nf-core pipeline · cosmic, gnomad, protein-databases
nf-core/proteogenomicsdb
Builds customised proteogenomics databases from reference proteomes, non-canonical sequences, and genomic variants.
What nf-core/proteogenomicsdb is
nf-core/proteogenomicsdb (also known as pgdb) is a bioinformatics pipeline created by Husen M. Umer and Yasset Perez-Riverol to construct specialised protein sequence databases for proteogenomics research.
Standard proteomics searches rely on canonical reference sequences, which typically omit non-canonical open reading frames, pseudogenes, and genomic variants. The pipeline addresses this by combining standard Ensembl reference proteomes with non-canonical transcripts and translated genomic variants, providing search databases capable of identifying non-standard peptides in mass spectrometry data.
The workflow is implemented in Nextflow and uses the pypgatk toolkit to automate database retrieval, translation, filtering, and decoy sequence generation.
What the pipeline does
The workflow starts by retrieving reference protein databases directly from Ensembl. It can subsequently extract and translate non-canonical protein sequences, including long non-coding RNAs (lncRNAs), pseudogenes, and small or alternative open reading frames (sORFs/altORFs).
In parallel, the pipeline translates genomic variants from sources such as COSMIC, cBioPortal, and gnomAD into variant protein sequences. It then computes decoy proteins using configurable estimation methods and concatenates the canonical, non-canonical, variant, and decoy sequences into a final database ready for proteomics search engines.
Key facts
- Workflow engine
- Nextflow
- Core toolkit
- pypgatk
- Reference proteome source
- Ensembl
- Variant sources
- COSMIC, cBioPortal, gnomAD
- Non-canonical categories
- Pseudogenes, lncRNAs, sORFs / altORFs
- Original developers
- Husen M. Umer (EMBL-EBI) and Yasset Perez-Riverol (Karolinska Institute)
- Latest release
- 1.0.0 (2021-04-27)
What you can use it for
- Reference and non-canonical database construction
- Building protein sequence databases that integrate canonical Ensembl proteomes with translated pseudogenes, non-coding RNAs, and alternative open reading frames.
- Cancer proteogenomics variant searching
- Translating cancer mutation records from COSMIC or cBioPortal into protein sequence databases to identify mutated peptides in tumour proteomics datasets.
- Population variant database generation
- Translating genomic variation catalogues from gnomAD into protein FASTA files to detect germline peptide variants.
- Target-decoy database preparation
- Computing decoy protein sequences using selected estimation methods and appending them to proteogenomic databases for false discovery rate estimation.
Run it here
The research agent runs nf-core/proteogenomicsdb with Nextflow on its own machine — up to 32 cores, 256 GiB of memory and 24 hours per run, which covers the test profile and real single-sample runs. It builds the samplesheet, checks it against the pipeline's schema and reads the results back. When a run is too big for one machine, it gives you the exact command for your own cluster instead.
Strengths and limits
Good at
- Translates genomic variants directly from established sources like COSMIC and gnomAD into proteogenomic databases.
- Captures non-canonical translations including pseudogenes, lncRNAs, and alternative open reading frames.
- Includes automated decoy sequence generation to support target-decoy search strategies in mass spectrometry.
- Employs Nextflow and containerisation to ensure portable and reproducible database generation across platforms.
Watch out for
- The workflow only generates protein search databases and does not perform spectrum matching, peptide identification, or downstream statistical analyses.
- Supported automated variant translation and reference downloads are tied specifically to the Ensembl, COSMIC, cBioPortal, and gnomAD data formats handled by pypgatk.
Questions
Can I run nf-core/proteogenomicsdb without my own cluster?
The research agent runs nf-core/proteogenomicsdb with Nextflow on its own machine — up to 32 cores, 256 GiB of memory and 24 hours per run, which covers the test profile and real single-sample runs. It builds the samplesheet, checks it against the pipeline's schema and reads the results back. When a run is too big for one machine, it gives you the exact command for your own cluster instead.
What licence is nf-core/proteogenomicsdb under?
MIT, like every nf-core pipeline.
Which reference proteome sources does the pipeline support?
The pipeline downloads and uses the Ensembl reference proteome as its reference database.
What genomic variant resources can be translated into protein databases?
The pipeline translates variant databases from COSMIC, cBioPortal, and gnomAD into proteogenomic protein sequences.
What non-canonical sequences can be included?
It can incorporate translated sequences derived from pseudogenes, non-coding RNAs (lncRNAs), and alternative or small open reading frames (altORFs/sORFs).
Does the pipeline produce decoy sequences for mass spectrometry searches?
Yes, it can estimate decoy proteins using various methods and attach them directly to the final proteogenomics database.
How to cite it
Philip Ewels, Alexander Peltzer, Sven Fillinger, Harshil Patel, Johannes Alneberg, Andreas Wilm, Maxime Ulysse Garcia, Paolo Di Tommaso & Sven Nahnsen. The nf-core framework for community-curated bioinformatics pipelines. Nat Biotechnol. 2020 Feb 13. doi: 10.1038/s41587-020-0439-x.
Written from nf-core/proteogenomicsdb's own README. Statements citing a figure that does not appear there are removed before publication. Licence and running details come from our registry.