do not merge: Fix iBAQ normalization silently skipped for protein groups (issue #8466)

[timosachsenberg]

The root cause could be an accession mismatch between prot_quant_ keys and ProteinHit accessions:

• transferPeptideDataToProteins_() populates prot_quant_ using LEADER accessions from getAccession_() + mapAccessionToLeader()
• performIbaqNormalization_() iterated over protein hits directly and looked up hit.getAccession() in prot_quant_
• When protein groups exist, non-leader hits would fail the lookup, silently skipping iBAQ normalization

The fix changes performIbaqNormalization_() to:

1. Build the same accession_to_leader mapping used elsewhere
2. Create a reverse leader_to_members mapping
3. Iterate over prot_quant_ entries (keyed by leaders) instead of hits
4. For each leader, find a sequence from the leader hit or any member

This ensures iBAQ normalization is applied correctly even when:

• Leader accession differs from protein hit accessions
• Only group member hits have sequences
• Complex protein inference produces group structures

Added two test cases that expose the bug:

• iBAQ with indistinguishable protein groups (leader present)
• iBAQ with missing leader protein hit (only members present)

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[timosachsenberg]

How the Mismatch Happens in ProteomicsLFQ

In a typical ProteomicsLFQ workflow, the accession mismatch occurs during the protein inference step.

---

1. Initial Peptide-to-Protein Mapping (PeptideIndexer)

Peptide AAAK → {sp|P12345|PROTA, sp|P67890|PROTB} Peptide CCCK → {sp|P12345|PROTA, sp|P67890|PROTB}

Both proteins share the same peptides → they are indistinguishable.

---

2. Protein Inference (Epifany / BayesianProteinInference)

Creates indistinguishable protein groups:

ProteinGroup {
  accessions: ["sp|P12345|PROTA", "sp|P67890|PROTB"],  // Leader is first
  probability: 0.95
}
The leader (sp|P12345|PROTA) is chosen based on scoring or alphabetical order.

3. What Gets Stored in ConsensusXML
ProteinHits (may or may not contain all group members):

<ProteinHit accession="sp|P67890|PROTB" sequence="AAAKCCCK..." />
<!-- Leader sp|P12345|PROTA might be missing or have no sequence! -->
IndistinguishableProteins (group structure):

<UserParam name="indistinguishable_proteins_0"
           value="0.95,sp|P12345|PROTA,sp|P67890|PROTB"/>
4. The Bug in ProteinQuantifier / iBAQ
Step A — transferPeptideDataToProteins_()
// Peptide references "sp|P67890|PROTB"
// mapAccessionToLeader() returns: "sp|P67890|PROTB" → "sp|P12345|PROTA"
// getAccession_() returns the LEADER

prot_quant_["sp|P12345|PROTA"].total_abundances[0] = 1234.0; 
// Stored under LEADER
Step B — performIbaqNormalization_() (OLD BUGGY CODE)

for (auto& hit : proteins.getHits())  // Only sees "sp|P67890|PROTB"
{
  // hit.getAccession() = "sp|P67890|PROTB"
  if (prot_quant_.find("sp|P67890|PROTB") != end())  // FALSE! Key is leader
  {
    // NEVER EXECUTED → normalization skipped
  }
}

[timosachsenberg]

@jpfeuffer that was the AI explanation.

[jpfeuffer]

I agree it is safer but do you agree that during normal usage (especially in proteomicslfq which was mentioned in the reported issue) the hits should always be a strict be a superset of the leader accessions and therefore the lookup should never fail? That is how inference is performed.

I also am not sure why the bot would need a reverse map? Why would one need to quantify or normalize the group members?? There should be no quant values available for them.

[timosachsenberg]

I agree and don't know why it could be no superset. So we should do something like:

iBAQ = Σ Intensity(unique peptides assigned to protein group leader)
       ---------------------------------------------------------
            N_theoretical(peptides for protein group leader)