pFlowMerge: Parellel call to flowMerge
In flowMerge: Cluster Merging for Flow Cytometry Data

Description Usage Arguments Details Value Warning Author(s) References See Also Examples

Calls the flowMerge methods to compute the merged solution from a flowClust object or set of objects in a parallelized manner using the snow framework.

pFlowMerge(flowData, cl, K = 1:15, 
   B.init = 100, tol.init = 0.01, tol = 1e-05, 
   B = 500, randomStart = 10, nu = 4, nu.est = 0, 
   trans = 1, varNames = NA)

`flowData`	The data to be fit. A list of `flowFrame`s, a `flowSet` or a `flowFrame`
`cl`	The `snow` cluster object. Can be NULL to call the non-parallel version of flowClust
`K`	See `flowClust` documentation
`B.init`	See `flowClust` documentation
`tol.init`	See `flowClust` documentation
`tol`	See `flowClust` documentation
`B`	See `flowClust` documentation
`randomStart`	See `flowClust` documentation
`nu`	See `flowClust` documentation
`nu.est`	See `flowClust` documentation
`trans`	See `flowClust` documentation
`varNames`	See `flowClust` documentation

Makes a parallelized call to flowClust. Parses the results to extract the max BIC solution, merges clusters, finds the optimal k-cluster solution using the entropy and returns it. If cl is NULL, a non-parallel call is made to the flowClust function.

A list of flowMerge objects. One per flowFrame passed into the method.

This function does not do any special memory management. A large data set will likely cause it to run out of memory and start swapping incessantly. If you have lots of data, it's best to feed it piecewise to pFlowClust.

Greg Finak <greg.finak@ircm.qc.ca>

Finak G, Bashasharti A, Brinkmann R, Gottardo R. Merging Mixture Model Components for Improved Cell Population Identification in High Throughput Flow Cytometry Data (Submitted)

pFlowClust,flowClust,merge,snow, fitPiecewiseLinreg

data(rituximab)
#Parallelized call below:
## Not run: cl<-makeSOCKcluster(rep("finakg@localhost",7))
## Not run: result<-pFlowMerge(rituximab,cl,varNames=c("FSC.H","SSC.H"))
## Not run: plot(result)
#cl<-NULL;
#result<-pFlowMerge(rituximab,cl=NULL,varNames=c("FSC.H","SSC.H"),K=1:8);
#plot(result);