metaumbra 1.1.3

Genome-level presence inference from metaproteomic peptide lists.

MetaUmbra

Genome-level presence inference from metaproteomic peptides

MetaUmbra performs genome-level presence inference from metaproteomic peptide lists. It combines unique peptide support with weighted shared peptide evidence to identify statistically supported microbial genomes and generate interpretable presence rankings.

Main features

• Evaluate candidate genome support from metaproteomic peptide tables
• Build genome-specific theoretical peptide references from protein FASTA files
• Support user-defined genome collections, including isolate genomes, strain panels, and MAG catalogs
• Use both unique and shared peptide evidence for genome presence inference
• Report genome-level p-values, BH-adjusted q-values, and presence scores
• Provide GUI, command-line, and Python workflow support
• Support peptide tables from common metaproteomics workflows such as DIA-NN and MaxQuant

Workflow overview

Installation

MetaUmbra requires Python 3.10 or newer.

# Install with all features (GUI, parquet support)
pip install metaumbra[all]

or

# Install with core features only
pip install metaumbra

Usage

MetaUmbra can be used through either the graphical interface or the command line.

For a detailed walkthrough, including input formats, CLI examples, output interpretation, and troubleshooting, see the MetaUmbra Usage Guide.

Graphical interface

metaumbra-gui

The GUI supports FASTA digestion, peptide table loading, genome presence scoring, and result export.

Command line

MetaUmbra provides separate commands for the main workflow steps:

metaumbra digest --help
metaumbra score --help
metaumbra extract-parquet --help

A typical workflow is:

metaumbra digest ...
metaumbra score ...

Use metaumbra extract-parquet ... to convert DIA-NN parquet reports to peptide TSV files before scoring.

Input

MetaUmbra requires:

• Protein FASTA files, with one FASTA file per genome
• An observed peptide table containing peptide sequences

Optional inputs include peptide scores, peptide-level error values, decoy flags, and genome lineage annotations.

Output

The main output is a TSV table containing genome-level evidence and significance values.

Key output columns include:

Column	Description
genome_id	Candidate genome identifier
num_peptides_matched	Number of observed peptides matched to the genome
num_peptides_unique	Number of matched peptides unique to the genome
shared_fraction	Fraction of matched peptides that are shared with other genomes
mean_degeneracy	Mean number of genomes containing the matched peptides
pvalue	Genome-level p-value
qvalue	BH-adjusted genome-level q-value
presence_score	Ranking score based on q-value

Citation

If you use MetaUmbra, please cite:

Wu Q, Ning Z, Zhang A, Cheng K, Figeys D. MetaUmbra: Statistically Controlled Genome-Level Presence Inference from Metaproteomic Peptides.[J]. bioRxiv, 2026.

A formal citation will be added after publication.

Contact

For questions or issues, please use the GitHub issue tracker or contact the corresponding author listed in the associated manuscript.