ExpandCGHcall: Expands result fron CGHcall to CGHcall object.
In tgac-vumc/CGHcall: Calling aberrations for array CGH tumor profiles.

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

Expands result from CGHcall function to CGHcall object.

1	ExpandCGHcall(listcall,inputSegmented, digits=3, divide=4, memeff = FALSE, fileoutpre="Callobj_",CellularityCorrectSeg=TRUE)

`listcall`	List object; output of function `CGHcall`
`inputSegmented`	An object of class `cghSeg`
`digits`	Number of decimal digits to be saved in the resulting call object. Allows for saving storage space
`divide`	Number of batches to divide the work load in. Larger values saves memory, but requires more computing time
`memeff`	When set to TRUE, memory efficient mode is used: results are written in batches to multiple external files. If FALSE, one output object is provided.
`fileoutpre`	Only relevant when memeff=TRUE. Define prefix for output file names
`CellularityCorrectSeg`	If TRUE, corrects segmented and normalized values for cellularity as well

This function is new in version 2.7.0. It allows more memory efficient handling of large data objects. If R crashes because of memory problem, we advise to set memeff = TRUE and increase the value of divide. When multiple files are output (in case of memeff=TRUE) the function combine may be used to combine CGHcall objects.

An object of class cghCall-class either as one object (when memeff = FALSE) or as multiple objects stored in .Rdata files in the working directory (when memeff = FALSE)

Sjoerd Vosse & Mark van de Wiel

Mark A. van de Wiel, Kyung In Kim, Sjoerd J. Vosse, Wessel N. van Wieringen, Saskia M. Wilting and Bauke Ylstra. CGHcall: calling aberrations for array CGH tumor profiles. Bioinformatics, 23, 892-894.

CGHcall, cghCall-class

  data(Wilting)
  ## Convert to \code{\link{cghRaw}} object
  cgh <- make_cghRaw(Wilting)
  print(cgh)
  ## First preprocess the data
  raw.data <- preprocess(cgh)
  ## Simple global median normalization for samples with 75% tumor cells
  perc.tumor <- rep(0.75, 3)
  normalized.data <- normalize(raw.data)
  ## Segmentation with slightly relaxed significance level to accept change-points.
  ## Note that segmentation can take a long time.
  ## Not run: segmented.data <- segmentData(normalized.data, alpha=0.02)
  ## Not run: postsegnormalized.data <- postsegnormalize(segmented.data)
  ## Call aberrations
  ## Not run: result <- CGHcall(postsegnormalized.data, cellularity=perc.tumor)
  ## Not run: result <- ExpandCGHcall(result,postsegnormalized.data)