docs(vignette): Add ccrcc dataset and ID conversion to vignettes

[tonywu1999]

PR Type

Documentation, Enhancement

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Description

• Updated vignette to include CCRCC dataset and ID conversion.

• Enhanced annotateProteinInfoFromIndra function for better ID handling.

• Improved examples for ID conversion and subnetwork queries.

• Added references to external datasets and tools.

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Changes walkthrough 📝

	Relevant files
Enhancement	annotateProteinInfoFromIndra.R Improved handling of `Protein` ID data type                            R/annotateProteinInfoFromIndra.R Modified .populateUniprotIdsInDataFrame to cast Protein to character. Ensures compatibility with different data types for Protein. +1/-1
Documentation	MSstatsBioNet.Rmd Updated vignette with CCRCC dataset and ID conversion        vignettes/MSstatsBioNet.Rmd Added CCRCC dataset example with reference to external paper. Updated ID conversion example using annotateProteinInfoFromIndra. Enhanced subnetwork query example with additional outputs. Replaced outdated examples with streamlined workflows. +23/-31

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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 added line df$UniprotId <- as.character(df$Protein) in the if (proteinIdType == "Uniprot") block may introduce unintended behavior if df$Protein contains non-character data types. Ensure that this conversion is necessary and does not lead to data corruption or loss. df$UniprotId <- as.character(df$Protein) Dataset Reference Clarity The new dataset reference in the vignette points to a specific paper and file path. Ensure that the dataset is accessible and the reference is clear for users to replicate the example without issues. We will be taking a subset of the dataset found in this [paper](https://pmc.ncbi.nlm.nih.gov/articles/PMC7331093/). ```{r} input = data.table::fread(system.file( "extdata/msstats.csv", package = "MSstatsBioNet" )) </details> <details><summary><a href='https://github.com/Vitek-Lab/MSstatsBioNet/pull/35/files#diff-ea524a7e9f2f63335edd3c785c469e00078c9aacf6bfd5c2ff95da29a998a607R109-R111'><strong>Subnetwork Query Example</strong></a> The updated example for `getSubnetworkFromIndra` introduces a `pvalueCutoff` parameter. Verify that this parameter is well-documented and its behavior is clear to users.</summary> ```txt subnetwork <- getSubnetworkFromIndra(annotated_df, pvalueCutoff = 0.05) head(subnetwork$nodes) head(subnetwork$edges)

[github-actions]

PR Code Suggestions ✨

Explore these optional code suggestions:

Category	Suggestion	Score
General	Add error handling for file reading Add error handling for the data.table::fread function to ensure that the file path is valid and the file exists, preventing runtime errors. vignettes/MSstatsBioNet.Rmd [45-48] -input = data.table::fread(system.file( - "extdata/msstats.csv", - package = "MSstatsBioNet" -)) +input = tryCatch({ + data.table::fread(system.file( + "extdata/msstats.csv", + package = "MSstatsBioNet" + )) +}, error = function(e) { + stop("Error reading input file: ", e$message) +}) Suggestion importance[1-10]: 8 Why: Adding error handling for file reading is a significant improvement, as it prevents runtime errors and provides meaningful feedback to the user in case of issues. This enhances the robustness of the code.	8
	Validate parameter range for robustness Add a check to ensure that the pvalueCutoff parameter in getSubnetworkFromIndra is within a valid range (e.g., between 0 and 1) to avoid unexpected behavior. vignettes/MSstatsBioNet.Rmd [109] +if (pvalueCutoff < 0 || pvalueCutoff > 1) { + stop("pvalueCutoff must be between 0 and 1.") +} subnetwork <- getSubnetworkFromIndra(annotated_df, pvalueCutoff = 0.05) Suggestion importance[1-10]: 6 Why: Adding a check for the pvalueCutoff parameter range improves the robustness of the code by ensuring valid input. However, the suggestion does not account for how pvalueCutoff is defined or passed in the current context, slightly reducing its impact.	6
Possible issue	Validate input structure for function Validate the structure of model$ComparisonResult before passing it to annotateProteinInfoFromIndra to ensure it contains the required columns and data. vignettes/MSstatsBioNet.Rmd [98] +if (!all(c("Protein", "OtherRequiredColumn") %in% colnames(model$ComparisonResult))) { + stop("model$ComparisonResult does not have the required structure.") +} annotated_df = annotateProteinInfoFromIndra(model$ComparisonResult, "Uniprot") Suggestion importance[1-10]: 7 Why: Validating the structure of model$ComparisonResult ensures that the function receives the expected input, preventing potential runtime errors. This is a useful addition for improving code reliability.	7

[codecov-commenter]

Codecov Report

All modified and coverable lines are covered by tests ✅

Project coverage is 82.79%. Comparing base (fc732dd) to head (afe1acd).

Additional details and impacted files

@@           Coverage Diff           @@
##            devel      #35   +/-   ##
=======================================
  Coverage   82.79%   82.79%           
=======================================
  Files           7        7           
  Lines         465      465           
=======================================
  Hits          385      385           
  Misses         80       80           

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[tonywu1999]

#25

[tonywu1999]

Bioconductor/Contributions#3500