ausswal/PromEvo

PromEvo is a pipeline to analyze core, proximal promoter elements, nucleotide composition, CpG islands, DNA structural properties, Non B-DNA motifs

Overview

Latest release: v0.1.7, Last update: 2026-10-22

Share link: https://snakemake.github.io/snakemake-workflow-catalog?wf=ausswal/PromEvo

Quality control: linting: passed formatting: passed

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/ausswal/PromEvo . --tag v0.1.7

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.

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.

Configuration

config/config.yaml has two parts.

Key	Meaning
scripts_dir	Folder with the PromEvo stage scripts. A relative path is taken from the repository root (default scripts). Override on the command line with --config scripts_dir=/absolute/path.
stages	The 17 stages in order. Each entry has id, script, after (what must finish first; databases is the motif database setup), and optionally guard: protein (skipped automatically when Stage 01 found no real protein data) and threads.

Stage 01 is interactive: it asks for the data-retrieval mode and inputs, then writes outputs/.pipeline_data_manifest.json. Every later stage requires that file.

Finished steps are recorded as marker files in outputs/.done/. Delete outputs/.done/1.done and outputs/.done/{2..17}.done to redo Stage 01 and everything after it.

Linting and formatting

Linting results

All tests passed!

Formatting results

All tests passed!