ChatSpatial

Tools · 18

• 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