vojdam/idat_to_graph

A Snakemake workflow for creating graph visualizations of DNA methylation data.

Overview

Latest release: None, Last update: 2026-03-09

Share link: https://snakemake.github.io/snakemake-workflow-catalog?wf=vojdam/idat_to_graph

Quality control: linting: passed formatting: passed

Topics: idat illumina methylation methylation-analysis

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/vojdam/idat_to_graph . --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.

Workflow overview

This workflow is used to create clustering tSNE and UMAP graphs from IDAT files obtained using sequencing on Illumina chips. The workflow is built using snakemake and consists of the following steps:

Convert the IDAT files to corresponding CSVs of beta values
Construct the tSNE graph
Construct the UMAP graph

Running the workflow

Input data

This workflow uses IDAT file pairs (_Grn and _Red); the file extensions should be either .idat.gz or .idat. The sample sheet has the following layout:

sample_id	diagnosis	idat_prefix
REFERENCE_SAMPLE 1	Control (muscle tissue)	201904410008_R06C01
REFERENCE_SAMPLE 2	Control (muscle tissue)	201904410008_R05C01

Parameters

This table lists all parameters that can be used to run the workflow.

parameter	type	details	default
sample_sheet
path	str	path to sample sheet, mandatory	“.test/config/sample_sheet.csv”
sample_folder
path	str	path to sample containing folder mandatory	“.test/config/samples/”

Linting and formatting

Linting results

All tests passed!

Formatting results

All tests passed!