New Features
scBaseCount database, covering Human, Mouse, Drosophila, and Zebrafish, with four species-specific marker gene set lists: human_gene_sets, mouse_gene_sets, fly_gene_sets, and zebrafish_gene_sets.Compute_Gene_PRC(): Computes PRC-AUC (Average Precision) and the no-skill baseline for a single gene against a user-defined cell group. Complements Compute_Gene_AUC_ROC() and is better suited to rare cell types under dropout and background contamination.Improvements
scBaseCount (Youngblut et al., 2026, doi:10.1016/j.cell.2026.08.025), plus README section 2.5.New Features
Plot_Group_Gene_Heatmap(): Generates publication-quality group-level mean Z-score expression heatmaps across custom cell groups (e.g., cell types or samples). Supports seamless integration with Seurat v4 and v5 objects.Improvements
Plot_Hierarchy_Proportion():
0–100%) for proportion heatmap values and updated legend titles to "Proportion (%)" / "Adjusted Proportion (%)"."Group (Cell Number)" axis header above Y-axis labels for improved readability.show_value_proportion parameter to overlay percentage numbers inside heatmap cells with dynamic text contrast.Plot_Group_Gene_Heatmap() using SlimR's internal paletteDiscrete() function (derived from ArchR) for column and row annotation bars.New Features
Plot_Hierarchy_Proportion() now accepts adjust_by_group = TRUE to scale per‑group proportions by relative cell counts, highlighting both within‑group composition and between‑group abundance differences. Heatmap row labels now also include the total cell count per group.CellTypist: pre‑computed markers for 399 cell types across 12 human organs, derived from the CellTypist organ atlas (Xu et al. 2023; Domínguez Conde et al. 2022). Markers were identified using the Scanpy workflow (Wilcoxon test, adjusted p‑value < 0.01, log2 fold‑change > 0), ranked by log fold‑change, and cut to the top 100 genes per cell type. See ?CellTypist and the package README for usage details.Improvements
Plot_Hierarchy_Proportion()."Markers_list_scIBD" dataset has been re‑calculated using the Scanpy sc.tl.rank_genes_groups function; its documentation and the README have been updated to reflect the new workflow.'paletteDiscrete' function failed to be called due to the absence of the '@export' attribute.New Features
Plot_Hierarchy_Proportion() creates a composite figure with a hierarchical cell‑type tree (bubbles and trapezoids) and an optional group proportion heatmap, handling partial sub‑type annotations and providing ArchR‑based or fallback colour palettes.Plot_Voronoi_diagram() generates a weighted Voronoi treemap of hierarchical cell‑type composition, with polygon area proportional to cell count and sub‑type colours matching the same palette logic as Plot_Hierarchy_Proportion.paletteDiscrete() function and ArchRPalettes dataset that faithfully reproduce the colour palettes (stallion, calm, kelly, etc.) from the ArchR package. The function supports natural sorting of category names, automatic interpolation when the number of categories exceeds the palette size, and reversal of colour order.Improvements
Plot_Hierarchy_Proportion function for hierarchical cell type visualisation.Plot_Voronoi_diagram with a detailed parameter guide and example code.New Features
Compute_Gene_AUC_ROC() computes single‑gene AUC and optionally plots the ROC curve, supporting raw and rank‑based scoring, expression truncation, and cell subsetting for robust marker evaluation.Improvements
README.md with Section 5.2 demonstrating the new function.New Features
Celltype_Compare(): a robust function for cross‑tabulating cell type labels and grouping variables between two single‑cell objects (e.g., Seurat). It automatically aligns cell barcodes using multiple normalisation strategies, returns count tables, column‑wise proportion tables, a dominant mapping, and a publication‑ready heatmap.Improvements
New Features
Improvements
.onAttach.library() calls from Celltype_Calculate() to comply with R packaging best practices. All dependencies are now accessed exclusively through NAMESPACE imports, preventing namespace pollution.geom_line(size = ...) with geom_line(linewidth = ...) in ROC curve plotting.Markers_filter_ScType() for filtering ScType markers by tissue type and cell name.ScType, ScType_raw, and ScType_table data objects.This release introduces a major new feature for fine-grained cell type identification alongside significant improvements to accuracy, performance, and usability.
New Feature: Per-Cell Annotation System
weighted (default), mean, and AUCell.Major Improvements to Per-Cell Annotation
min_score = "auto" threshold that scales with the number of cell types, preventing excessive "Unassigned" labels in large marker sets (e.g., 30+ types).min_confidence parameter for ratio-based filtering, providing more robust cell type discrimination than simple score differences.weighted scoring method with new marker specificity and IDF-like weights.AUCell method with adaptive n_top calculation and a combined binary/rank-weighted scoring strategy.Raw_score_matrix and a Parameters list for better reproducibility and debugging.Performance & Stability
RANN package for optional 10-100x faster k-NN computations in spatial smoothing.compute_adaptive_parameters().Testing & Documentation
Celltype_Calculate() to use individual gene AUCs for more robust predictions.Parameter_Calculate() for better model generalization.Parameter_Calculate() to include threshold parameter prediction.New Features
Improvements
has_colnames parameter to Read_excel_markers() to support reading Excel files without column headers.New Features
Improvements
Markers_list_scIBD database.Read_seurat_markers() for outputs from the presto package.Celltype_Verification().New Features
Celltype_Verification() function for generating validation dot plots.colour_low, colour_high) for all plotting functions.Improvements
Read_seurat_markers() with better compatibility for FindMarkers results from the presto package.Bug Fixes
New Features
Celltype_Calculate() function.Improvements
Bug Fixes
New Features
Celltype_Calculate() function for automated cluster scoring.Celltype_Annotation() function for an end-to-end annotation workflow.Improvements
Bug Fixes
Celltype_annotation_Heatmap() function.calculate_probability().Celltype_annotation_Heatmap() to use the new calculate_probability() function.Celltype_annotation_Bar() to Celltype_annotation_Box() and improved its visualization output.