tmweiskittel/tmw_analysis_emseq

None

Overview

Latest release: None, Last update: 2026-06-15

Share link: https://snakemake.github.io/snakemake-workflow-catalog?wf=tmweiskittel/tmw_analysis_emseq

Quality control: linting: failed formatting: failed

Wrappers: bio/fastqc bio/multiqc

Deployment

Step 1: Install Snakemake and Snakedeploy

Snakemake and Snakedeploy are best installed via the Conda package manager. It is recommended to install conda via Miniforge. Run

conda create -c conda-forge -c bioconda -c nodefaults --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

For other installation methods, refer to the Snakemake and Snakedeploy documentation.

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/tmweiskittel/tmw_analysis_emseq . --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 using apptainer/singularity, use

snakemake --cores all --sdm apptainer

To run the workflow using a combination of conda and apptainer/singularity for software deployment, use

snakemake --cores all --sdm conda apptainer

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.

Workflow overview

This workflow is a best-practice workflow for <detailed description>. The workflow is built using snakemake and consists of the following steps:

  1. Download genome reference from NCBI

  2. Validate downloaded genome (python script)

  3. Simulate short read sequencing data on the fly (dwgsim)

  4. Check quality of input read data (FastQC)

  5. Collect statistics from tool output (MultiQC)

Running the workflow

Input data

This template workflow creates artificial sequencing data in *.fastq.gz format. It does not contain actual input data. The simulated input files are nevertheless created based on a mandatory table linked in the config.yaml file (default: .test/samples.tsv). The sample sheet has the following layout:

sample

condition

replicate

read1

read2

sample1

wild_type

1

sample1.bwa.read1.fastq.gz

sample1.bwa.read2.fastq.gz

sample2

wild_type

2

sample2.bwa.read1.fastq.gz

sample2.bwa.read2.fastq.gz

Workflow parameters

The following table is automatically parsed from the workflow’s config.schema.y(a)ml file.

Parameter

Type

Description

Required

Default

sample_sheet

string

path to sample sheet, mandatory

yes

config/samples.tsv

get_genome

yes

. ncbi_ftp

string

URL for genome retrieval from NCBI FTP server

yes

simulate_reads

yes

. read_length

integer

length of target reads in bp

yes

100

. read_number

integer

number of total reads to be simulated

yes

10000

Linting and formatting

Linting results
 1Lints for snakefile /tmp/tmp1rgl_w81/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 download_methylkit_raw (line 1, /tmp/tmp1rgl_w81/workflow/rules/download_differential_methylation.smk):
10    * Specify a conda environment or container for each rule.:
11      This way, the used software for each specific step is documented, and the
12      workflow can be executed on any machine without prerequisites.
13      Also see:
14      https://snakemake.readthedocs.io/en/latest/snakefiles/deployment.html#integrated-package-management
15      https://snakemake.readthedocs.io/en/latest/snakefiles/deployment.html#running-jobs-in-containers
16
17Lints for rule make_single_methylkit_tabix_db (line 23, /tmp/tmp1rgl_w81/workflow/rules/download_differential_methylation.smk):
18    * Param out_dir is a prefix of input or output file but hardcoded:
19      If this is meant to represent a file path prefix, it will fail when
20      running workflow in environments without a shared filesystem. Instead,
21      provide a function that infers the appropriate prefix from the input or
22      output file, e.g.: lambda w, input: os.path.splitext(input[0])[0]
23      Also see:
24      https://snakemake.readthedocs.io/en/stable/snakefiles/rules.html#non-file-parameters-for-rules
25      https://snakemake.readthedocs.io/en/stable/tutorial/advanced.html#tutorial-input-functions
26
27Lints for rule download_gencode_gtf (line 1, /tmp/tmp1rgl_w81/workflow/rules/setup_differential_methylation.smk):
28    * No log directive defined:
29      Without a log directive, all output will be printed to the terminal. In
30      distributed environments, this means that errors are harder to discover.
31      In local environments, output of concurrent jobs will be mixed and become
32      unreadable.
33      Also see:
34      https://snakemake.readthedocs.io/en/stable/snakefiles/rules.html#log-files
35    * Specify a conda environment or container for each rule.:
36      This way, the used software for each specific step is documented, and the
37      workflow can be executed on any machine without prerequisites.
38      Also see:
39      https://snakemake.readthedocs.io/en/latest/snakefiles/deployment.html#integrated-package-management
40      https://snakemake.readthedocs.io/en/latest/snakefiles/deployment.html#running-jobs-in-containers
41
42Lints for rule upload_differential_methylation_results (line 1, /tmp/tmp1rgl_w81/workflow/rules/cloud_upload.smk):
43    * Specify a conda environment or container for each rule.:
44      This way, the used software for each specific step is documented, and the
45      workflow can be executed on any machine without prerequisites.
46      Also see:
47      https://snakemake.readthedocs.io/en/latest/snakefiles/deployment.html#integrated-package-management
48      https://snakemake.readthedocs.io/en/latest/snakefiles/deployment.html#running-jobs-in-containers
Formatting results
 1[DEBUG] 
 2[DEBUG] 
 3[DEBUG] In file "/tmp/tmp1rgl_w81/workflow/Snakefile":  Formatted content is different from original
 4[DEBUG] 
 5[DEBUG] In file "/tmp/tmp1rgl_w81/workflow/rules/cloud_upload.smk":  Formatted content is different from original
 6[DEBUG] 
 7[DEBUG] 
 8[DEBUG] In file "/tmp/tmp1rgl_w81/workflow/rules/download_differential_methylation.smk":  Formatted content is different from original
 9[DEBUG] 
10[DEBUG] In file "/tmp/tmp1rgl_w81/workflow/rules/differential_methylation.smk":  Formatted content is different from original
11[DEBUG] 
12[DEBUG] In file "/tmp/tmp1rgl_w81/workflow/rules/setup_differential_methylation.smk":  Formatted content is different from original
13[INFO] 5 file(s) would be changed 😬
14[INFO] 2 file(s) would be left unchanged 🎉
15
16snakefmt version: 0.11.5