HMRF

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 HMRF

# create a directory to save your HMRF results to
hmrf_folder = paste0(getwd(),'/','11_HMRF/')
if(!file.exists(hmrf_folder)) dir.create(hmrf_folder, recursive = T)

# perform hmrf
my_spatial_genes = km_spatialgenes[1:100]$genes
HMRF_spatial_genes = doHMRF(gobject = my_giotto_object,
                            expression_values = 'scaled',
                            spatial_genes = my_spatial_genes,
                            spatial_network_name = 'Delaunay_network',
                            k = 9,
                            betas = c(28,2,2),
                            output_folder = paste0(hmrf_folder, '/', 'Spatial_genes/SG_top100_k9_scaled'))

# check and visualize hmrf results
for(i in seq(28, 30, by = 2)) {
  viewHMRFresults2D(gobject = my_giotto_object,
                    HMRFoutput = HMRF_spatial_genes,
                    k = 9, betas_to_view = i,
                    point_size = 2)
}

my_giotto_object = addHMRF(gobject = my_giotto_object,
                  HMRFoutput = HMRF_spatial_genes,
                  k = 9, betas_to_add = c(28),
                  hmrf_name = 'HMRF')

# visualize selected hmrf result
giotto_colors = Giotto:::getDistinctColors(9)
names(giotto_colors) = 1:9
spatPlot(gobject = my_giotto_object, cell_color = 'HMRF_k9_b.28',
         point_size = 3, coord_fix_ratio = 1, cell_color_code = giotto_colors)