Spatial autocorrelation

Source: R/spatial_enrichment.R

Find spatial autocorrelation. Note that spatialAutoCorGlobal will return values as a data.table instead of appending information to the gobject. spatialAutoCorLocal will append the results as a spatial enrichment object by default.
If providing external data using either the node_values and/or weight_matrix params, the order of values provided should be the same as the ordering of the columns and rows of the weight matrix.

spatialAutoCorGlobal(
  gobject = NULL,
  spat_unit = NULL,
  feat_type = NULL,
  feats = NULL,
  method = c("moran", "geary"),
  data_to_use = c("expression", "cell_meta"),
  expression_values = c("normalized", "scaled", "custom"),
  meta_cols = NULL,
  spatial_network_to_use = "kNN_network",
  wm_method = c("distance", "adjacency"),
  wm_name = "spat_weights",
  node_values = NULL,
  weight_matrix = NULL,
  test_method = c("none", "monte_carlo"),
  mc_nsim = 99,
  cor_name = NULL,
  return_gobject = FALSE,
  verbose = TRUE
)

spatialAutoCorLocal(
  gobject = NULL,
  spat_unit = NULL,
  feat_type = NULL,
  feats = NULL,
  method = c("moran", "gi", "gi*", "mean"),
  data_to_use = c("expression", "cell_meta"),
  expression_values = c("normalized", "scaled", "custom"),
  meta_cols = NULL,
  spatial_network_to_use = "kNN_network",
  wm_method = c("distance", "adjacency"),
  wm_name = "spat_weights",
  node_values = NULL,
  weight_matrix = NULL,
  test_method = c("none"),
  enrich_name = NULL,
  return_gobject = TRUE,
  output = c("spatEnrObj", "data.table"),
  verbose = TRUE
)

Arguments

gobject

giotto object

spat_unit

spatial unit

feat_type

feature type

feats

features (expression) on which to run autocorrelation. (leaving as NULL means that all features will be tested)

method

method of autocorrelation. See details (default = 'moran')

data_to_use

if using data from gobject, whether to test using expression ('expression') or cell metadata ('cell_meta')

expression_values

name of expression information to use

meta_cols

columns in cell metadata to test

spatial_network_to_use

spatial network to use

wm_method

type of weight matrix to generate from spatial network if no weight matrix is found attached to the spatial network

wm_name

name of attached weight matrix to use

node_values

alternative method of directly supplying a set of node values

weight_matrix

alternative method of directly supplying a spatial weight matrix

test_method

method to test values for significance (default is no testing)

mc_nsim

when test_method = 'monte_carlo' this is number of simulations to perform

cor_name

name to assign the results in global autocorrelation output

return_gobject

(default = FALSE) whether to return results appended to

verbose

be verbose

enrich_name

name to assign local autocorrelation spatial enrichment results

output

'spatEnrObj' or 'data.table' metadata in the giotto object or as a data.table

Value

spatial autocorrelation

Details

Global Methods:

  • Moran's I 'moran'

  • Geary's C 'geary'

Local Methods:

  • Local Moran's I 'moran'

  • Getis-Ord Gi 'Gi'

  • Getis-Ord Gi* 'Gi*'

  • Local mean 'mean'

Functions

  • spatialAutoCorGlobal(): Global autocorrelation (single value returned)

  • spatialAutoCorLocal(): Local autocorrelation (values generated for each spatial ID)