`createNearestNetwork`¶

createNearestNetwork

Description¶

create a nearest neighbour (NN) network

Usage¶

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¶

Argument	Description
`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

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` <#knn>`_ and ``sNN` <#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

Value¶

giotto object with updated NN network

Examples¶

data(mini_giotto_single_cell)

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

createNearestNetwork¶