pseudotime.knetl {iCellR} | R Documentation |
iCellR KNN Network
Description
This function takes an object of class iCellR and and runs kNet for dimensionality reduction.
Usage
pseudotime.knetl(
x = NULL,
dist.method = "euclidean",
k = 5,
abstract = TRUE,
data.type = "pca",
dims = 1:20,
conds.to.plot = NULL,
my.layout = "layout_with_fr",
node.size = 10,
cluster.membership = FALSE,
interactive = TRUE,
node.colors = NULL,
edge.color = "gray",
out.name = "Pseudotime.Abstract.KNetL",
my.seed = 1
)
Arguments
x |
An object of class iCellR. |
dist.method |
the distance measure to be used to compute the dissimilarity matrix. This must be one of: "euclidean", "maximum", "mandatattan", "canberra", "binary", "minkowski" or "NULL". By default, distance="euclidean". If the distance is "NULL", the dissimilarity matrix (diss) should be given by the user. If distance is not "NULL", the dissimilarity matrix should be "NULL". |
k |
KNN the higher the number the less sensitivity, default = 5. |
abstract |
Draw all the cells or clusters, , default = TRUE. |
data.type |
Choose between "tsne", "pca", "umap", default = "pca". We highly recommend PCA. |
dims |
PCA dimentions to be use for clustering, default = 1:20. |
conds.to.plot |
Choose the conditions you want to see in the plot, default = NULL (all conditions). |
my.layout |
Choose a layout, default = "layout_with_fr". |
node.size |
Size of the nodes, , default = 10. |
cluster.membership |
Calculate memberships based on distance. |
interactive |
If set to TRUE an interactive HTML file will be created, default = TRUE. |
node.colors |
Color of the nodes, default = random colors. |
edge.color |
Solor of the edges, default = "gray". |
out.name |
If "interactive" is set to TRUE, the out put name for HTML, default = "Abstract.KNetL". |
my.seed |
seed number, default = 1. |
Value
A plot.