0.11.0