[BioC] Calculation times

[Claire Wilson]

Dear all,

I have recently upgraded my linux machine from R1.6.2/Bioconductor 1.1 to R1.7/Bioconductor 1.2 and have found that the new version runs considerabley slower than the old version. So much so that I have a function to calculate fold change for an expression set that takes a few minutes to run in R1.6.2/BioC 1.1, but well over half an hour to run on the latest version. 

here is the code..
 calc.fc <- function(y, x) {
	  # split y according to treatment
    	     exprs.values <- split(y, treatment)
	  # exprs.values has 2 elements control in [[1]] and treatment in [[2]]
	  # exprs.values[[1]][1:3] is the control group for a
	  # exprs.values[[1]][4:6] is the control group for b
	  # exprs.values[[2]][1:3] is the treatment group for a
	  # exprs.values[[2]][4:6] is the treatment group for b
    if (x == "a") {
        # Calculate the means expression level for each group in a
           m1 <- log2(mean(exprs.values[[1]][1:3]))
           m2 <- log2(mean(exprs.values[[2]][1:3]))
    }else{
       # Calculate the means expression level for each group in b
          m1 <- log2(mean(exprs.values[[1]][4:6]))
          m2 <- log2(mean(exprs.values[[2]][4:6]))
     }
    # Calculate the fold change
       log.fold.change <- m1 - m2
    # If it is less than 0 it is a negative fold change
    # Need to make it positive, take the anti-log and then make it negative again
    # Else just calculate the anti-log
      if (log.fold.change < 0 ) {
          x <- -1 * log.fold.change
          fold.change <- -1 * (2^x)
      }else {
          fold.change <- (2^log.fold.change)
      }
      return (t(fold.change))
  }
  
# Run the function
 esApply(eset,1,calc.fc, x="a")

Any ideas?
Thanks

claire
--
Claire Wilson   
Bioinformatics group  
Paterson Institute for Cancer Research  
Christies Hospital NHS Trust  
Wilmslow Road,  
Withington  
Manchester  
M20 4BX  
tel: +44 (0)161 446 8218  
url: http://bioinf.picr.man.ac.uk/
 
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