Spatial gene coexpression

1. processing steps

library(Giotto)

path_to_matrix = system.file("extdata", "seqfish_field_expr.txt", package = 'Giotto')
path_to_locations = system.file("extdata", "seqfish_field_locs.txt", package = 'Giotto')

my_giotto_object = createGiottoObject(raw_exprs = path_to_matrix,
                                      spatial_locs = path_to_locations)

# processing
my_giotto_object <- filterGiotto(gobject = seqfish_mini, 
                             expression_threshold = 0.5, 
                             gene_det_in_min_cells = 20, 
                             min_det_genes_per_cell = 0)
my_giotto_object <- normalizeGiotto(gobject = my_giotto_object)

# create network (required for binSpect methods)
my_giotto_object = createSpatialNetwork(gobject = my_giotto_object, minimum_k = 2)

# identify genes with a spatial coherent expression profile
km_spatialgenes = binSpect(my_giotto_object, bin_method = 'kmeans')

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2. Run spatial gene co-expression method

# 1. calculate spatial correlation scores 
ext_spatial_genes = km_spatialgenes[1:500]$genes
spat_cor_netw_DT = detectSpatialCorGenes(my_giotto_object,
                                         method = 'network', 
                                         spatial_network_name = 'Delaunay_network',
                                         subset_genes = ext_spatial_genes)

# 2. cluster correlation scores
spat_cor_netw_DT = clusterSpatialCorGenes(spat_cor_netw_DT, 
                                          name = 'spat_netw_clus', k = 8)
heatmSpatialCorGenes(my_giotto_object, spatCorObject = spat_cor_netw_DT, 
                     use_clus_name = 'spat_netw_clus')

# rank spatial correlation clusters based on how similar they are
netw_ranks = rankSpatialCorGroups(my_giotto_object, 
                                  spatCorObject = spat_cor_netw_DT, 
                                  use_clus_name = 'spat_netw_clus')

# extract information about clusters
top_netw_spat_cluster = showSpatialCorGenes(spat_cor_netw_DT, 
                                            use_clus_name = 'spat_netw_clus',
                                            selected_clusters = 6, 
                                            show_top_genes = 1)

cluster_genes_DT = showSpatialCorGenes(spat_cor_netw_DT, 
                                       use_clus_name = 'spat_netw_clus',
                                       show_top_genes = 1)

cluster_genes = cluster_genes_DT$clus; names(cluster_genes) = cluster_genes_DT$gene_ID

# create spatial metagenes and visualize
my_giotto_object = createMetagenes(my_giotto_object, gene_clusters = cluster_genes, name = 'cluster_metagene')
spatCellPlot(my_giotto_object,
             spat_enr_names = 'cluster_metagene',
             cell_annotation_values = netw_ranks$clusters,
             point_size = 1.5, cow_n_col = 3)