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Status](https://github.com/nf-core/pgdb/workflows/nf-core%20CI/badge.svg)](https://github.com/nf-core/pgdb/actions?query=workflow%3A%22nf-core+CI%22)\n[![GitHub Actions Linting Status](https://github.com/nf-core/pgdb/workflows/nf-core%20linting/badge.svg)](https://github.com/nf-core/pgdb/actions?query=workflow%3A%22nf-core+linting%22)\n[![AWS CI](https://img.shields.io/badge/CI%20tests-full%20size-FF9900?logo=Amazon%20AWS)](https://nf-co.re/pgdb/results)\n[![Cite with Zenodo](https://zenodo.org/badge/DOI/10.5281/zenodo.4722662.svg)](https://doi.org/10.5281/zenodo.4722662)\n\n[![Nextflow](https://img.shields.io/badge/nextflow%20DSL2-%E2%89%A521.10.3-23aa62.svg)](https://www.nextflow.io/)\n[![run with conda](http://img.shields.io/badge/run%20with-conda-3EB049?logo=anaconda)](https://docs.conda.io/en/latest/)\n[![run with docker](https://img.shields.io/badge/run%20with-docker-0db7ed?logo=docker)](https://www.docker.com/)\n[![run with singularity](https://img.shields.io/badge/run%20with-singularity-1d355c.svg)](https://sylabs.io/docs/)\n[![Launch on Nextflow Tower](https://img.shields.io/badge/Launch%20%F0%9F%9A%80-Nextflow%20Tower-%234256e7)](https://tower.nf/launch?pipeline=https://github.com/nf-core/pgdb)\n\n[![Get help on Slack](http://img.shields.io/badge/slack-nf--core%20%23pgdb-4A154B?logo=slack)](https://nfcore.slack.com/channels/pgdb)\n[![Follow on Twitter](http://img.shields.io/badge/twitter-%40nf__core-1DA1F2?logo=twitter)](https://twitter.com/nf_core)\n[![Watch on YouTube](http://img.shields.io/badge/youtube-nf--core-FF0000?logo=youtube)](https://www.youtube.com/c/nf-core)\n\n## Introduction\n\n**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:\n\n- The reference proteome (ENSEMBL Reference proteome)\n- Non canonical proteins: pseudo-genes, sORFs, lncRNA.\n- Variants: COSMIC, cBioPortal, GENOMAD variants\n\nThe pipeline allows to estimate decoy proteins with different methods and attach them to the final proteogenomics database.\n\nThe pipeline is built using [Nextflow](https://www.nextflow.io), 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.\n\n## Quick Start\n\n1. Install [`Nextflow`](https://www.nextflow.io/docs/latest/getstarted.html#installation) (`\u003e=21.10.3`)\n\n2. Install any of [`Docker`](https://docs.docker.com/engine/installation/), [`Singularity`](https://www.sylabs.io/guides/3.0/user-guide/) (you can follow [this tutorial](https://singularity-tutorial.github.io/01-installation/)), [`Podman`](https://podman.io/), [`Shifter`](https://nersc.gitlab.io/development/shifter/how-to-use/) or [`Charliecloud`](https://hpc.github.io/charliecloud/) for full pipeline reproducibility _(you can use [`Conda`](https://conda.io/miniconda.html) both to install Nextflow itself and also to manage software within pipelines. Please only use it within pipelines as a last resort; see [docs](https://nf-co.re/usage/configuration#basic-configuration-profiles))_.\n\n3. Download the pipeline and test it on a minimal dataset with a single command:\n\n   ```console\n   nextflow run nf-core/pgdb -profile test,YOURPROFILE --outdir \u003cOUTDIR\u003e\n   ```\n\n   Note that some form of configuration will be needed so that Nextflow knows how to fetch the required software. This is usually done in the form of a config profile (`YOURPROFILE` in the example command above). You can chain multiple config profiles in a comma-separated string.\n\n   \u003e - The pipeline comes with config profiles called `docker`, `singularity`, `podman`, `shifter`, `charliecloud` and `conda` which instruct the pipeline to use the named tool for software management. For example, `-profile test,docker`.