feat(getSubnetworkFromIndra): Add additional filters

[tonywu1999]

PR Type

Enhancement, Tests

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Description

• Added new filtering parameters to getSubnetworkFromIndra function.

• Implemented filtering logic for statement types, paper count, and evidence count.

• Updated documentation to reflect new parameters and functionality.

• Enhanced unit tests to validate new filtering features.

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Changes walkthrough 📝

	Relevant files
Enhancement	getSubnetworkFromIndra.R Add filtering parameters and logic to main function            R/getSubnetworkFromIndra.R Added new parameters for filtering: statement_types, paper_count_cutoff, and evidence_count_cutoff. Updated function logic to apply new filters to INDRA response and edges. Adjusted node construction to consider filtered edges. +14/-2    utils_getSubnetworkFromIndra.R Add utility functions for filtering INDRA response and edges R/utils_getSubnetworkFromIndra.R Introduced .filterIndraResponse to filter INDRA statements by type and evidence count. Added .filterEdgesDataFrame to filter edges by paper count. Updated edge metadata to include paper count. +41/-1
Documentation	getSubnetworkFromIndra.Rd Update documentation for new filtering parameters                man/getSubnetworkFromIndra.Rd Updated documentation to include descriptions for new parameters. Adjusted usage examples to reflect new filtering options. +16/-1
Tests	test-getSubnetworkFromIndra.R Update and enhance tests for filtering features                    tests/testthat/test-getSubnetworkFromIndra.R Modified tests to include statement_types parameter in function calls. Adjusted expected results to validate new filtering logic. Added TODO for p-value filtering test adjustments. +5/-4

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[github-actions]

PR Reviewer Guide 🔍

Here are some key observations to aid the review process:

⏱️ Estimated effort to review: 4 🔵🔵🔵🔵⚪

🧪 PR contains tests

🔒 No security concerns identified

⚡ Recommended focus areas for review Parameter Default Values The new parameters statement_types, paper_count_cutoff, and evidence_count_cutoff have default values. Ensure these defaults align with expected use cases and do not unintentionally exclude relevant data. #' @param statement_types list of interaction types to filter on. Equivalent to #' statement type in INDRA. Default is c("IncreaseAmount", "DecreaseAmount"). #' @param paper_count_cutoff number of papers to filter on. Default is 1. #' @param evidence_count_cutoff number of evidence to filter on for each #' paper. E.g. A paper may have 5 sentences describing the same interaction vs 1 #' sentence. Default is 1. Filtering Logic The filtering logic in .filterIndraResponse and .filterEdgesDataFrame should be validated to ensure it correctly handles edge cases, such as empty responses or unexpected data formats. .filterIndraResponse <- function(res, interaction_types, evidence_count_cutoff) { filtered_response = Filter( function(statement) statement$data$stmt_type %in% interaction_types, res) filtered_response = Filter( function(statement) statement$data$evidence_count >= evidence_count_cutoff, filtered_response ) return(filtered_response) } Test Coverage The updated tests include new parameters, but additional tests should be added to cover edge cases for the filtering logic, such as invalid parameter values or empty datasets. suppressWarnings(subnetwork <- getSubnetworkFromIndra(input, statement_types = c("Activation", "Phosphorylation"))) expect_equal(nrow(subnetwork$nodes), 2) expect_equal(nrow(subnetwork$edges), 1) }) test_that("getSubnetworkFromIndra with pvalue filter works correctly", { input <- data.table::fread( system.file("extdata/groupComparisonModel.csv", package = "MSstatsBioNet") ) local_mocked_bindings(.callIndraCogexApi = function(x) { return(readRDS(system.file("extdata/indraResponse.rds", package = "MSstatsBioNet"))) }) suppressWarnings( subnetwork <- getSubnetworkFromIndra(input, pvalueCutoff = 0.45, statement_types = c("Activation", "Phosphorylation")) ) # TODO: Adjust test file to reflect p-value filtering expect_equal(nrow(subnetwork$nodes), 2) expect_equal(nrow(subnetwork$edges), 1)

[github-actions]

PR Code Suggestions ✨

Explore these optional code suggestions:

Category	Suggestion	Score
Possible issue	Validate field existence and type Ensure that the statement$data$evidence_count field exists and is numeric before applying the filter in .filterIndraResponse to avoid runtime errors if the field is missing or improperly formatted. R/utils_getSubnetworkFromIndra.R [50-52] filtered_response = Filter( - function(statement) statement$data$evidence_count >= evidence_count_cutoff, + function(statement) is.numeric(statement$data$evidence_count) && statement$data$evidence_count >= evidence_count_cutoff, filtered_response ) Suggestion importance[1-10]: 9 Why: This suggestion ensures that the evidence_count field exists and is numeric before applying the filter, which is crucial to prevent runtime errors if the field is missing or improperly formatted. It directly enhances the robustness of the code.	9
	Validate stmt_type field existence Add a check to ensure that statement$data$stmt_type is not NULL or missing before applying the filter in .filterIndraResponse to prevent potential errors. R/utils_getSubnetworkFromIndra.R [48-49] filtered_response = Filter( - function(statement) statement$data$stmt_type %in% interaction_types, + function(statement) !is.null(statement$data$stmt_type) && statement$data$stmt_type %in% interaction_types, res) Suggestion importance[1-10]: 9 Why: Adding a check for the existence of stmt_type ensures that the filter does not fail due to missing or null values, improving the reliability of the function and preventing potential runtime errors.	9
	Validate paper_count initialization Ensure that the paperCount field is initialized and numeric in .constructEdgesDataFrame to avoid errors when filtering or aggregating data. R/utils_getSubnetworkFromIndra.R [134] -edge$data$paper_count <- 1 +edge$data$paper_count <- ifelse(is.numeric(edge$data$paper_count), edge$data$paper_count, 1) Suggestion importance[1-10]: 8 Why: This suggestion ensures that the paper_count field is properly initialized and numeric, which is important for avoiding errors during filtering or aggregation. It improves the robustness of the code.	8
General	Add tests for new parameters Update the test cases to include assertions for the new paper_count_cutoff and evidence_count_cutoff parameters to ensure they are correctly applied and tested. tests/testthat/test-getSubnetworkFromIndra.R [8-9] -suppressWarnings(subnetwork <- getSubnetworkFromIndra(input, statement_types = c("Activation", "Phosphorylation"))) +suppressWarnings(subnetwork <- getSubnetworkFromIndra(input, statement_types = c("Activation", "Phosphorylation"), paper_count_cutoff = 2, evidence_count_cutoff = 3)) Suggestion importance[1-10]: 7 Why: Updating the test cases to include assertions for the new parameters ensures that the added functionality is properly tested. While this is a good enhancement, it is not critical as the existing tests already cover the function's behavior to some extent.	7

[codecov-commenter]

Codecov Report

All modified and coverable lines are covered by tests ✅

Project coverage is 87.41%. Comparing base (dd20f47) to head (80b393f).

Additional details and impacted files

@@            Coverage Diff             @@
##            devel      #30      +/-   ##
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+ Coverage   86.73%   87.41%   +0.68%     
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  Files           7        7              
  Lines         407      429      +22     
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+ Hits          353      375      +22     
  Misses         54       54              

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