tof_cluster_phenograph | R Documentation |
This function performs PhenoGraph clustering on high-dimensional cytometry data using a user-specified selection of input variables/high-dimensional cytometry measurements.
tof_cluster_phenograph(
tof_tibble,
cluster_cols = where(tof_is_numeric),
num_neighbors = 30,
distance_function = c("euclidean", "cosine"),
...
)
tof_tibble |
A 'tof_tbl' or 'tibble'. |
cluster_cols |
Unquoted column names indicating which columns in 'tof_tibble' to use in computing the PhenoGraph clusters. Defaults to all numeric columns in 'tof_tibble'. Supports tidyselect helpers. |
num_neighbors |
An integer indicating the number of neighbors to use when constructing PhenoGraph's k-nearest-neighbor graph. Smaller values emphasize local graph structure; larger values emphasize global graph structure (and will add time to the computation). Defaults to 30. |
distance_function |
A string indicating which distance function to use for the nearest-neighbor calculation. Options include "euclidean" (the default) and "cosine" distances. |
... |
Optional additional parameters that can be passed to
|
For additional details about the Phenograph algorithm, see this paper.
A tibble with one column named '.phenograph_cluster'. This column will contain an integer vector of length 'nrow(tof_tibble)' indicating the id of the PhenoGraph cluster to which each cell (i.e. each row) in 'tof_tibble' was assigned.
Other clustering functions:
tof_cluster()
,
tof_cluster_ddpr()
,
tof_cluster_flowsom()
,
tof_cluster_kmeans()
sim_data <-
dplyr::tibble(
cd45 = rnorm(n = 1000),
cd38 = rnorm(n = 1000),
cd34 = rnorm(n = 1000),
cd19 = rnorm(n = 1000)
)
tof_cluster_phenograph(tof_tibble = sim_data)
tof_cluster_phenograph(tof_tibble = sim_data, cluster_cols = c(cd45, cd19))
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