I'm trying to use
LVSmiRNA to normalize a total of ~1700 (agilent) samples. The problem is that the step when
estVC is called takes lot of time.
The vignette of the package propose to use
multicore package but this packages is deprecated and CRAN suggest to use parallel.
Hence I just changed one line from the proposed code from the
LVSmiRNA's vignette to run
estVC. This code follows:
require(parallel) options(cores=16) require(LVSmiRNA) require(limma) MIR <- read.mir(mirna_files, path=mirna_path, verbose=TRUE) colnames(MIR$E) <- colnames(MIR$Eb) <- samples_names class(MIR)<-"EList" MIR.RA <- estVC(MIR, verbose=TRUE)
I just expected to get a different output from
estVC when parallel is loaded and cores option is set to a large number than the one I obtained:
May I should indicate something else to
estVC in order to run it faster than sequentially? Otherwise, may you know a faster way to apply this normalization to a large set of samples?