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The ProteoGenomics database generation workflow creates different protein databases for ProteoGenomics data analysis.

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nf-core/pgdb

The ProteoGenomics database generation workflow (pgdb) use the pypgatk and nextflow to create different protein databases for ProteoGenomics data analysis.

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install with bioconda Docker Get help on Slack

Introduction

nf-core/pgdb is a bioinformatics pipeline to generate proteogenomics databases. pgdb allows users to create proteogenomics databases using EMSEMBL as the reference proteome database. Three different major databases can be attached to the final proteogenomics database:

  • The reference proteome (ENSEMBL Reference proteome)
  • Non canonical proteins: pseudo-genes, sORFs, lncRNA.
  • Variants: COSMIC, cBioPortal, GENOMAD variants

The pipeline allows to estimate decoy proteins with different methods and attach them to the final proteogenomics database.

The pipeline is built using Nextflow, a workflow tool to run tasks across multiple compute infrastructures in a very portable manner. It comes with docker containers making installation trivial and results highly reproducible.

Quick Start

  1. Install nextflow

  2. Install any of Docker, Singularity, Podman, Shifter or Charliecloud for full pipeline reproducibility (please only use Conda as a last resort; see docs)

  3. Download the pipeline and test it on a minimal dataset with a single command (This run will download the canonical ENSEMBL reference proteome and create proteomics database with it):

    nextflow run nf-core/pgdb -profile test,<docker/singularity/podman/shifter/charliecloud/conda/institute>

    Please check nf-core/configs to see if a custom config file to run nf-core pipelines already exists for your Institute. If so, you can simply use -profile <institute> in your command. This will enable either docker or singularity and set the appropriate execution settings for your local compute environment.

  4. Start running your own analysis!

    nextflow run nf-core/pgdb -profile <docker/singularity/podman/conda/institute> --ncrna true --pseudogenes true --altorfs true

    This will create a proteogenomics database with the ENSEMBL reference proteome and non canonical proteins like pseudo genes, non coding rnas or alternative open reading frames.

See usage docs for all of the available options when running the pipeline.

Pipeline Summary

By default, the pipeline currently performs the following:

ProteoGenomics Database

  • Download protein databases from ENSEMBL
  • Translate from Genomics Variant databases into ProteoGenomics Databases (COSMIC, GNOMAD)
  • Add to a Reference proteomics database, non-coding RNAs + pseudogenes.
  • Compute Decoy for a proteogenomics databases

Documentation

The nf-core/pgdb pipeline comes with documentation about the pipeline: usage and output.

Credits

nf-core/pgdb was originally written by Husen M. Umer (EMBL-EBI) & Yasset Perez-Riverol (Karolinska Institute)

Contributions and Support

If you would like to contribute to this pipeline, please see the contributing guidelines.

For further information or help, don't hesitate to get in touch on the Slack #pgdb channel (you can join with this invite).

Citations

You can cite the nf-core publication as follows:

The nf-core framework for community-curated bioinformatics pipelines.

Philip Ewels, Alexander Peltzer, Sven Fillinger, Harshil Patel, Johannes Alneberg, Andreas Wilm, Maxime Ulysse Garcia, Paolo Di Tommaso & Sven Nahnsen.

Nat Biotechnol. 2020 Feb 13. doi: 10.1038/s41587-020-0439-x.

An extensive list of references for the tools used by the pipeline can be found in the CITATIONS.md file.

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The ProteoGenomics database generation workflow creates different protein databases for ProteoGenomics data analysis.

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