Package: oligopipe
oligopipe - Python package for Oligogenic Variant Analysis pipelinesThis package offers a command-line interface to the Oligogenic Variant Analysis pipelines
developed at theInteruniveristy Institute of Bioinformatics in Brussels.It contains two modules:prediction with VarCoPP2.0, as discussed in the paper “Faster and more accurate pathogenic combination predictions with VarCoPP2.0":takes a patient's variants from VCF/TSV along with additional parameters and predicts the pathogenicity of all digenic variant combinations.prioritization with HOP-- under constructionRequirementsThe package requires Python 3.8-3.10 (currently higher versions are not supported yet).Additional requirements are specified in therequirements.txtfile and automatically satisfied when installing withpip.InstallationPIP-based installationThe easiest way to install is via thePyPI archivewith the commandpip install oligopipeIt is recommended to use a virtual environment for the management of dependencies.Source-based installationThe source code can be installed by cloning the repository or unpacking from a source code archive and runningpip install .in the source directory.For the purposes of testing or development, you may prefer to install as an editable module via PIP by runningpip install -e .in the source directory.UsageRunningoligopipewithout any arguments or with--helpreturns the overview of the CLI:$ oligopipe
usage: oligopipe [-h] {predict,prioritize,config} ...

CLI for oligopipe - oligogenic variant analysis pipelines

optional arguments:
  -h, --help            show this help message and exit

Commands:
  Run oligopipe {command} -h to get detailed help

  {predict,prioritize,config}
    predict             Run a VarCoPP prediction
    prioritize          Run a prioritization analysis with HOP -- under construction
    config              Show the template config fileThe individual pipelines are available as submodules of the CLI, and also have dedicated help pages.Both modules allow using a YAML config file for submitting input parameters and file paths,
as well as passing them as command-line arguments (which will be favored if both are given).
Running theoligopipe configmodule will print out a template for that config file.Running a predictionPlease refer tothe docsfor extensive documentation on the pipeline logic, the expected inputs and outputs.Check the available arguments:$ oligopipe predict --helpThe input arguments are grouped in categories:Variant input: VCF or TSV file and genome build (both required), patient's sexFiltering optionsOutput optionsDatabase credentials(required; see below)An example prediction run could then look like this (with database credentials in the config file):$ oligopipe predict --config path/to/input_config.yaml \
                    --variants-vcf path/to/example_vcf_2_hg19.vcf --genome-build hg19 --patient-sex F \
                    --panel path/to/example_vcf_2_gene_panel.txt \
                    --outdir resultsWhich will create the following result files:metadata.json: summary of the pipeline run (inputs, statistics)predictions_with_annotations.json: "raw" output of the predictions, containing also feature annotationspredicted_variant_combinations.tsv: table of variant combinations with their predictionspredicted_gene_pairs.tsv: table of gene pairs with prediction statisticsone file per type of variants that were discarded by the pipeline (if applicable):filtered_variants.txtmissing_variants.txt(missing from the annotation database)invalid_zygosity_variants.txtNote: if no variant combinations remain after the filtering, then the gene pair/variant combination files are not createdRunning a prioritizationNot available yetAnnotation databaseThe pipelines rely on an annotation database for quick retrieval of the variant, gene and gene pair input features for VarCoPP.We currently offer limited access to such a database for use in this package.
If you wish to get access, pleaseemail usso that we can provide you with the credentials.Additional documentationExtensive documentation (and a FAQ page) about the pipelines can be found inthe docs.CitationsPrediction with VarCoPP(2.0):Versbraegen N., Gravel B., Nachtegael C., Renaux A., Verkinderen E., Nowé A., Lenaerts T., Papadimitriou S.(2023) Faster and more accurate pathogenic combination predictions with VarCoPP2.0.BMC Bioinformatics. 24:179. DOI:https://doi.org/10.1186/s12859-023-05291-3Papadimitriou S., Gazzo A., Versbraegen N., Nachtegael C., Aerts J., Moreau Y., Van Dooren S., Nowé A., Smits G., Lenaerts T.(2019) Predicting disease-causing variant combinations.Proceedings of the National Academy of Sciences. 116(24):11878-11887. DOI:https://doi.org/10.1073/pnas.1815601116Prioritization with HOP:Currently in reviewSupportIf you are having issues, please let us know viaoligopipe@ibsquare.be.Known issuesIf you runoligopipeon a Macbook with M1 chip, you might get errors related to dependenciespsycopg2andpython-magic.
Try to resolve them by running:pip uninstall psycopg2and thenpip install psycopg2-binarypip install python-magic-binLicenseThe package is licensed under the MIT license.