adjust error handling for zero edges and handling of issue column

[tonywu1999]

Summary by CodeRabbit

• Bug Fixes
  • Improved handling of missing columns to prevent errors when filtering data.
  • Stricter error handling when no edges remain after filtering, ensuring clearer feedback for invalid input.

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PR Type

Bug fix

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Description

• Check for issue column before filter

• Filter only NA issues when present

• Stop with error if no edges remain

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File Walkthrough

	Relevant files
Error handling	utils_getSubnetworkFromIndra.R Issue check and strict edge-error handling                              R/utils_getSubnetworkFromIndra.R Wrap input$issue filter in column-existence check Change zero-edge warning to a stopping error +4/-2

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[coderabbitai]

Walkthrough

The edge filtering logic in the utility script was updated to check for the existence of the "issue" column before filtering out rows with missing values. Additionally, the script now raises an error rather than a warning if no edges remain after filtering, enforcing stricter failure handling.

Changes

File(s)	Change Summary
R/utils_getSubnetworkFromIndra.R	Added conditional check for "issue" column before filtering; changed warning to error on empty result

Estimated code review effort

🎯 1 (Trivial) | ⏱️ ~3 minutes

Poem

A hop and a skip through the code we go,
Now errors will stop us, not just say hello.
If "issue" is missing, we check with care,
No silent warnings—rabbits play fair!
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📜 Recent review details

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📥 Commits

Reviewing files that changed from the base of the PR and between 4fdc717 and 6678c78.

📒 Files selected for processing (1)

• R/utils_getSubnetworkFromIndra.R (2 hunks)

🔇 Additional comments (2)

R/utils_getSubnetworkFromIndra.R (2)

119-121: LGTM! Good defensive programming practice.

The conditional check prevents runtime errors when the "issue" column is absent from the input data, while preserving the existing filtering behavior when the column exists.

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300-300: Good change for data integrity, but note this is a breaking change.

Converting from warning to error when no edges remain is appropriate as it prevents downstream processing of empty datasets and forces users to address filtering issues. The error message provides clear guidance.

Note that this is a breaking change - existing code that previously continued with warnings will now fail.

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[github-actions]

PR Reviewer Guide 🔍

Here are some key observations to aid the review process:

