Description Usage Arguments Details Value Examples
SNPRMA will preprocess SNP chips. The preprocessing consists of quantile normalization to a known target distribution and summarization to the SNP-Allele level.
1 2  | 
filenames | 
 'character' vector with file names.  | 
mixtureSampleSize | 
 Sample size to be use when fitting the mixture model.  | 
fitMixture | 
 'logical'. Fit the mixture model?  | 
eps | 
 Stop criteria.  | 
verbose | 
 'logical'.  | 
seed | 
 Seed to be used when sampling.  | 
cdfName | 
 cdfName: 'GenomeWideSnp\_5', 'GenomeWideSnp\_6'  | 
sns | 
 Sample names.  | 
'snprma2' allows one to genotype very large datasets (via ff package) and also permits the use of clusters or multiple cores (via snow package) to speed up preprocessing.
A | 
 Summarized intensities for Allele A  | 
B | 
 Summarized intensities for Allele B  | 
sns | 
 Sample names  | 
gns | 
 SNP names  | 
SNR | 
 Signal-to-noise ratio  | 
SKW | 
 Skewness  | 
mixtureParams | 
 Parameters from mixture model  | 
cdfName | 
 Name of the CDF  | 
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26  | if (require(genomewidesnp6Crlmm) & require(hapmapsnp6) & require(oligoClasses)){
  path <- system.file("celFiles", package="hapmapsnp6")
  ## the filenames with full path...
  ## very useful when genotyping samples not in the working directory
  cels <- list.celfiles(path, full.names=TRUE)
  snprmaOutput <- snprma(cels)
  snprmaOutput[["A"]][1:10,]
  snprmaOutput[["B"]][1:10,]
}
## Not run: 
## HPC Example
library(ff)
library(snow)
library(crlmm)
## genotype 50K SNPs at a time
ocProbesets(50000)
## setup cluster - 8 cores on the machine
setCluster(8, "SOCK")
path <- system.file("celFiles", package="hapmapsnp6")
cels <- list.celfiles(path, full.names=TRUE)
snprmaOutput <- snprma2(cels)
## End(Not run)
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