\n   \u003e - Please check [nf-core/configs](https://github.com/nf-core/configs#documentation) to see if a custom config file to run nf-core pipelines already exists for your Institute. If so, you can simply use `-profile \u003cinstitute\u003e` in your command. This will enable either `docker` or `singularity` and set the appropriate execution settings for your local compute environment.\n   \u003e - If you are using `singularity`, please use the [`nf-core download`](https://nf-co.re/tools/#downloading-pipelines-for-offline-use) command to download images first, before running the pipeline. Setting the [`NXF_SINGULARITY_CACHEDIR` or `singularity.cacheDir`](https://www.nextflow.io/docs/latest/singularity.html?#singularity-docker-hub) Nextflow options enables you to store and re-use the images from a central location for future pipeline runs.\n   \u003e - If you are using `conda`, it is highly recommended to use the [`NXF_CONDA_CACHEDIR` or `conda.cacheDir`](https://www.nextflow.io/docs/latest/conda.html) settings to store the environments in a central location for future pipeline runs.\n\n4. Start running your own analysis!\n\n   ```bash\n   nextflow run nf-core/pgdb -profile \u003cdocker/singularity/podman/conda/institute\u003e --ncrna true --pseudogenes true --altorfs true\n   ```\n\n   \u003e 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.\n\nSee [usage docs](https://nf-co.re/pgdb/usage) for all of the available options when running the pipeline.\n\n## Pipeline Summary\n\nBy default, the pipeline currently performs the following:\n\n![ProteoGenomics Database](/docs/images/pgdb-databases.png)\n\n- Download protein databases from ENSEMBL\n- Translate from Genomics Variant databases into ProteoGenomics Databases (`COSMIC`, `GNOMAD`)\n- Add to a Reference proteomics database, non-coding RNAs + pseudogenes.\n- Compute Decoy for a proteogenomics databases\n\n## Documentation\n\nThe nf-core/pgdb pipeline comes with documentation about the pipeline: [usage](https://nf-co.re/pgdb/usage) and [output](https://nf-co.re/pgdb/output).\n\n## Credits\n\nnf-core/pgdb was originally written by Husen M. Umer (EMBL-EBI) \u0026 Yasset Perez-Riverol (Karolinska Institute)\n\n## Contributions and Support\n\nIf you would like to contribute to this pipeline, please see the [contributing guidelines](.github/CONTRIBUTING.md).\n\nFor further information or help, don't hesitate to get in touch on the [Slack `#pgdb` channel](https://nfcore.slack.com/channels/pgdb) (you can join with [this invite](https://nf-co.re/join/slack)).\n\n## Citations\n\nThe pgdb pipeline should be cited using the following citation:\n\n\u003e Umer HM, Audain E, Zhu Y, Pfeuffer J, Sachsenberg T, Lehtiö J, Branca R, Perez-Riverol Y. Generation of ENSEMBL-based proteogenomics databases boosts the identification of non-canonical peptides.\n\u003e\n\u003e _Bioinformatics_. 2021 Dec 14;38(5):1470–2. doi: [10.1093/bioinformatics/btab838](https://dx.doi.org/10.1093/bioinformatics/btab838). Epub ahead of print. PMID: 34904638; PMCID: PMC8825679.\n\nadditionally you can cite the pipeline directly with the following doi: 10.5281/zenodo.4722662\n\nAn extensive list of references for the tools used by the pipeline can be found in the [`CITATIONS.md`](CITATIONS.md) file.\n\nYou can cite the `nf-core` publication as follows:\n\n\u003e **The nf-core framework for community-curated bioinformatics pipelines.**\n\u003e\n\u003e Philip Ewels, Alexander Peltzer, Sven Fillinger, Harshil Patel, Johannes Alneberg, Andreas Wilm, Maxime Ulysse Garcia, Paolo Di Tommaso \u0026 Sven Nahnsen.\n\u003e\n\u003e _Nat Biotechnol._ 2020 Feb 13. doi: [10.1038/s41587-020-0439-x](https://dx.doi.org/10.1038/s41587-020-0439-x).\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fbigbio%2Fpgdb","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fbigbio%2Fpgdb","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fbigbio%2Fpgdb/lists"}