style(countMissingPercentage): Fix styling of arrows to equal signs

[tonywu1999]

User description

Motivation and Context

Accidentally used arrows instead of equal signs in #171

Changes

• Fix styling from arrows to equal signs.

Testing

Existing unit tests pass

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

Enhancement, Tests

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Description

• Standardize assignment operators to '='

• Align function usage across code, tests

• Minor refactor in counts indexing

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Diagram Walkthrough

flowchart LR
  utils["R/utils_groupcomparison.R getSamplesInfo()"] -- "style: <- to =" --> utils
  tests["inst/tinytest/test_utils_groupcomparison.R"] -- "style: <- to =" --> tests
  utils -- "consistent API expectations" --> tests

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File Walkthrough

	Relevant files
Enhancement	utils_groupcomparison.R Use '=' for counts reassignment                                                    R/utils_groupcomparison.R Replace '<-' with '=' for assignment Keep logic and data.table operations unchanged +1/-1
Tests	test_utils_groupcomparison.R Tests updated to '=' assignment style                                        inst/tinytest/test_utils_groupcomparison.R Replace '<-' with '=' throughout tests Preserve all test logic and expectations +49/-49

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Summary by CodeRabbit

• Style
  • Standardized assignment operator usage for consistency; no behavioral changes.
• Tests
  • Updated test code to use consistent assignment syntax; test logic and outcomes unchanged.
• Notes
  • No user-facing changes in this release.

[coderabbitai]

Walkthrough

Replaced R assignment operator <- with = in a utility function and corresponding tests. No logic, control flow, or public API changes.

Changes

Cohort / File(s)	Summary
Utilities: assignment syntax R/utils_groupcomparison.R	Switched assignment in .countMissingPercentage from <- to = with no behavioral change.
Tests: assignment syntax inst/tinytest/test_utils_groupcomparison.R	Replaced <- with = across tests; test data and assertions unchanged.

Estimated code review effort

🎯 1 (Trivial) | ⏱️ ~2 minutes

Suggested labels

Review effort 2/5

Suggested reviewers

• mstaniak

Poem

A whisker twitch, a tidy tweak,
I hop through code with syntax chic.
From <- to =, neat as can be,
Carrots aligned in harmony.
Tests still nibble, green and bright—
Thump! Another tidy night. 🥕🐇

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[github-actions]

PR Reviewer Guide 🔍

Here are some key observations to aid the review process:

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

🧪 PR contains tests

🔒 No security concerns identified

⚡ Recommended focus areas for review Possible Reordering Bug The new reindexing of counts using match(intersect(colnames(contrast_matrix), GROUP), GROUP) could introduce NA rows or drop groups unexpectedly if names are missing or ordering assumptions change. Verify behavior when contrast_matrix has groups not present in counts and ensure no NA indices slip through. counts = counts[match(intersect(colnames(contrast_matrix), GROUP), GROUP), ] Test Determinism Tests now construct objects with = consistently, but some expectations depend on ordering derived from contrast_matrix and samples_info. Confirm tests cover mismatched ordering between contrast_matrix columns and summarized$GROUP to catch potential reindexing issues introduced in the code change. expect_true(setequal(names(output), c(names(result), "MissingPercentage")), info = "Basic functionality: No extraneous columns added") ## Test 2: With imputed values contrast_matrix = matrix(c(1, -1), nrow = 1, ncol = 2) colnames(contrast_matrix) = c("Group1", "Group2") summarized = data.table::data.table( GROUP = c("Group1", "Group2"), TotalGroupMeasurements = c(100, 100), NumMeasuredFeature = c(80, 70), NumImputedFeature = c(10, 20) ) result = list() samples_info = data.table::data.table(GROUP = c("Group1", "Group2"), NumRuns = c(10, 10)) output = MSstats:::.countMissingPercentage(contrast_matrix, summarized, result, samples_info, TRUE) expected_missing = 1 - (80 + 70) / (100 + 100) # 0.25 expected_imputed = (10 + 20) / (100 + 100) # 0.15 expect_equal(output$MissingPercentage[1], expected_missing, info = "Imputed values: Missing percentage calculation") expect_equal(output$ImputationPercentage[1], expected_imputed, info = "Imputed values: Imputation percentage calculation") ## Test 3: With empty conditions (groups not in summarized data) contrast_matrix = matrix(c(1, -1, 0), nrow = 1, ncol = 3) colnames(contrast_matrix) = c("Group1", "Group2", "Group3") summarized = data.table::data.table( GROUP = c("Group1"), TotalGroupMeasurements = c(100), NumMeasuredFeature = c(80), NumImputedFeature = c(0) ) result = list() samples_info = data.table::data.table(GROUP = c("Group1", "Group2", "Group3"), NumRuns = c(10, 10, 10)) output = MSstats:::.countMissingPercentage(contrast_matrix, summarized, result, samples_info, FALSE) expect_equal(length(output$MissingPercentage), 1, info = "Empty conditions: MissingPercentage length") expect_true(is.numeric(output$MissingPercentage), info = "Empty conditions: Numeric output") ## Test 4: Multiple contrasts with different missing patterns contrast_matrix = matrix(c(1, -1, 0, 0, 1, -1, 1, 0, -1), nrow = 3, ncol = 3, byrow = TRUE) colnames(contrast_matrix) = c("Group3", "Group2", "Group1") summarized = data.table::data.table( GROUP = c("Group1", "Group2", "Group3"), TotalGroupMeasurements = c(100, 100, 100), NumMeasuredFeature = c(90, 80, 70), NumImputedFeature = c(5, 10, 15) ) result = list() samples_info = data.table::data.table( GROUP = c("Group3", "Group2", "Group1"), NumRuns = c(1, 1, 1) ) output = MSstats:::.countMissingPercentage(contrast_matrix, summarized, result, samples_info, TRUE) expected_missing_1 = 1 - (70 + 80) / (100 + 100) # 1 - 150/200 = 0.25 expected_imputed_1 = (15 + 10) / (100 + 100) # 25/200 = 0.125 expected_missing_2 = 1 - (80 + 90) / (100 + 100) # 1 - 170/200 = 0.15 expected_imputed_2 = (10 + 5) / (100 + 100) # 15/200 = 0.075 expected_missing_3 = 1 - (70 + 90) / (100 + 100) # 1 - 160/200 = 0.20 expected_imputed_3 = (15 + 5) / (100 + 100) # 20/200 = 0.10 expect_equal(length(output$MissingPercentage), 3, info = "Column ordering: MissingPercentage length") expect_equal(length(output$ImputationPercentage), 3, info = "Column ordering: ImputationPercentage length") expect_equal(output$MissingPercentage[1], expected_missing_1, info = "Column ordering: Contrast 1 missing percentage (Group3 vs Group2)")

