Documentation: https://tron-bioinformatics.github.io/oblx
If you use OBLX, please cite the following publication:
Kress, L., Hausmann, J., Freimuth, J., Schrörs, B., Lang, F., & Ibn-Salem, J. (2026). OBLX: Building standardized reference resources for reproducible bioinformatics data analysis. Frontiers in Bioinformatics, 6, 1910035. https://doi.org/10.3389/fbinf.2026.1910035
OBLX (/ˌɒbl.ˈɛks/) is a pipeline which downloads reference genomes, genome annotations and further resources, and generates from these the indexes required for various bioinformatics tools and pipelines. The pipeline consists of two independently executable stages: Download Resources and Build Indices. Download Resources retrieves the reference genome, genome annotation and other resources and prepares the data for bioinformatics index generation. The reference genome and genome annotation are downloaded from GENCODE; the preferred genome assembly version, GENCODE release and organism can be specified via the config file. Additional resources from GATK, UCSC and gnomAD are retrieved (see Download Resources for details). Build Indices then generates tool-specific indices. The resulting genome library is consistent with respect to chromosome, transcript and gene naming and supports an extensive set of bioinformatics tools, all listed in Supported Tools. OBLX is implemented as a Snakemake pipeline (Mölder et al., 2021).
Pre-built OBLX libraries for human and mouse are available for download via ftp://easyfuse.tron-mainz.de/oblx.
For each OBLX version that leads to changes in the human or mouse library, an OBLX library is generated. Currently, these versions are available:
| OBLX_VERSION | BUILD_RELEASE human | BUILD_RELEASE mouse |
|---|---|---|
| v2.1.0 | GRCh38_50 | GRCm39_M38 |
| v2.0.0 | GRCh38_49 | GRCm39_M38 |
| v1.0.0 | GRCh38_49 | GRCm39_M38 |
Specify your preferred OBLX library e.g.:
OBLX_VERSION="v1.0.0"
OBLX_ORGANISM="human"
BUILD_RELEASE="GRCh38_49"Download the respective OBLX library (this downloads the respective files contained in the library, no tar.gz):
wget --recursive --no-host-directories "ftp://easyfuse.tron-mainz.de/oblx/${OBLX_VERSION}/${OBLX_ORGANISM}/${BUILD_RELEASE}"To verify the files run the following commands (to setup gpg key see https://github.com/TRON-Bioinformatics/security). If any of the checks fail, please refer to this repository. If the error is not documented, feel free to open an issue.
cd "oblx/${OBLX_VERSION}/${OBLX_ORGANISM}"
# download the respective checksum
wget "ftp://easyfuse.tron-mainz.de/oblx/${OBLX_VERSION}/${OBLX_ORGANISM}/${BUILD_RELEASE}.checksum.txt.sig"
# extract the checksum file
gpg --output ${BUILD_RELEASE}.checksum.txt --decrypt ${BUILD_RELEASE}.checksum.txt.sig
# check the downloaded assets
sha256sum -c ${BUILD_RELEASE}.checksum.txtTo run OBLX, adapt and execute the following command:
snakemake -s workflow/Snakefile \
--directory </path/to/output/directory> \
--latency-wait 60 \
--software-deployment-method [conda|apptainer] \
[--configfile <path/to/config/file>] \
[--profile </path/to/cluster/profile/>]
OBLX does not require any user-provided input. You only specify the output directory and, if non-default settings are desired, adapt the configuration.
The output of the pipeline is written to the directory specified with
--directory. Descriptions of the downloaded genome resources are documented in
Download Resources;
descriptions of the generated indices are documented in
Build Indices.
We welcome contributions! Please see CONTRIBUTING.md and developer_guide for guidelines.
OBLX was originally developed by Luis Kress and Johannes Hausmann at TRON - Translational Oncology at the Medical Center of the Johannes Gutenberg University Mainz gGmbH (non-profit).
🛠️ Main developers:
✨ Contributors and code reviewers:
- Mölder, F., Jablonski, K. P., Letcher, B., Hall, M. B., Van Dyken, P. C., Tomkins-Tinch, C. H., Sochat, V., Forster, J., Vieira, F. G., Meesters, C., Lee, S., Twardziok, S. O., Kanitz, A., VanCampen, J., Malladi, V., Wilm, A., Holtgrewe, M., Rahmann, S., Nahnsen, S., & Köster, J. (2025). Sustainable data analysis with Snakemake. F1000Research, 10, 33. https://doi.org/10.12688/f1000research.29032.3
- Figure generated with BioRender icons.