metaumbra 1.1.2

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.

pip install metaumbra

Usage

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

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
weighted_evidence	Total degeneracy-weighted peptide evidence
weighted_evidence_shared	Weighted evidence from shared peptides
p_presence	Genome-level p-value
q_presence	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.