Comprehensive Metric Measurement Capacity Guidance Across All Interfaces:
End-to-End Analytical Workflow R Script Generators:
Inbuilt and Standalone Shiny Studio Ecosystem Alignment:
launch_scSimEval_app()) and the standalone deployment repository (scSimEval_shiny) to complete feature parity, including the four-mode Data Hub, confirmation buttons, app-wide loading indicators, and HPC batch execution script generators.Multi-Dataset Options & Standalone Reproducible R Scripts Across All Visualizations:
Dataset 1, Dataset 2, ..., Dataset N) with live active dataset badge synchronization.download_*_r_script) buttons to all 8 visualization subpanels and the Comparative Bubble Matrix. These generate 100% self-contained, reproducible R scripts with embedded benchmark data, user choices, and publication-ready ggplot2 code that can be executed independently outside of Shiny.Standardization to MiB for Peak RAM & Dual-Value Reporting in Master Benchmark Scores Table:
Score_Raw in native statistical and physical units: KS distance, runtime in seconds, peak RAM in MiB, Chi-Square values, etc.) alongside direction-aware normalized scores (Score in $[0, 1]$ where 1.0 represents best performance), equipped with per-column dropdown filtering.Modernized Help & Getting Started Tab and Ecosystem-Wide Documentation Alignment:
example_scrna, example_scatac, example_multiomics) and the rich pre-computed multi-dataset benchmark suite bundled in the Shiny application.Multi-Dataset Benchmarking Study Support (e.g., 16 Datasets × 6 Simulators):
benchmark_simulation_suite(): high-performance R function engineered for beginner users and high-throughput HPC clusters with automatic sparse matrix coercion (dgCMatrix), proactive garbage collection (gc()) per dataset to prevent RAM accumulation, and multi-threading.granular_benchmark_table) and a cross-dataset averaged summary table (benchmark_summary_table).Cross-Dataset Averaged Comparative Bubble Matrix:
plot_benchmark_bubble_matrix() and Shiny Studio Tab 4 (Comparative Bubble Matrix), multi-dataset evaluations automatically average fidelity scores across all evaluated datasets for each simulator.Streamlined Data Hub Ingestion (Four Canonical Modes):
Minimalist & Streamlined Shiny Studio Interface:
Refined Multiomics Scope & Natural Language:
Methodology Guide & Normalization Pipeline:
Package & Visualization Synchronization:
compute_dataset_embeddings(), plot_dataset_embeddings(), compute_embedding_quality_metrics()).Example Metadata Inputs & Data Format Documentation:
example_cell_types and example_batch_info matching the package's benchmark reference matrices (example_scrna).example_cell_types.csv, example_batch_annotations.csv) in Data Hub (Modes 2 & 3) and Help & Getting Started (Section 5) of scSimEval Studio.read_uploaded_labels() to automatically parse both 1-column vectors and standard 2-column tables (Cell_ID, Cell_Type or Batch) exported from Seurat and SingleCellExperiment.compute_method_leaderboard() & .ingest_bubble_data() Robustness:
Method = "Simulation" and Category = "Uncategorized" when evaluating single simulation accuracy results (evaluate_simulation_accuracy()) or pre-formed benchmark data frames lacking explicit method labels.R CMD check example failure in man/compute_method_leaderboard.Rd.Expanded Upload Size Limit (10 GB):
shiny.maxRequestSize from 500 MB to 10 GB (10 * 1024^3 bytes) in inst/shiny/scSimEvalApp/app.R to accommodate large-scale single-cell and single-nucleus multiomics count matrices.maxRequestSize argument to launch_scSimEval_app() in R/11_shiny_app.R (defaulting to 10 GB).Organism-Agnostic Metric Harmonization:
calc_cell_cycle_phase_fidelity() which was reliant on species-specific cell-cycle phase definitions and marker genes (primarily human and mouse). All 62 core evaluation metrics across the 8 categories are verified to operate purely on mathematical, distributional, and machine-learning properties of single-cell matrices without species or organism-specific priors, guaranteeing universal applicability to plant (e.g. soybean, rice, Arabidopsis) and animal datasets alike.Dependency & Package Best Practices:
