CytobankBridgeR (version 1.0.0)

gates.apply_cluster_gates: Gates

Description

Gates High Level Functions

Usage

gates.apply_cluster_gates(UserSession, experiment_id, name, clusters,
  channel_name, integer_min = 1, integer_max = max(clusters),
  grouped = FALSE, timeout = 60)

Arguments

UserSession

Cytobank UserSession object (created via the authenticate function)

experiment_id

integer representing an experiments ID

name

character representing a cluster prefix (if grouped=FALSE) or multicluster gate name

clusters

integer vector representing the clusters to gate - There are 2 modes of operation: 1) grouped=FALSE: clusters represent individual integer clusters to gate, this will create multiple gates that represents multiple individual populations 2) grouped=TRUE: clusters represent a multi-integer cluster to gate, this will create one gate that represents one population around the integer clusters specified

channel_name

character representing the channel short name

integer_min

integer representing the minimum cluster integer for setting scales [optional] - The default is set to 1, this assumes clusters begin at 1, but can be changed if there is any +/- offset - The minimum scale will be set to integer_min-1 (0 by)

integer_max

integer representing the maximum cluster integer for setting scales [optional] - The default is the maximum number presented within the clusters vector, but can be set to any integer - The max scale will be set to integer_max+1

grouped

logical representing whether to gate a vector of integer clusters as individual integer clusters (grouped=FALSE), or together as a single multicluster (grouped=TRUE)

timeout

integer representing the request timeout time in seconds [optional]

Details

gates.apply_cluster_gates Apply cluster gate(s) to specific clusters via an integer vector

Examples

# NOT RUN {
gates.apply_cluster_gates(cyto_session, 22, name="cluster_names",
  clusters=c(1,5,9), channel_name="cluster_id")
# }