openCyto (version 1.10.3)

gating: Apply the gates to a GatingSet

Description

It applies the gates to the GatingSet based on the population tree described in graphGML.

It loads the gating methods by topological order and applies them to GatingSet.

Usage

gating(x, y, ...)
## S3 method for class 'gatingTemplate,GatingSet':
gating(x, y, env_fct = NULL, ...)
## S3 method for class 'gatingTemplate,GatingSetList':
gating(x, y, env_fct = NULL, ...)

Arguments

x

a gatingTemplate object

y

a GatingSet object

...

• start

{ a character that specifies the population (correspoding to 'alias' column in csv template) where the gating prcoess will start from. It is useful to quickly skip some gates and go directly to the target population in the testing run. Default is "root".} stop.at{ a character that specifies the population (correspoding to 'alias' column in csv template) where the gating prcoess will stop at. Default is NULL, indicating the end of gating tree.} mc.cores{ passed to multicore package for parallel computing} parallel_type{ character specifying the parallel type. The valid options are "none", "multicore", "cluster".} cl{ cluster object passed to parallel package (when parallel_type is "cluster")}

Value

• Nothing. As the side effect, gates generated by gating methods are saved in GatingSet.

item

env_fct

code

fcTree

Examples

gt <- gatingTemplate(file.path(path, "data/ICStemplate.csv"), "ICS")
 gs <- GatingSet(fs) #fs is a flowSet/ncdfFlowSet
 gating(gt, gs)
 gating(gt, gs, stop.at = "v") #proceed the gating until population 'v'
 gating(gt, gs, start = "v") # start from 'v'
 gating(gt, gs, parallel_type = "multicore", mc.cores = 8) #parallel gating using multicore
 #parallel gating by using cluster
 cl1 <- makeCluster (8, type = "MPI")
 gating(gt, gs, parallel_type = "cluster", cl = cl1)
 stopCluster ( cl1 )