Network visualisation for an IDER-based similarity matrix. The vertexes are initial clusters, and the edge width denotes the similarity between two initial clusters.
plotNetwork( seu, ider, colour.by = NULL, weight.factor = 6.5, col.vector = NULL, vertex.size = 1 )
| seu | Seurat S4 object after the step of `getIDER`, containing `initial_cluster` and `Batch` in its meta.data. Required. |
|---|---|
| ider | A list. Output of `getIDER`. Required. |
| colour.by | Character. It should be one of the colnames of Seurat object meta.data.It is used to colour the vertex of the network graph. (Default: NULL) |
| weight.factor | Numerical. Adjust the thickness of the edges. (Default: 6.5) |
| col.vector | A vector of Hex colour codes. If no value is given (default), a vector of 74 colours will be used. |
| vertex.size | Numerical. Adjsut the size of vertexes. (Default: 1) |
plotNetwork(
seu,
ider,
colour.by = NULL,
weight.factor = 6.5,
col.vector = NULL,
vertex.size = 1
)Seurat S4 object after the step of `getIDER`, containing `initial_cluster` and `Batch` in its meta.data. Required.
A list. Output of `getIDER`. Required.
Character. It should be one of the colnames of Seurat object meta.data.It is used to colour the vertex of the network graph. (Default: NULL)
Numerical. Adjust the thickness of the edges. (Default: 6.5)
A vector of Hex colour codes. If no value is given (default), a vector of 74 colours will be used.
Numerical. Adjsut the size of vertexes. (Default: 1)
An igraph object
if (FALSE) { plotNetwork(seu, ider, weight.factor = 5) }