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

🧪 No relevant tests

🔒 No security concerns identified

⚡ Recommended focus areas for review Filter Behavior Ensure that when the issue column is present and all rows are filtered out, the function handles the empty input appropriately or surfaces a clear error. if ("issue" %in% colnames(input)) { input <- input[is.na(input$issue), ] } Error Handling Consistency Verify that converting the warning to a stop in .filterEdgesDataFrame aligns with overall error-handling strategy and that callers properly catch or handle this error. if (nrow(edges) == 0) { stop("No edges remain after applying filters. Consider relaxing filters") } Test Coverage Add tests for cases with and without the issue column as well as for empty edge sets to cover the new filtering and error branches. if ("issue" %in% colnames(input)) { input <- input[is.na(input$issue), ] } # Combine filtered data with exempt proteins and remove duplicates if (!is.null(exempt_proteins) && nrow(exempt_proteins) > 0) { combined_input <- rbind(exempt_proteins, input) # Remove duplicates based on Protein column, keeping first occurrence input <- combined_input[!duplicated(combined_input$Protein), ] } input$Protein <- as.character(input$Protein) return(input) } #' Add additional metadata to an edge #' @param edge object representation of an INDRA statement #' @param input filtered groupComparison result #' @param source_namespace namespace of the source for evidence URL #' @return edge with additional metadata #' @keywords internal #' @noRd .addAdditionalMetadataToIndraEdge <- function(edge, input, source_namespace = "@HGNC") { edge$evidence_list <- paste( "https://db.indra.bio/statements/from_agents?subject=", edge$source_id, source_namespace, "&object=", edge$target_id, "@HGNC&format=html", sep = "" ) # Convert back to uniprot IDs if (source_namespace == "@HGNC") { matched_rows_source <- input[which(input$HgncId == edge$source_id), ] } matched_rows_target <- input[which(input$HgncId == edge$target_id), ] if ((source_namespace == "@HGNC" && nrow(matched_rows_source) != 1) || nrow(matched_rows_target) != 1) { stop(paste0( "INDRA Exception: Unexpected number of matches for the following HGNC IDs in the input data: ", edge$source_id, " or ", edge$target_id, ". Each ID must match exactly one entry in the input data, but 0 or multiple matches were found. Please check the input data for duplicates or missing entries." )) } if (source_namespace == "@HGNC") { edge$source_uniprot_id <- matched_rows_source$Protein } else { edge$source_uniprot_id <- edge$source_id } edge$target_uniprot_id <- matched_rows_target$Protein return(edge) } #' Collapse duplicate INDRA statements into a mapping of edge to metadata #' @param res INDRA response #' @param input filtered groupComparison result #' @importFrom r2r hashmap keys #' @return processed edge to metadata mapping #' @keywords internal #' @noRd .collapseDuplicateEdgesIntoEdgeToMetadataMapping <- function(res, input) { edgeToMetadataMapping <- hashmap() for (edge in res) { key <- paste(edge$source_id, edge$target_id, sep = "_") if (key %in% keys(edgeToMetadataMapping)) { edgeToMetadataMapping[[key]]$data$evidence_count <- edgeToMetadataMapping[[key]]$data$evidence_count + edge$data$evidence_count edgeToMetadataMapping[[key]]$data$stmt_type <- unique(c( edgeToMetadataMapping[[key]]$data$stmt_type, edge$data$stmt_type)) edgeToMetadataMapping[[key]]$data$stmt_type <- unique(c( edgeToMetadataMapping[[key]]$data$stmt_type, edge$data$stmt_type)) edgeToMetadataMapping[[key]]$data$paper_count <- edgeToMetadataMapping[[key]]$data$paper_count + 1 } else { edge <- .addAdditionalMetadataToIndraEdge(edge, input) edge$data$paper_count <- 1 edgeToMetadataMapping[[key]] <- edge } } for (key in keys(edgeToMetadataMapping)) { edgeToMetadataMapping[[key]]$data$stmt_type <- paste(unique(edgeToMetadataMapping[[key]]$data$stmt_type), collapse = ", ") } return(edgeToMetadataMapping) } #' Construct edges data.frame from INDRA response #' @param res INDRA response #' @param input filtered groupComparison result #' @param protein_level_data output of dataProcess #' @importFrom r2r query keys #' @return edge data.frame #' @keywords internal #' @noRd .constructEdgesDataFrame <- function(res, input, protein_level_data) { res <- .collapseDuplicateEdgesIntoEdgeToMetadataMapping(res, input) edges <- data.frame( source = vapply(keys(res), function(x) { query(res, x)$source_uniprot_id }, ""), target = vapply(keys(res), function(x) { query(res, x)$target_uniprot_id }, ""), interaction = vapply(keys(res), function(x) { query(res, x)$data$stmt_type }, ""), evidenceCount = vapply(keys(res), function(x) { query(res, x)$data$evidence_count }, 1), paperCount = vapply(keys(res), function(x) { query(res, x)$data$paper_count }, 1), evidenceLink = vapply(keys(res), function(x) { query(res, x)$evidence_list }, ""), sourceCounts = vapply(keys(res), function(x) { query(res, x)$data$source_counts }, ""), stringsAsFactors = FALSE ) # add correlation - maybe create a separate function if (!is.null(protein_level_data)) { protein_level_data <- protein_level_data[ protein_level_data$Protein %in% edges$source | protein_level_data$Protein %in% edges$target, ] correlations <- .getCorrelationMatrixFromProteinLevelData(protein_level_data) edges$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) } }) } return(edges) } #' Construct nodes data.frame from groupComparison output #' @param input filtered groupComparison result #' @param edges edges data frame #' @return nodes data.frame #' @keywords internal #' @noRd .constructNodesDataFrame <- function(input, edges) { nodes <- data.frame( id = input$Protein, logFC = input$log2FC, pvalue = input$adj.pvalue, hgncName = if ("HgncName" %in% colnames(input) && is.character(input$HgncName)) input$HgncName else NA, stringsAsFactors = FALSE ) nodes <- nodes[which(nodes$id %in% edges$source | nodes$id %in% edges$target),] return(nodes) } #' Filter Edges Data Frame #' @param edges response from INDRA #' @param paper_count_cutoff cutoff for number of papers #' @param correlation_cutoff if protein_level_abundance is not NULL, apply a #' cutoff for edges with correlation less than a specified cutoff. #' @return filtered edges data frame #' @keywords internal #' @noRd .filterEdgesDataFrame <- function(edges, paper_count_cutoff, correlation_cutoff) { edges <- edges[which(edges$paperCount >= paper_count_cutoff), ] if ("correlation" %in% colnames(edges)) { edges <- edges[which(abs(edges$correlation) >= correlation_cutoff), ] } if (nrow(edges) == 0) { stop("No edges remain after applying filters. Consider relaxing filters") }

[github-actions]

PR Code Suggestions ✨

Explore these optional code suggestions:

Category	Suggestion	Impact
General	Warn when issue column is missing If the issue column is required for downstream logic, silently skipping the filter when it’s missing may hide data issues. Consider emitting a warning when the column is absent to alert users. R/utils_getSubnetworkFromIndra.R [119-121] if ("issue" %in% colnames(input)) { input <- input[is.na(input$issue), ] +} else { + warning("`issue` column not found; no issue filtering applied") } Suggestion importance[1-10]: 5 __ Why: Emitting a warning when the issue column is absent improves user awareness of skipped filtering without altering core logic.	Low
	Suppress call stack in error By default stop() shows the call stack which can clutter error output; adding call. = FALSE makes the message cleaner. R/utils_getSubnetworkFromIndra.R [300] -stop("No edges remain after applying filters. Consider relaxing filters") +stop("No edges remain after applying filters. Consider relaxing filters", call. = FALSE) Suggestion importance[1-10]: 4 __ Why: Adding call. = FALSE cleans up the error message output, a minor stylistic enhancement that doesn’t affect the function’s behavior.	Low

[codecov-commenter]

Codecov Report

Attention: Patch coverage is 66.66667% with 1 line in your changes missing coverage. Please review.

Project coverage is 65.29%. Comparing base (4fdc717) to head (6678c78).

Files with missing lines	Patch %	Lines
R/utils_getSubnetworkFromIndra.R	66.66%	1 Missing ⚠️

Additional details and impacted files

@@            Coverage Diff             @@
##            devel      #50      +/-   ##
==========================================
+ Coverage   65.23%   65.29%   +0.05%     
==========================================
  Files           7        7              
  Lines         607      608       +1     
==========================================
+ Hits          396      397       +1     
  Misses        211      211              

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