create a nearest neighbour (NN) network

createNearestNetwork(
  gobject,
  type = c("sNN", "kNN"),
  dim_reduction_to_use = "pca",
  dim_reduction_name = "pca",
  dimensions_to_use = 1:10,
  genes_to_use = NULL,
  expression_values = c("normalized", "scaled", "custom"),
  name = "sNN.pca",
  return_gobject = TRUE,
  k = 30,
  minimum_shared = 5,
  top_shared = 3,
  verbose = T,
  ...
)

Arguments

gobject

giotto object

type

sNN or kNN

dim_reduction_to_use

dimension reduction method to use

dim_reduction_name

name of dimension reduction set to use

dimensions_to_use

number of dimensions to use as input

genes_to_use

if dim_reduction_to_use = NULL, which genes to use

expression_values

expression values to use

name

arbitrary name for NN network

return_gobject

boolean: return giotto object (default = TRUE)

k

number of k neighbors to use

minimum_shared

minimum shared neighbors

top_shared

keep at ...

verbose

be verbose

...

additional parameters for kNN and sNN functions from dbscan

Value

giotto object with updated NN network

Details

This function creates a k-nearest neighbour (kNN) or shared nearest neighbour (sNN) network based on the provided dimension reduction space. To run it directly on the gene expression matrix set dim_reduction_to_use = NULL.

See also kNN and sNN for more information about how the networks are created.

Output for kNN:

  • from: cell_ID for source cell

  • to: cell_ID for target cell

  • distance: distance between cells

  • weight: weight = 1/(1 + distance)

Output for sNN:

  • from: cell_ID for source cell

  • to: cell_ID for target cell

  • distance: distance between cells

  • weight: 1/(1 + distance)

  • shared: number of shared neighbours

  • rank: ranking of pairwise cell neighbours

For sNN networks two additional parameters can be set:

  • minimum_shared: minimum number of shared neighbours needed

  • top_shared: keep this number of the top shared neighbours, irrespective of minimum_shared setting

Examples

data(mini_giotto_single_cell)

mini_giotto_single_cell <- createNearestNetwork(gobject = mini_giotto_single_cell,
                                                dimensions_to_use = 1:3, k = 3)