load_data
Load spatial transcriptomics data from various platforms (Visium, Xenium, Slide-seq v2, MERFISH, seqFISH)
preprocess
Quality control, normalization, HVG selection, PCA, and neighbor graph construction
spatial_plot
Generate spatial plots of gene expression or metadata
embedding_plot
Generate embedding plots (e.g., UMAP, t-SNE) colored by gene expression or metadata
gene_expression_overlay
Overlay gene expression on spatial coordinates
spatial_domain
Identify spatial domains using methods like SpaGCN, STAGATE, GraphST, BANKSY, Leiden, or Louvain
deconvolution
Perform cell-type deconvolution using FlashDeconv, Cell2location, RCTD, DestVI, Stereoscope, SPOTlight, Tangram, or CARD
cell_cell_communication
Analyze cell-cell communication with LIANA+, CellPhoneDB, CellChat, or FastCCC
cell_type_annotation
Annotate cell types using Tangram, scANVI, CellAssign, mLLMCelltype, scType, or SingleR
differential_expression
Perform differential expression analysis with Wilcoxon, t-test, Logistic Regression, or pyDESeq2
trajectory_inference
Infer developmental trajectories using CellRank, Palantir, or DPT
rna_velocity
Estimate RNA velocity with scVelo or VeloVI
spatial_statistics
Compute spatial statistics including Moran's I, Geary's C, Ripley's K, co-occurrence, neighborhood enrichment, and more
enrichment_analysis
Perform enrichment analysis with GSEA, ORA, Enrichr, ssGSEA, or Spatial EnrichMap
spatially_variable_genes
Identify spatially variable genes using SpatialDE, SPARK-X, or FlashS
multi_sample_integration
Integrate multiple samples with Harmony, BBKNN, Scanorama, or scVI
cnv_analysis
Analyze copy number variations with InferCNVPy or Numbat
spatial_registration
Register spatial data across sections using PASTE or STalign