Package index • spatialLIBD

All functions
`add10xVisiumAnalysis()`	Add analysis data from a 10x Genomics Visium experiment to a SPE object
`add_images()`	Add non-standard images with the same dimensions as current ones
`add_key()`	Create a unique spot identifier
`add_qc_metrics()`	Quality Control for Spatial Data
`annotate_registered_clusters()`	Annotated spatially-registered clusters
`check_modeling_results()`	Check input modeling_results
`check_sce()`	Check input sce
`check_sce_layer()`	Check input sce_layer
`check_spe()`	Check input spe
`cluster_export()`	Export a column with cluster results
`cluster_import()`	Import cluster results
`enough_ram()`	Determine if you have enough RAM memory
`fetch_data()`	Download the Human DLPFC Visium data from LIBD
`frame_limits()`	Identify the image limits
`gene_set_enrichment()`	Evaluate the enrichment for a list of gene sets
`gene_set_enrichment_plot()`	Plot the gene set enrichment results
`geom_spatial()`	A ggplot2 layer for visualizing the Visium histology
`get_colors()`	Obtain the colors for a set of cluster names
`img_edit()`	Edit a background image
`img_update()`	Update the image for one sample
`img_update_all()`	Update the images for all samples
`layer_boxplot()`	Layer-level (group-level) boxplots
`layer_matrix_plot()`	Visualize a matrix of values across human brain layers
`layer_stat_cor()`	Layer modeling correlation of statistics
`layer_stat_cor_plot()`	Visualize the layer modeling correlation of statistics
`libd_layer_colors`	Vector of LIBD layer colors
`locate_images()`	Locate image files
`read10xVisiumAnalysis()`	Load analysis data from a 10x Genomics Visium experiment
`read10xVisiumWrapper()`	Load data from a 10x Genomics Visium experiment and make it spatialLIBD-ready
`registration_block_cor()`	Spatial registration: block correlation
`registration_model()`	Spatial registration: model
`registration_pseudobulk()`	Spatial registration: pseudobulk
`registration_stats_anova()`	Spatial registration: compute ANOVA statistics
`registration_stats_enrichment()`	Spatial registration: compute enrichment statistics
`registration_stats_pairwise()`	Spatial registration: compute pairwise statistics
`registration_wrapper()`	Spatial registration: wrapper function
`run_app()`	Run the spatialLIBD Shiny Application
`sce_to_spe()`	Convert a SCE object to a SPE one
`sig_genes_extract()`	Extract significant genes
`sig_genes_extract_all()`	Extract significant genes for all modeling results
`sort_clusters()`	Sort clusters by frequency
`tstats_Human_DLPFC_snRNAseq_Nguyen_topLayer`	Cell cluster t-statistics from Tran et al
`vis_clus()`	Sample spatial cluster visualization
`vis_clus_p()`	Sample spatial cluster visualization workhorse function
`vis_gene()`	Sample spatial gene visualization
`vis_gene_p()`	Sample spatial gene visualization workhorse function
`vis_grid_clus()`	Sample spatial cluster visualization grid
`vis_grid_gene()`	Sample spatial gene visualization grid

Reference

All functions