# spatialHeatmap

## Documentation for package ‘spatialHeatmap’ version 2.2.0

- DESCRIPTION file.
- User guides, package vignettes and other documentation.
- Package NEWS.

## Help Pages

spatialHeatmap-package | spatialHeatmap Spatial Heatmap, Matrix Heatmap, Network
adj_mod | Compute Adjacency Matrix and Identify Modules
aggr_rep | Aggregate "Sample__Condition" Replicates in Data Matrix
aSVG.remote.repo | A list of URLs of remote aSVG repos
auc_bar | Bar plot of AUCs from validating data sets
auc_stat | Extract AUC statistics in coclustering optimization
auc_violin | Plot extracted AUCs by parameter settings
cluster_cell | Cluster single cells or combination of single cells and bulk
cocluster | Coclustering bulk and single cell data in a single run
coclus_opt | Optimizing coclustering process with two levels of parallelizations available.
coclus_roc | Co-cluster bulk and single cell data Calculate ROC/AUC for the combined bulk and single cell data
com_factor | Combine Factors in Targets File
custom_shiny | Create Customized Shiny App of Spaital Heatmap
deg.table | A table of differentialy-expressed genes (DEGs) detected by different methods
deg_ovl | Plot Overlap of Spatially-Enriched Genes Across Methods
desired_bulk_shiny | Integrated Shiny App
edit_tar | Edit Targets Files
filter_cell | Filter single cell data separately in a list
filter_data | Filter the Data Matrix
filter_iter | Iteratively filter bulk and single data according to parameters in a data frame.
lis.deg.up.down | A nested list of differentialy-expressed genes (DEGs) detected by different methods
matrix_hm | Matrix Heatmap
mean_auc_bar | Plot mean of extracted AUCs by parameter settings
network | Visualize a Target Assayed Item in a Network Graph
norm_data | Normalize Sequencing Count Matrix
norm_multi | Normalize one or multiple count data sets.
plot_dim | Plotting single cells in reduced dimensionalities
profile_gene | Plot Gene Expression Profiles in a Data Frame
random_para | Generate random combinations of parameter settings
read_cache | Read R Objects from Cache
read_fr | Import Data from Tabular Files
read_hdf5 | Read Data from the Shiny App Database
reduce_rep | Reduce sample replicates
refine_cluster | Refine single cell clusters
return_feature | Return aSVG Files Relevant to Target Features
save_cache | Save R Objects in Cache
shiny_shm | Integrated Shiny App
spatialHeatmap | spatialHeatmap Spatial Heatmap, Matrix Heatmap, Network
spatial_enrich | Identify Spatial Feature-Specifcally Expressed Genes
spatial_hm | Plot Spatial Heatmaps
spd_auc_violin | Violin plot of extracted AUCs by top spd.sets
submatrix | Subset Target Assayed Items and Their Nearest Neighbors
sub_asg | Subset the bulk-cell assignments
sub_data | Subset Target Data for Spatial Enrichment
true_bulk | Assign true bulk to cells in 'colData' slot.
update_feature | Update aSVG Spatial Features
write_hdf5 | Construct Database for the Shiny App