Create an S4 nnNetObj
Usage
createNearestNetObj(
name = "test",
network,
nn_type = NULL,
spat_unit = "cell",
feat_type = "rna",
provenance = NULL,
misc = NULL
)Arguments
- name
name of nnNetObj
- network
igraph object or data.frame containing nearest neighbor information (see details)
- nn_type
type of nearest neighbor network
- spat_unit
spatial unit (e.g. "cell")
- feat_type
feature type (e.g. "rna", "dna", "protein")
- provenance
origin of aggregated information (if applicable)
- misc
misc
Details
igraph and dataframe-like inputs must include certain information. For igraph, it must have, at minimum vertex 'name' attributes and 'distance' edge attribute. dataframe-like inputs must have 'from', 'to', and 'distance' columns
Examples
x <- GiottoData::loadSubObjectMini("nnNetObj")
createNearestNetObj(
network = slot(x, "igraph"), name = "sNN",
nn_type = "sNN"
)
#> An object of class nnNetObj : "sNN"
#> --| Contains nearest neighbor network generated with: sNN
#> ----| for feat_type: rna
#> ----| spat_unit: cell
#> IGRAPH 859f76e DNW- 462 3021 --
#> + attr: name (v/c), weight (e/n), distance (e/n), shared (e/n), rank
#> | (e/n)
#> + edges from 859f76e (vertex names):
#> [1] 240649020551054330404932383065726870513->335295524680090725199231409883288198017
#> [2] 240649020551054330404932383065726870513->77151711298730578178892667721058396928
#> [3] 240649020551054330404932383065726870513->322879686187630160969459793861944841206
#> [4] 240649020551054330404932383065726870513->31072896077757820678000109671990674373
#> [5] 240649020551054330404932383065726870513->102184699197574201819246996094734116255
#> [6] 240649020551054330404932383065726870513->17685062374745280598492217386845129350
#> + ... omitted several edges
#>
#>