vepyr (/ˈvaɪpər/) — VEP Yielding Performant Results — is a blazing-fast Rust
reimplementation of Ensembl's Variant Effect
Predictor, exposed as a
Python library and a vepyr command. It builds and uses Ensembl VEP caches
locally, annotates VCF input through a native DataFusion engine, and returns
results as a polars.LazyFrame or a VCF with CSQ in the INFO column.
https://biodatageeks.org/vepyr/
| Quick start | Install, get a cache, annotate |
| Polars DataFrames | Schema, region filters, filter_vep in Polars |
| Command line | vepyr annotate, VCF in, VCF out |
| Nextflow | The vepyr/annotate module, amd64 and arm64 containers |
| Download Ensembl VEP and plugin caches | Prebuilt release-116 caches |
| Caches | Cache types, entity schemas, CSQ output fields |
| Plugins | CADD, SpliceAI, AlphaMissense, ClinVar, dbNSFP, PhenotypeOrthologous |
| API reference | build_cache(), annotate(), … |
| Performance | Benchmarks vs Ensembl VEP |
pip install vepyror from bioconda (linux-64, osx-64, osx-arm64):
conda install -c conda-forge -c bioconda vepyrEither installs both the Python package and a vepyr executable:
vepyr annotate \
-i input.vcf.gz \
-o annotated.vcf.gz \
--dir_cache ~/vepyr_cache/116_GRCh38_ensembl \
--fasta GRCh38.fa \
--everything \
--fork 8See Developers for building from source and running the test suite.