[github-actions]

PR Code Suggestions ✨

Explore these optional code suggestions:

Category	Suggestion	Impact
Possible issue	Guard against NA indices match can return NA for non-matches, which will propagate NA rows and potentially reorder incorrectly, leading to dropped or NA rows in counts. Filter to valid indices before subsetting to avoid accidental NA subsetting and preserve intended ordering. R/utils_groupcomparison.R [409] -counts = counts[match(intersect(colnames(contrast_matrix), GROUP), GROUP), ] +ord <- match(intersect(colnames(contrast_matrix), counts$GROUP), counts$GROUP) +ord <- ord[!is.na(ord)] +counts <- counts[ord, ] Suggestion importance[1-10]: 7 __ Why: Using match directly can introduce NA indices and unintended subsetting; filtering out NAs as suggested is correct and safer while preserving order. It's a moderate robustness improvement rather than a critical bug fix.	Medium
General	Prevent potential zero-division in test Avoid expressions that could divide by zero in edge cases; if both totals are zero, this would yield NaN and make the test brittle. Add a safeguard in the expectation to handle zero denominators to keep the test robust. inst/tinytest/test_utils_groupcomparison.R [113] -expected_missing = 1 - (0 + 80) / (0 + 100) # 0.2 +denom <- (0 + 100) +expected_missing = if (denom == 0) NA_real_ else 1 - (0 + 80) / denom # 0.2 Suggestion importance[1-10]: 4 __ Why: The test line is valid for the given values and improves only edge-case robustness if denominators could be zero; it's reasonable but minor and not directly required by the current PR changes.	Low

[coderabbitai]

Actionable comments posted: 0

🧹 Nitpick comments (2)

R/utils_groupcomparison.R (1)

409-409: Style-only change looks good; consider making GROUP column reference explicit to avoid NSE pitfalls.

The switch from <- to = is fine and consistent with the surrounding file style. Minor robustness nit: referencing GROUP as a bare symbol outside a data.table j/by context relies on the current environment. Making the column reference explicit improves clarity and avoids accidental name masking.

Apply this minimal, safer refactor:

-        counts = counts[match(intersect(colnames(contrast_matrix), GROUP), GROUP), ]
+        idx = match(intersect(colnames(contrast_matrix), counts$GROUP), counts$GROUP)
+        counts = counts[idx, ]

inst/tinytest/test_utils_groupcomparison.R (1)

83-84: Optional: add a test asserting column/order stability for repeated runs.

You already validate ordering with permuted column names. Consider one more assertion that output$MissingPercentage aligns with rownames(contrast_matrix) when there are repeated GROUP rows pre-aggregation, to guard against future refactors in the counting step.

If useful, I can draft a small additional test case that duplicates GROUP rows before aggregation and checks the order and values.

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📥 Commits

Reviewing files that changed from the base of the PR and between 8c137ef and b6a6fee.

📒 Files selected for processing (2)

• R/utils_groupcomparison.R (1 hunks)
• inst/tinytest/test_utils_groupcomparison.R (4 hunks)

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• GitHub Check: build

🔇 Additional comments (2)

inst/tinytest/test_utils_groupcomparison.R (2)

3-6: LGTM on assignment operator normalization across tests.

All changes are purely stylistic (<- → =) and preserve test intent and calculations. The suite continues to exercise ordering, empty-group handling, and imputation logic appropriately.

Also applies to: 12-13, 22-25, 35-42, 43-46, 52-54, 61-63, 68-72, 78-84, 102-104, 110-114, 117-131, 134-141

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102-114: Edge-case assertion looks correct.

The “complete missing group” case correctly computes 0.2. No issues introduced by the assignment style change.