gt_gating: Applies a gatingTemplate to a GatingSet.
In openCyto: Hierarchical Gating Pipeline for flow cytometry data

Description Usage Arguments Value Examples

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

1	gt_gating(x, y, ...)

`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 process 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. keep.helperGatesa `logical` flag indicating whether to keep the intermediate helper gates that are automatically generated by openCyto. Default is TRUE. 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")

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

## Not run: 
 gt <- gatingTemplate(file.path(path, "data/ICStemplate.csv"), "ICS")
 gs <- GatingSet(fs) #fs is a flowSet/ncdfFlowSet
 gt_gating(gt, gs)
 gt_gating(gt, gs, stop.at = "v") #proceed the gating until population 'v'
 gt_gating(gt, gs, start = "v") # start from 'v'
 gt_gating(gt, gs, parallel_type = "multicore", mc.cores = 8) #parallel gating using multicore
 #parallel gating by using cluster
 cl1 <- makeCluster (8, type = "MPI")
 gt_gating(gt, gs, parallel_type = "cluster", cl = cl1)
 stopCluster ( cl1 )

## End(Not run)