Split dendrogram at each node and keep the leave (label) information.
Arguments
- gobject
giotto object
- spat_unit
spatial unit
- feat_type
feature type
- expression_values
expression values to use
- cluster_column
name of column to use for clusters
- cor
correlation score to calculate distance
- distance
distance method to use for hierarchical clustering
- h
height of horizontal lines to plot
- h_color
color of horizontal lines
- show_dend
show dendrogram
- verbose
be verbose
Value
data.table object
Details
Creates a data.table with three columns and each row represents a node in the dendrogram. For each node the height of the node is given together with the two subdendrograms. This information can be used to determine in a hierarchical manner differentially expressed marker genes at each node.
Examples
g <- GiottoData::loadGiottoMini("visium")
#> 1. read Giotto object
#> 2. read Giotto feature information
#> 3. read Giotto spatial information
#> 3.1 read Giotto spatial shape information
#> cell_spatInfo_spatVector.shp
#> cell
#>
#> 3.2 read Giotto spatial centroid information
#> cell
#>
#> 3.3 read Giotto spatial overlap information
#> No overlaps were found, overlap loading will be
#> skipped
#>
#> 4. read Giotto image information
#> a giotto python environment was found
#> Using python path:
#> "/Users/yuanlab/Library/r-miniconda/envs/giotto_env/bin/pythonw"
getDendrogramSplits(g, cluster_column = "leiden_clus")
#> height 0.9390206
#> height 0.5534887
#> height 0.3766879
#> height 0.1956274
#> height 0.1330244
#> height 0.1259414
#> node_h tree_1 tree_2 nodeID
#> <list> <list> <list> <char>
#> 1: 0.939020.... 2, 1, 3 7, 4, 5, 6 node_1
#> 2: 0.553488.... 7 4, 5, 6 node_2
#> 3: 0.376687.... 4 5, 6 node_3
#> 4: 0.195627.... 2 1, 3 node_4
#> 5: 0.133024.... 1 3 node_5
#> 6: 0.125941.... 5 6 node_6