fix(summarization): Fix Rename ref regression covariate to ref_covariate for SRM experiments

[tonywu1999]

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Checklist Before Requesting a Review

• I have read the MSstats contributing guidelines
• My changes generate no new warnings
• Any dependent changes have been merged and published in downstream modules
• I have run the devtools::document() command after my changes and committed the added files

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PR Type

Bug fix, Tests

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Description

• Fix SRM covariate reference column usage

• Update imputation merge key names

• Add regression test for saved output

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Diagram Walkthrough

flowchart LR
  srm["SRM summarized input"] 
  cov["Use ref_covariate column"] 
  merge["Merge imputed output correctly"] 
  test["Regression test against saved SRM output"]
  srm -- "reference lookup" --> cov
  cov -- "feeds" --> merge
  merge -- "verified by" --> test

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File Walkthrough

	Relevant files
Bug fix	linear_summary.cpp Fix reference covariate lookup in C++                                        src/linear_summary.cpp Read reference values from ref_covariate Align SRM covariate lookup with input schema +1/-1      utils_output.R Update R output merge covariate column                                      R/utils_output.R Use ref_covariate in imputation merge keys Keep merged summarized output consistent +1/-1
Tests	test_dataProcess.R Add SRM regression coverage for dataProcess                            inst/tinytest/test_dataProcess.R Load saved SRM processed output fixture Assert current output matches saved result Preserve heavy-label rows validation +8/-0

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[github-actions]

PR Reviewer Guide 🔍

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⏱️ Estimated effort to review: 2 🔵🔵⚪⚪⚪

🧪 PR contains tests

🔒 No security concerns identified

⚡ Recommended focus areas for review Wrong length ref_covariate appears to be a per-row column, but the new code still uses refs.length() to decide how many entries to pull from contrast_matrix. On SRM inputs where many rows share the same reference covariate, this makes seq(0, n_refs - 2) much larger than the number of actual reference levels and can return incorrect or out-of-bounds contrast values. unique_refs is already computed here and seems to be the intended count. CharacterVector refs = input["ref_covariate"]; CharacterVector unique_refs = unique(refs); int n_refs = refs.length(); ref = contrast_matrix[seq(0, n_refs - 2)];

[github-actions]

PR Code Suggestions ✨

Explore these optional code suggestions:

Category	Suggestion	Impact
Possible issue	Align merge keys safely Building the merge keys from input alone can fail when predicted_survival still carries the legacy ref column or omits ref_covariate. Derive the reference key from columns shared by both tables so imputation does not break on mixed-schema data. R/utils_output.R [131-137] -cols = intersect(colnames(input), c("newABUNDANCE", - "cen", "RUN", - "FEATURE", "ref_covariate")) +merge_keys = c("cen", "RUN", "FEATURE") +if ("ref_covariate" %in% colnames(input) && + "ref_covariate" %in% colnames(predicted_survival)) { + merge_keys = c(merge_keys, "ref_covariate") +} else if ("ref" %in% colnames(input) && + "ref" %in% colnames(predicted_survival)) { + merge_keys = c(merge_keys, "ref") +} +cols = intersect(colnames(input), c("newABUNDANCE", merge_keys)) input = merge(input[, colnames(input) != "newABUNDANCE", with = FALSE], predicted_survival, - by = setdiff(cols, "newABUNDANCE"), + by = merge_keys, all.x = TRUE) Suggestion importance[1-10]: 6 __ Why: Building merge keys from input alone can fail if predicted_survival does not expose the same reference column, so checking for a shared ref_covariate or ref is a sensible safeguard. The suggestion is relevant and plausible, but its importance depends on whether mixed-schema tables are actually expected after this PR.	Low
	Preserve legacy reference support Accessing input["ref_covariate"] unconditionally can throw at runtime for callers that still pass the legacy ref column. Choose the available reference column dynamically so this path works with both old and new input schemas. src/linear_summary.cpp [69-70] CharacterVector temp_ref = coef_names[find_ref]; -CharacterVector refs = input["ref_covariate"]; +CharacterVector input_names = input.names(); +bool has_ref_covariate = false; +for (int i = 0; i < input_names.size(); ++i) { + if (input_names[i] == "ref_covariate") { + has_ref_covariate = true; + break; + } +} +CharacterVector refs = has_ref_covariate + ? CharacterVector(input["ref_covariate"]) + : CharacterVector(input["ref"]); Suggestion importance[1-10]: 5 __ Why: Accessing input["ref_covariate"] directly can raise a runtime error if some callers still provide only ref, so the fallback is technically sound. Still, the PR appears to be intentionally renaming the schema to ref_covariate, which makes this more of a backward-compatibility improvement than a clear defect in the change.	Low