View source: R/Seurat-function.R
RunPHATE | R Documentation |
Run PHATE (Potential of Heat-diffusion for Affinity-based Trajectory Embedding)
RunPHATE(object, ...)
## S3 method for class 'Seurat'
RunPHATE(
object,
reduction = "pca",
dims = NULL,
features = NULL,
assay = NULL,
slot = "data",
n_components = 2,
knn = 5,
decay = 40,
n_landmark = 2000,
t = "auto",
gamma = 1,
n_pca = 100,
knn_dist = "euclidean",
knn_max = NULL,
t_max = 100,
do_cluster = FALSE,
n_clusters = "auto",
max_clusters = 100,
reduction.name = "phate",
reduction.key = "PHATE_",
verbose = TRUE,
seed.use = 11L,
...
)
## Default S3 method:
RunPHATE(
object,
assay = NULL,
n_components = 2,
knn = 5,
decay = 40,
n_landmark = 2000,
t = "auto",
gamma = 1,
n_pca = 100,
knn_dist = "euclidean",
knn_max = NULL,
t_max = 100,
do_cluster = FALSE,
n_clusters = "auto",
max_clusters = 100,
reduction.key = "PHATE_",
verbose = TRUE,
seed.use = 11L,
...
)
object |
An object. This can be a Seurat object or a matrix-like object. |
... |
Additional arguments to be passed to the phate.PHATE function. |
reduction |
A character string specifying the reduction to be used. Default is "pca". |
dims |
An integer vector specifying the dimensions to be used. Default is NULL. |
features |
A character vector specifying the features to be used. Default is NULL. |
assay |
A character string specifying the assay to be used. Default is NULL. |
slot |
A character string specifying the slot name to be used. Default is "data". |
n_components |
An integer specifying the number of PHATE components. Default is 2. |
knn |
An integer specifying the number of nearest neighbors on which to build kernel. Default is 5. |
decay |
An integer specifying the sets decay rate of kernel tails. Default is 40. |
n_landmark |
An integer specifying the number of landmarks to use in fast PHATE. Default is 2000. |
t |
A character string specifying the power to which the diffusion operator is powered. This sets the level of diffusion. If ‘auto’, t is selected according to the knee point in the Von Neumann Entropy of the diffusion operator. Default is "auto". |
gamma |
A numeric value specifying the informational distance constant between -1 and 1. gamma=1 gives the PHATE log potential, gamma=0 gives a square root potential. Default is 1. |
n_pca |
An integer specifying the number of principal components to use for calculating neighborhoods. For extremely large datasets, using n_pca < 20 allows neighborhoods to be calculated in roughly log(n_samples) time. Default is 100. |
knn_dist |
A character string specifying the distance metric for k-nearest neighbors. Recommended values: "euclidean, "cosine, "precomputed". Default is "euclidean". |
knn_max |
An integer specifying the maximum number of neighbors for which alpha decaying kernel is computed for each point. For very large datasets, setting knn_max to a small multiple of knn can speed up computation significantly. Default is NULL. |
t_max |
An integer specifying the maximum |
do_cluster |
A logical value indicating whether to perform clustering on the PHATE embeddings. Default is FALSE. |
n_clusters |
An integer specifying the number of clusters to be identified. Default is "auto". |
max_clusters |
An integer specifying the maximum number of clusters to test. Default is 100. |
reduction.name |
A character string specifying the name of the reduction to be stored in the Seurat object. Default is "phate". |
reduction.key |
A character string specifying the prefix for the column names of the PHATE embeddings. Default is "PHATE_". |
verbose |
A logical value indicating whether to print verbose output. Default is TRUE. |
seed.use |
An integer specifying the random seed to be used. Default is 11. |
pancreas_sub <- Seurat::FindVariableFeatures(pancreas_sub)
pancreas_sub <- RunPHATE(object = pancreas_sub, features = Seurat::VariableFeatures(pancreas_sub))
CellDimPlot(pancreas_sub, group.by = "CellType", reduction = "phate")
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