Module quant 

Multi-sample quantitation over a koth-aligned matrix: correct the peptide->protein feature assignment using the across-sample intensity pattern, then emit a protein-group × sample abundance matrix.

uno is an ID + quant tool, not a stats framework. It stops at the abundance matrix; normalization, differential-expression testing, and interpretation are left to downstream tools (MSstats/limma/etc.), which take this matrix plus the experimental design. So there is deliberately NO design file, contrast, or FDR here — only the pieces that make the abundance values correct:

• resolve_feature_competition — one feature quantifies for one protein (parsimony), so a minority peptide can’t measure a mass-coincident feature owned by an abundant background.
• profile_reassign — re-route a feature to the protein whose across-sample profile it tracks, fixing mass+RT ties the ID stage couldn’t (design-free: uses variation, not condition labels).
• group_abundance — sum each protein group’s assigned peptides per run.

Modules

directms1

DirectMS1Quant two-condition statistics (reference port) and the uno per-run evidence adapter. Exposed as uno quant. Rust reimplementation of pinned DirectMS1Quant contrast analysis, part of uno-core. Adapted from Mark Ivanov’s Apache-2.0 implementation; see THIRD_PARTY.md.

Functions

feature_winners

The one-feature-one-protein claim behind resolve_feature_competition, on plain (feature, score) columns so per-run quantitative evidence can replay exactly the same rule. Returns the winning row indices in ascending (input) order. A feature goes to its highest-scoring row; ties keep the lower index; rows with a non-finite score never win.

group_abundance

Protein-group abundance matrix — uno’s quant deliverable (design-free).

profile_reassign

Single-pass profile-guided reassignment (combines ID and quant).

resolve_feature_competition

Feature-level competition for quant: each consensus feature may quantify for only ONE protein — the best-scoring one whose peptide claims it. uno’s ID stage already does this (parsimony: one peak → one protein), but the per-peptide quant feature-pick discards it and lets any peptide grab any mass+RT match. On a mixed proteome that means a minority-species peptide (e.g. E. coli) quantifies on a mass-coincident feature owned by an abundant background protein, reading its flat profile instead of the real signal. Replaying the claim here — a feature goes to the peptide whose protein scores highest — drops those stolen features, so the minority peptide falls back to its real feature or drops out. prot_score maps (decoy, accession) → the protein’s binomial score (higher = more confident).