Package index

All functions

applyQCfilter()

Subset a Seurat object by QC status (Seurat v5-safe)

apply_tuned_clustering()

Apply chosen k/res to an object (returns updated object)

auto_annotate()

Auto-annotate cell types (multi-backend wrapper)

calcQCmetrics()

Calculate QC metrics (UMIs, genes, mito%, MALAT1, stress; optional splicing metrics) Computes nCount/nFeature, pctMT, MALAT1 fraction, stress_score (case-insensitive SYMBOL match), and optional splicing metrics from same object layers or external Seurat objects. Compatible with Seurat v5 layers and v4 slots. Returns a data.frame and (if add_to_meta=TRUE) writes *_QC fields into obj@meta.data (no regression in field names).

default_stress_genes()

Default stress genes

flagLowQuality()

Flag low-quality cells

generic_signatures()

Generic, cross-tissue marker signatures (broad/extended)

list_panglao_tissues()

List the tissue names supported by the PanglaoDB marker database

prep_flagged_ranks()

Prepare ranked gene stats for dropped vs kept (logCPM mean diff)

qc_featuremaps()

Make & save UMAP featuremaps for QC metrics

removed_cells_analysis()

Removed cells clustering + enrichment (used by report)

render_qc_report()

Render a pretty HTML QC report

rescue_by_coherence()

Rescue borderline/removed cells by cluster coherence

run_enrichment()

Hallmark enrichment (ORA + GSEA) for dropped cells

run_qc_pipeline()

High-level wrapper that computes QC metrics, flags low-quality cells, (optionally) detects doublets and performs lightweight annotation, and renders an HTML report.

scq_plot_auto_confidence()

FeaturePlot-like map of auto-annotation confidence

toy_seu

toy_seu

tune_clustering()

Grid-search to preserve small clusters (k.param & resolution)