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createMetafeats

createMetafeats.Rd

This function creates an average metafeat/metagene/module for clusters.

Usage

createMetafeats(
  gobject,
  spat_unit = NULL,
  feat_type = NULL,
  expression_values = c("normalized", "scaled", "custom"),
  feat_clusters,
  name = "metafeat",
  return_gobject = TRUE
)

Arguments

gobject

Giotto object

spat_unit

spatial unit

feat_type

feature type

expression_values

expression values to use

feat_clusters

numerical vector with features as names

name

name of the metagene results

return_gobject

return giotto object

Value

giotto object

Details

An example for the 'gene_clusters' could be like this: cluster_vector = c(1, 1, 2, 2); names(cluster_vector) = c('geneA', 'geneB', 'geneC', 'geneD')

See also

GiottoVisuals::spatCellPlot()

Examples

if (FALSE) {
# load a dataset
g <- GiottoData::loadGiottoMini("viz")
# set a spat unit to use
activeSpatUnit(g) <- "aggregate"

# create the metafeats
# We do this by making an annotation vector which is a numerical vector
# of cluster assignments where each number is named by the feature it describes.
#
# Here we create an example annotation vector by arbitrarily using the first 6
# features and putting 3 in cluster 1 and the other 3 in cluster 2.
feats_to_use <- featIDs(g)[1:6]
clust_to_use <- c(1, 1, 1, 2, 2, 2)
names(clust_to_use) <- feats_to_use

# show
clust_to_use

g <- createMetafeats(
    gobject = g,
    feat_clusters = clust_to_use,
    name = "new_metagene"
)

GiottoVisuals::spatCellPlot(
    gobject = g,
    spat_enr_names = "new_metagene",
    cell_annotation_values = c("1", "2"),
    point_size = 3.5,
    cow_n_col = 2
)
}