refactor(getSubnetworkFromIndra): Create separate helper function to get correlation matrix

[tonywu1999]

PR Type

Enhancement

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Description

• Refactored correlation matrix computation into a separate helper function.

• Added a new internal function .getCorrelationMatrixFromProteinLevelData.

• Removed redundant imports and streamlined dependencies.

• Updated the NAMESPACE file to reflect changes in imports.

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Changes walkthrough 📝

	Relevant files
Configuration changes	NAMESPACE Removed unused import and updated dependencies                      NAMESPACE Removed unused import quantification from MSstats. Updated NAMESPACE to reflect streamlined dependencies. +0/-1
Enhancement	utils_getSubnetworkFromIndra.R Refactored correlation matrix computation logic                    R/utils_getSubnetworkFromIndra.R Extracted correlation matrix computation into .getCorrelationMatrixFromProteinLevelData. Removed inline correlation computation logic from .constructEdgesDataFrame. Added a new internal function .getCorrelationMatrixFromProteinLevelData. Removed redundant imports quantification and pivot_wider. +17/-8

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[github-actions]

PR Reviewer Guide 🔍

Here are some key observations to aid the review process:

⏱️ Estimated effort to review: 3 🔵🔵🔵⚪⚪

🧪 No relevant tests

🔒 No security concerns identified

⚡ Recommended focus areas for review Possible Issue The new function .getCorrelationMatrixFromProteinLevelData assumes that the column originalRUN will always exist in protein_level_data. If this column is missing, the function will throw an error. This should be validated or handled gracefully. #' Construct correlation matrix from MSstats #' @param protein_level_data output of dataProcess #' @importFrom tidyr pivot_wider #' @return correlations matrix #' @keywords internal #' @noRd .getCorrelationMatrixFromProteinLevelData <- function(protein_level_data) { wide_data <- pivot_wider(protein_level_data[,c("Protein", "LogIntensities", "originalRUN")], names_from = Protein, values_from = LogIntensities) wide_data <- wide_data[, -which(names(wide_data) == "originalRUN")] if (any(colSums(!is.na(wide_data)) == 0)) { warning("protein_level_data contains proteins with all missing values, unable to calculate correlations for those proteins.") } correlations <- cor(wide_data, use = "pairwise.complete.obs") return(correlations) } Edge Case Handling The cor function in .getCorrelationMatrixFromProteinLevelData uses pairwise.complete.obs. This may lead to unexpected results if there are many missing values. Consider documenting or validating this behavior. #' Construct correlation matrix from MSstats #' @param protein_level_data output of dataProcess #' @importFrom tidyr pivot_wider #' @return correlations matrix #' @keywords internal #' @noRd .getCorrelationMatrixFromProteinLevelData <- function(protein_level_data) { wide_data <- pivot_wider(protein_level_data[,c("Protein", "LogIntensities", "originalRUN")], names_from = Protein, values_from = LogIntensities) wide_data <- wide_data[, -which(names(wide_data) == "originalRUN")] if (any(colSums(!is.na(wide_data)) == 0)) { warning("protein_level_data contains proteins with all missing values, unable to calculate correlations for those proteins.") } correlations <- cor(wide_data, use = "pairwise.complete.obs") return(correlations) }

[github-actions]

PR Code Suggestions ✨

Explore these optional code suggestions:

Category	Suggestion	Score
Possible issue	Add validation for required columns Ensure that the pivot_wider function in .getCorrelationMatrixFromProteinLevelData handles cases where the protein_level_data input lacks the required columns ("Protein", "LogIntensities", "originalRUN") to prevent runtime errors. R/utils_getSubnetworkFromIndra.R [251] +if (!all(c("Protein", "LogIntensities", "originalRUN") %in% colnames(protein_level_data))) { + stop("protein_level_data must contain 'Protein', 'LogIntensities', and 'originalRUN' columns.") +} wide_data <- pivot_wider(protein_level_data[,c("Protein", "LogIntensities", "originalRUN")], names_from = Protein, values_from = LogIntensities) Suggestion importance[1-10]: 9 Why: The suggestion adds a critical validation step to ensure that the required columns are present in the input data before proceeding, which prevents runtime errors. This is highly relevant and improves the robustness of the function.	9
	Handle NULL correlations gracefully Ensure that the apply function used to assign correlations to edges in .constructEdgesDataFrame handles cases where correlations is NULL, to prevent runtime errors. R/utils_getSubnetworkFromIndra.R [194-199] -edges$correlation <- apply(edges, 1, function(edge) { - if (edge["source"] %in% rownames(correlations) && edge["target"] %in% colnames(correlations)) { - return(correlations[edge["source"], edge["target"]]) - } else { - return(NA) - } -}) +edges$correlation <- if (!is.null(correlations)) { + apply(edges, 1, function(edge) { + if (edge["source"] %in% rownames(correlations) && edge["target"] %in% colnames(correlations)) { + return(correlations[edge["source"], edge["target"]]) + } else { + return(NA) + } + }) +} else { + rep(NA, nrow(edges)) +} Suggestion importance[1-10]: 9 Why: The suggestion ensures that the function can handle cases where the correlation matrix is NULL, avoiding runtime errors and maintaining functionality. This is a critical improvement for robustness.	9
	Handle empty matrix after column removal Add a check to handle cases where the wide_data matrix becomes empty after removing the "originalRUN" column, to avoid errors in subsequent correlation calculations. R/utils_getSubnetworkFromIndra.R [252] wide_data <- wide_data[, -which(names(wide_data) == "originalRUN")] +if (ncol(wide_data) == 0) { + stop("wide_data is empty after removing 'originalRUN' column. Cannot calculate correlations.") +} Suggestion importance[1-10]: 8 Why: The suggestion addresses a potential issue where the matrix could become empty after removing a specific column, which would cause errors in subsequent operations. This is a valuable enhancement to ensure the function's stability.	8

[codecov-commenter]

Codecov Report

Attention: Patch coverage is 0% with 8 lines in your changes missing coverage. Please review.

Project coverage is 82.79%. Comparing base (d98b6ed) to head (59d2c3c).

Files with missing lines	Patch %	Lines
R/utils_getSubnetworkFromIndra.R	0.00%	8 Missing ⚠️

Additional details and impacted files

@@            Coverage Diff             @@
##            devel      #34      +/-   ##
==========================================
- Coverage   83.33%   82.79%   -0.54%     
==========================================
  Files           7        7              
  Lines         462      465       +3     
==========================================
  Hits          385      385              
- Misses         77       80       +3     

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