TRON-Bioinformatics/oblx
Reproducible generation of references and resources for next generation sequencing pipelines.
Overview
Latest release: v1.0.0, Last update: 2026-06-18
Share link: https://snakemake.github.io/snakemake-workflow-catalog?wf=TRON-Bioinformatics/oblx
Quality control: linting: failed formatting: passed
Topics: ngs-analysis reproducible-research snakemake-workflow snakemake oblx workflow
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/TRON-Bioinformatics/oblx . --tag v1.0.0
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.
Configuration
See the config section in our online docs.
Workflow parameters
The following table is automatically parsed from the workflow’s config.schema.y(a)ml file.
Parameter |
Type |
Description |
Required |
Default |
|---|---|---|---|---|
organism |
string |
Trivial name of the organism for which the genomelib should be built. |
human |
|
genome_build |
string |
GRC reference genome build for which the genomelib should be built. |
GRCh38 |
|
release |
string |
Release number of the GENCODE annotation for the corresponding reference genome_build. |
49 |
|
gnomad_release |
string |
Release number of the gnomAD resources to be used. |
4.1 |
|
intron_slop |
integer |
Number of intronic bases that should extend the exome definition |
20 |
|
exome_transcript_definition |
string |
Define which GENCODE transcripts should be used to create the exome definition. The default is the |
basic |
|
star_sjdb_overhang |
integer |
|
100 |
|
star_genome_sa_index_n_bases |
integer |
Defines the STAR parameter |
14 |
|
minimum_allele_frequency |
number |
|
0.001 |
|
gencode_url |
string |
URL from which GENCODE resources can be downloaded. Expected to point to the root of a FTP directory (accessed via HTTPS) under which the general GENCODE dir structure can be found, i.e., |
https://ftp.ebi.ac.uk/pub/databases/gencode |
|
ucsc_url |
string |
URL from which UCSC resources can be downloaded. Expected to point to the root of a directory (accessed via HTTPS) under which the UCSC “problematic”, “exomeProbesets”, and “gencode” bigBed resource files may be found. Only needed when organism is “human”. |
https://hgdownload.soe.ucsc.edu/gbdb/hg38 |
|
ucsc_golden_path_url |
string |
URL from which the UCSC golden path resources (i.e. the repeatmasking resource file) can be downloaded for a given assembly. Only needed when organism is “human”. |
https://hgdownload.soe.ucsc.edu/goldenPath |
|
gatk_url |
string |
URL from which the GATK resources may be downloaded. Only needed when organism is “human”. |
https://storage.googleapis.com/gcp-public-data–broad-references/hg38/v0 |
|
gnomad_url |
string |
URL from which the gnomAD population SNP VCF files may be downloaded. Only needed when organism is “human”. |
https://storage.googleapis.com/gcp-public-data–gnomad/release |
|
chrom_filter |
array |
List of chromosome names to be included in the genomelib. Only needed when organism is “human” as this currently only defines which chromosomes are downloaded from gnomAD (chrM is not included at the moment as this would require to download from gnomAD v3.1). |
[‘chr1’, ‘chr2’, ‘chr3’, ‘chr4’, ‘chr5’, ‘chr6’, ‘chr7’, ‘chr8’, ‘chr9’, ‘chr10’, ‘chr11’, ‘chr12’, ‘chr13’, ‘chr14’, ‘chr15’, ‘chr16’, ‘chr17’, ‘chr18’, ‘chr19’, ‘chr20’, ‘chr21’, ‘chr22’, ‘chrX’, ‘chrY’] |
Linting and formatting
Linting results
1Using workflow specific profile workflow/profiles/default for setting default command line arguments.
2WorkflowError in file "/tmp/tmpwt6gxj5n/TRON-Bioinformatics-oblx-2651959/workflow/Snakefile", line 14:
3Expecting Snakemake version 9.20.0 or higher (you are currently using 9.17.2).
Formatting results
All tests passed!