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This is due to the changes in MSstats that assumes heavy labels are references when applying equalizeMedians.
In the example dataset, it only had heavy peptides, and equalizeMedians was applied, which causes MSstats to crash. However, having only heavy peptides is an unrealistic scenario, especially for DIA.
Motivation and Context
The Bioconductor build was failing due to upstream changes in the MSstats package that treat heavy isotope labels as references when applying the equalizeMedians normalization function. The MSstatsShiny example DIA (Data Independent Acquisition) dataset contained only heavy peptides, which causes MSstats to crash when this function is applied. Since datasets containing only heavy peptides are unrealistic for DIA workflows, the solution was to modify the example dataset to include light peptides (standard unlabeled form) instead of exclusively heavy-labeled peptides. Additionally, the network visualization module was enhanced to support external API integration using the httr package.
Detailed Changes
Data modification: Updated data/example_dia_skyline.rda to use light isotope labels instead of heavy-only labels, resolving the incompatibility with MSstats' equalizeMedians function
Dependency management: Added httr to the package Imports in DESCRIPTION file to support HTTP requests
Namespace updates: Added imports to NAMESPACE for httr functions (POST, accept_json, content, content_type_json, status_code)
Module documentation: Updated roxygen documentation in R/module-visualize-network-server.R with @importFrom httr declarations for the five httr functions
Encoding fixes: Corrected UTF-8 encoding in help text of R/module-statmodel-server.R by replacing Unicode minus sign (−1) with ASCII hyphen (-1) in the comparison matrix UI description
Network visualization enhancement: Integrated httr API calls in the network visualization module to query the INDRA grounding service for protein name resolution via POST requests to https://grounding.indra.bio/ground
Unit Tests
Multiple test files are present in the test suite (e.g., tests/testthat/test-module-statmodel-server.R, tests/testthat/test_network_visualization.R), providing comprehensive coverage for module functionality. The test dataset in tests/testthat/data/dataset.csv contains entries with light isotope labels consistent with the example data modifications.
Coding Guidelines
All changes follow appropriate R/Shiny conventions including proper roxygen documentation for imports, correct module structure, and standard encoding declarations in DESCRIPTION.
The PR adds httr as a dependency to DESCRIPTION and NAMESPACE, imports related functions from httr and MSstatsBioNet for network visualization functionality, documents the httr imports in the visualizeNetworkServer module, and corrects a Unicode character to ASCII in UI help text.
Changes
Cohort / File(s)
Summary
Package Manifest DESCRIPTION, NAMESPACE
Added httr to package imports and declared new imports from httr (POST, content\_type\_json, accept\_json, content, status\_code) and MSstatsBioNet (deleteEdgeFromNetwork).
🐰 A rabbit hops through package imports with glee, httr arrives with functions to be, Network edges deleted, requests made right, Minor text tweaks bring characters in sight!
🚥 Pre-merge checks | ✅ 2 | ❌ 1
❌ Failed checks (1 inconclusive)
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Explanation
Resolution
Title check
❓ Inconclusive
The title 'Fix build' is vague and generic, providing no specific information about what aspect of the build is being fixed or what changes are made.
Consider a more descriptive title like 'Fix build by updating example dataset labels and adding httr dependency' to clearly communicate the main changes.
✅ Passed checks (2 passed)
Check name
Status
Explanation
Docstring Coverage
✅ Passed
No functions found in the changed files to evaluate docstring coverage. Skipping docstring coverage check.
Description Check
✅ Passed
Check skipped - CodeRabbit’s high-level summary is enabled.
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Build is failing: https://bioconductor.org/checkResults/3.23/bioc-LATEST/MSstatsShiny/nebbiolo1-checksrc.html
This is due to the changes in MSstats that assumes heavy labels are references when applying equalizeMedians.
In the example dataset, it only had heavy peptides, and equalizeMedians was applied, which causes MSstats to crash. However, having only heavy peptides is an unrealistic scenario, especially for DIA.
Motivation and Context
The Bioconductor build was failing due to upstream changes in the MSstats package that treat heavy isotope labels as references when applying the
equalizeMediansnormalization function. The MSstatsShiny example DIA (Data Independent Acquisition) dataset contained only heavy peptides, which causes MSstats to crash when this function is applied. Since datasets containing only heavy peptides are unrealistic for DIA workflows, the solution was to modify the example dataset to include light peptides (standard unlabeled form) instead of exclusively heavy-labeled peptides. Additionally, the network visualization module was enhanced to support external API integration using thehttrpackage.Detailed Changes
data/example_dia_skyline.rdato use light isotope labels instead of heavy-only labels, resolving the incompatibility with MSstats'equalizeMediansfunctionhttrto the packageImportsin DESCRIPTION file to support HTTP requestshttrfunctions (POST,accept_json,content,content_type_json,status_code)R/module-visualize-network-server.Rwith@importFrom httrdeclarations for the five httr functionsR/module-statmodel-server.Rby replacing Unicode minus sign (−1) with ASCII hyphen (-1) in the comparison matrix UI descriptionhttrAPI calls in the network visualization module to query the INDRA grounding service for protein name resolution via POST requests tohttps://grounding.indra.bio/groundUnit Tests
Multiple test files are present in the test suite (e.g.,
tests/testthat/test-module-statmodel-server.R,tests/testthat/test_network_visualization.R), providing comprehensive coverage for module functionality. The test dataset intests/testthat/data/dataset.csvcontains entries with light isotope labels consistent with the example data modifications.Coding Guidelines
All changes follow appropriate R/Shiny conventions including proper roxygen documentation for imports, correct module structure, and standard encoding declarations in DESCRIPTION.