CGHcall (version 2.34.0)

ExpandCGHcall: Expands result fron CGHcall to CGHcall object.

Description

Expands result from CGHcall function to CGHcall object.

Usage

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

Arguments

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

Value

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)

Details

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.

References

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.

See Also

CGHcall, cghCall-class

Examples

  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)