Devel

[EmanuelSoda]

Summary by Sourcery

Update plotting tests and z-score hit computation to be compatible with current ggplot2 and dplyr behavior, and adjust examples and tests accordingly.

Enhancements:

• Refine find_zscore_hit to use dplyr::reframe for counting barcodes per gene, aligning with modern dplyr semantics.

Documentation:

• Wrap the find_zscore_hit usage example in \dontrun{} to avoid execution during example checks.

Tests:

• Update visualization, mapped-reads, barcode, and MDS tests to assert ggplot outputs using ggplot2::is_ggplot()/inherits instead of direct class string comparisons.
• Comment out the robust z-score hit median test that no longer matches the updated implementation.

[sourcery-ai]

Reviewer's Guide

This PR modernizes ggplot-related tests, updates z-score hit computation to use dplyr::reframe instead of summarise, and comments out a fragile robust z-score test, while lightly adjusting documentation for find_zscore_hit.

Flow diagram for updated find_zscore_hit z-score hit computation

flowchart TD
    A["find_zscore_hit(table_treate_vs_control, number_barcode, metric)"] --> B{metric}
    B -- "median" --> C["Group rows by Gene"]
    C --> D["Filter rows with Zscore < median(Zscore)"]
    D --> E["dplyr::group_by(Gene)"]
    E --> F["dplyr::reframe(numberOfBarcode = n())"]
    F --> G["Filter genes with numberOfBarcode > number_barcode"]
    G --> H["Return filtered table (median-based hits)"]

    B -- "mean" --> I["Group rows by Gene"]
    I --> J["Filter rows with Zscore < mean(Zscore)"]
    J --> K["dplyr::group_by(Gene)"]
    K --> L["dplyr::reframe(numberOfBarcode = n())"]
    L --> M["Filter genes with numberOfBarcode > number_barcode"]
    M --> N["Return filtered table (mean-based hits)"]

Loading

File-Level Changes

Change	Details	Files
Modernize visualization and MDS tests to assert ggplot objects using ggplot2 helpers instead of raw class inspection.	Replace expectations like expect_equal(class(x)[1], "gg") or class(plot)[2] == "ggplot" with expect_true(ggplot2::is_ggplot(...)) or expect_true(inherits(..., "ggplot")) to check for ggplot outputs more robustly. Normalize plot variable naming by renaming local variables from p to plot where updated expectations reference the object. Apply these updates consistently across visualization tests (trend, boxplot/violin, barcode plots, z-score distribution, mapped reads, barcode lost, common hit) and MDS/variance plotting tests.	tests/testthat/test-visualization.R tests/testthat/test-MDS.R
Adjust find_zscore_hit implementation to use dplyr::reframe for counting barcodes per gene instead of summarise, and protect its example from running on CRAN/test environments.	Wrap the find_zscore_hit documentation example code in a \dontrun{} block so it is not executed during example runs. Replace dplyr::summarise(numberOfBarcode = n()) with dplyr::reframe(numberOfBarcode = n()) in the median-branch to compute barcode counts per gene while returning an ungrouped tibble. Replace dplyr::summarise(.data$numberOfBarcode) with dplyr::reframe(numberOfBarcode = n()) in the mean-branch, mirroring the new counting behavior and avoiding partial argument matching on summarise.	R/find_zscore_hit.R
Temporarily disable a robust z-score hit test that likely no longer matches the implementation or is unstable.	Comment out the entire find_robust_zscore_hit median test block to prevent it from running while keeping the code for future reference.	tests/testthat/test-statistics.R
Non-functional project metadata / vignette touch-ups (no concrete diff provided).	Update DESCRIPTION and Analysis_Example vignette, likely for housekeeping or compatibility, though no specific content changes are shown in the snippet.	DESCRIPTION vignettes/Analysis_Example.Rmd

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[sourcery-ai]

Hey - I've left some high level feedback:

• In find_zscore_hit(), the switch from summarise() to reframe() changes the required dplyr version and grouping behavior; if the intention is to keep the same grouped output structure as before, consider explicitly checking/setting grouping or stick with summarise() for compatibility.
• The find_robust_zscore_hit median test in test-statistics.R is now fully commented out; if it is intentionally deprecated it may be clearer to remove it entirely or add a brief comment explaining why it is disabled.
• The tests now mix ggplot2::is_ggplot() and inherits(..., "ggplot") for plot checks; consider standardizing on one approach across the test suite for consistency.

Prompt for AI Agents

Please address the comments from this code review:

## Overall Comments
- In `find_zscore_hit()`, the switch from `summarise()` to `reframe()` changes the required dplyr version and grouping behavior; if the intention is to keep the same grouped output structure as before, consider explicitly checking/setting grouping or stick with `summarise()` for compatibility.
- The `find_robust_zscore_hit median` test in `test-statistics.R` is now fully commented out; if it is intentionally deprecated it may be clearer to remove it entirely or add a brief comment explaining why it is disabled.
- The tests now mix `ggplot2::is_ggplot()` and `inherits(..., "ggplot")` for plot checks; consider standardizing on one approach across the test suite for consistency.

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