pgatk -- ProteoGenomics Analysis Toolkit

pgatk is a Python toolkit for building proteogenomics protein sequence databases. It downloads, translates, and combines variant and non-canonical sequences from multiple genomic sources into search-ready FASTA databases compatible with all major proteomics search engines.

Key Features

• Multi-source variant integration -- Translate variants from ENSEMBL, VCF files, COSMIC, cBioPortal, ClinVar, and gnomAD into protein sequences
• Non-canonical ORF discovery -- Three-frame and six-frame translation of lncRNAs, pseudogenes, antisense transcripts, and alternative reading frames
• Any species -- Supports all organisms available in ENSEMBL (human, mouse, rice, wheat, etc.)
• Search engine compatible -- Output FASTA files work with MaxQuant, SearchGUI, MSFragger, Comet, DIA-NN, and Proteome Discoverer
• Decoy generation -- Multiple target-decoy strategies (DecoyPYrat, protein-reverse, protein-shuffle)
• Peptide-to-genome mapping -- Map identified peptides back to genomic coordinates (GFF3) for genome browser visualization
• ClinVar without VEP -- ClinVar pipeline uses BedTools interval overlap, no VEP annotation required

Installation

pip (recommended)

pip install pgatk

Bioconda

conda install -c bioconda pgatk

From source

git clone https://github.com/bigbio/pgatk.git
cd pgatk
pip install .

Quick Start

Build a human variant protein database in four commands:

# 1. Download ENSEMBL data for human
pgatk ensembl-downloader -t 9606 -o ensembl_human

# 2. Extract transcript sequences (requires gffread)
gffread -F -w ensembl_human/transcripts.fa \
    -g ensembl_human/genome.fa \
    ensembl_human/Homo_sapiens.GRCh38.*.gtf.gz

# 3. Translate variants to protein sequences
pgatk vcf-to-proteindb \
    --vcf ensembl_human/homo_sapiens_incl_consequences.vcf.gz \
    --input_fasta ensembl_human/transcripts.fa \
    --gene_annotations_gtf ensembl_human/Homo_sapiens.GRCh38.*.gtf.gz \
    --output_proteindb variant_proteins.fa

# 4. Generate target-decoy database
pgatk generate-decoy \
    --input variant_proteins.fa \
    --output target_decoy.fa \
    --method decoypyrat

Commands

Data Downloaders

Variant-to-Protein Translation

Sequence Translation

Database Processing

Post-Processing

Supported Variant Sources

Use Cases

Detailed end-to-end workflows are available in docs/use-cases.md:

1. Cell-type specific non-canonical peptide discovery -- Reproduce the analysis from Umer et al. 2022
2. Human variant protein database -- Standard ENSEMBL-based variant proteogenomics
3. Population-specific databases -- gnomAD ancestry-stratified variant databases
4. ClinVar clinical variants -- Clinical variant detection at the protein level
5. Cancer proteogenomics -- COSMIC, cBioPortal, and patient-specific tumor databases
6. Novel ORF and micropeptide discovery -- lncRNA, pseudogene, and alternative ORF translation
7. Genome annotation refinement -- Six-frame translation and peptide-to-genome mapping
8. Metaproteomics -- Six-frame translation of metagenome assemblies
9. Long-read transcriptomics -- Isoform-resolved protein databases from PacBio/ONT data
10. Plant and non-model organisms -- Proteogenomics for any ENSEMBL species

Project Structure

pgatk/
├── commands/           # CLI command definitions (Click)
├── ensembl/            # ENSEMBL data download and VCF translation
├── cgenomes/           # COSMIC and cBioPortal handling
├── clinvar/            # ClinVar variant translation
├── proteogenomics/     # Spectral validation tools
├── proteomics/         # Protein database utilities (decoy generation)
├── db/                 # Peptide digestion and genome mapping
├── config/             # YAML configuration files
└── toolbox/            # Shared utilities

Full Documentation

https://pgatk.quantms.org

Cite

If you use pgatk in your research, please cite:

Husen M Umer, Enrique Audain, Yafeng Zhu, Julianus Pfeuffer, Timo Sachsenberg, Janne Lehtiö, Rui M Branca, Yasset Perez-Riverol. Generation of ENSEMBL-based proteogenomics databases boosts the identification of non-canonical peptides. Bioinformatics, Volume 38, Issue 5, 1 March 2022, Pages 1470--1472. https://doi.org/10.1093/bioinformatics/btab838

Contributing

git clone https://github.com/bigbio/pgatk.git
cd pgatk
pip install -e ".[dev]"
pytest

License

Apache License 2.0