irlba to Suggests: in DESCRIPTION to properly declare conditional SVD acceleration in compute_dataset_embeddings().set.seed() invocation with RNG-safe execution that preserves and restores .Random.seed on function exit in accordance with Bioconductor guidelines.eval = FALSE in vignettes/shiny-app.Rmd to satisfy Bioconductor vignette check requirements.Paired, Unpaired & Mosaic Multiomics Framework:
pairing = c("paired", "unpaired") parameter (with is_paired alias) to evaluate_multiomics_accuracy() and evaluate_multiple_datasets().Sub-panel 8: Cell Embeddings (UMAP, t-SNE, PCA) & Quality Metrics:
compute_dataset_embeddings(), plot_dataset_embeddings(), and compute_embedding_quality_metrics().Comprehensive All-in-One Benchmark Archive (.zip) & Export Suite:
download_complete_zip) in Shiny Studio Tab 5 ("Download Results") to deliver all quantitative results, spreadsheets, reports, and figures in an organized hierarchy..xlsx), CSV (.csv), tab-delimited text (.txt), and native R object (.rds) formats in both root and metrics/ subfolders.method_rankings_leaderboard (.csv & .txt) and dataset_properties_summary (.csv & .txt).scSimEval_all_plots_report.pdf).figures/grouped/: Both 600 DPI publication-grade JPEGs and vectorized PDFs for comparative bubble matrix, overall evaluation summary, scalability benchmark, metric boxplots by category, performance heatmap, PCA simulator ordination, MDS metric space, comparative distribution QC, and cell embeddings comparison grid.figures/individual/: Individual publication-grade barplots for every evaluated metric (metric_bar_<MetricName>.jpeg & .pdf) and simulator-specific 1-to-1 comparison cell embeddings against empirical reference (cell_embeddings_compare_<SimulatorName>.jpeg & .pdf).Documentation, Search & Site Integration:
vignettes/shiny-app.Rmd documenting all 6 navigation tabs, 8 visualization panels, UI controls, export options, and an R-API cross-reference table.Dedicated Individual Figure Export (Shiny Tab 5 - Card 4):
.pdf) or ultra-high-resolution 600 DPI JPEG (.jpeg).Expanded Embeddings in Complete Benchmark Archive (download_complete_zip):
.zip bundle to systematically generate and organize cell embedding figures for all three supported dimensionality reduction techniques (UMAP, t-SNE, and PCA) in figures/grouped/ (09_cell_embeddings_umap_grid, 10_cell_embeddings_tsne_grid, 11_cell_embeddings_pca_grid).figures/individual/.Documentation & Vignette Synchronization:
vignettes/shiny-app.Rmd to document the new Card 4 export controls and the expanded zip bundle directory structure.plot_metric_pca() and plot_metric_mds() — category = "all" support:
category = "all" or NULL now correctly retains all metrics across all categories without filtering out rows.inst/shiny/scSimEvalApp/app.R to ensure seamless execution across any R environment without requiring package re-installation.Error in x[clustering == i, ] : (subscript) logical subscript too long): corrected all roxygen @examples
blocks in the clustering/batch/DE/trajectory/multiomics metric functions so
cluster labels align with matrix dimensions and all required arguments are
supplied. All examples now pass R CMD check.calc_expected_mi, which errored
in an installed-namespace context ("could not find function").\figure widths now declared in pixels, explicit
@title tags for distribution metrics, ASCII-only documentation text, and
regenerated man/ pages.sessionInfo() blocks to every
vignette as required by BiocCheck.DESCRIPTION, README.md, vignettes/demo-multiomics.Rmd, and
vignettes/scSimEval-workflow.Rmd to reflect these distinctions.^doc$ and ^inst/doc$
from .Rbuildignore so that pre-rendered vignette HTML files are correctly
included in the source tarball and R CMD INSTALL --html succeeds.docs/ folder by removing scratch files (git_help.Rmd),
redundant source Markdown files, and the empty tutorials/ directory.launch_scSimEval_app()) for real-time benchmark exploration, custom data upload, and 600 DPI publication exports.