| cel2ras {SNPMaP} | R Documentation |
Workflow functions to process SNPMaP objects. Called by snpmap().
cel2raw(x, cels = x@chps, lowMemory = x@lowMemory, ...)
cel2long(x, cels = x@chps, lowMemory = x@lowMemory, set = x@set, normalize = x@normalize,
log.intensities = x@logInt, ...)
cel2short(x, cels = x@chps, lowMemory = x@lowMemory, set = x@set, normalize = x@normalize,
log.intensities = x@logInt, ...)
cel2ras(x, cels = x@chps, lowMemory = x@lowMemory, set = x@set, normalize = x@normalize,
log.intensities = x@logInt, subtractMismatch = x@useMM, ...)
cel2rasS(x, cels = x@chps, lowMemory = x@lowMemory, set = x@set, normalize = x@normalize,
log.intensities = x@logInt, subtractMismatch = x@useMM, FUN = x@summary, ...)
raw2long(x, lowMemory = x@lowMemory, set = x@set, normalize = x@normalize,
log.intensities = x@logInt, tidy = FALSE, ...)
raw2short(x, lowMemory = x@lowMemory, set = x@set, normalize = x@normalize,
log.intensities = x@logInt, tidy = FALSE, ...)
raw2ras(x, lowMemory = x@lowMemory, set = x@set, normalize = x@normalize,
log.intensities = x@logInt, subtractMismatch = x@useMM, tidy = FALSE, ...)
raw2rasS(x, lowMemory = x@lowMemory, set = x@set, normalize = x@normalize,
log.intensities = x@logInt, subtractMismatch = x@useMM, FUN = x@summary,
tidy = FALSE, ...)
long2short(x, lowMemory = x@lowMemory, tidy = FALSE, ...)
long2ras(x, lowMemory = x@lowMemory, subtractMismatch = x@useMM, tidy = FALSE, ...)
long2rasS(x, lowMemory = x@lowMemory, subtractMismatch = x@useMM, FUN = x@summary,
tidy = FALSE, ...)
short2ras(x, lowMemory = x@lowMemory, subtractMismatch = x@useMM, tidy = FALSE, ...)
short2rasS(x, lowMemory = x@lowMemory, subtractMismatch = x@useMM, FUN = x@summary,
tidy = FALSE, ...)
ras2rasS(x, lowMemory = x@lowMemory, FUN = x@summary, tidy = FALSE, ...)
x |
An object of class SNPMaP. |
cels |
character; a vector of the CEL files to be included. |
lowMemory |
logical; should the SNP data be stored on disk rather than in memory? |
tidy |
logical; if the data is stored on disk, should the old FileDoubleMatrix be unlinked? |
set |
numeric; the set of probesets to include. See SNPMaP.cdm-package. |
normalize |
logical; quantile normalize probe intensities across arrays. |
log.intensities |
logical; take natural log of probe intensities. |
subtractMismatch |
logical; subtract mismatch probe intensities if available from perfect match intensities. |
FUN |
function; function to compute summary statistic for RAS on each chip. See SNPMaP-class. |
... |
additional arguments passed to other workflow and internal functions. |
The workflow functions work by calling cel2raw(), raw2long(), long2short(),
short2ras(), ras2rasS().
Object of class SNPMaP.
SNPMaP-package,
SNPMaP.cdm-package,
SNPMaP-class,
snpmap(),
norm(),
logIntensities()
## Not run:
## Getting started
## Creates the 'raw' SNPMaP object x on disk with mismatch probes included
x<-snpmap(useMM=TRUE, RUN='cel2raw', lowMemory=TRUE)
## Print a summary of the SNPMaP object
summary(x)
## Add a comment (prints in the summary)
comment(x)<-'High and low extreme pools from January'
## View pseudo image to screen for artefacts
image(x)
## Plot probe intensities
plot(x, FUN=log)
boxplot(x, FUN=log)
## tidy=TRUE removes the FileDoubleMatrix from the old x to keep the disk tidy
x<-raw2ras(x, tidy=TRUE)
## Plot Relative Allele Scores
plot(x)
## Default tidy=FALSE does not remove the original FileDoubleMatrix from disk
## Useful if you want to keep x (no side effects)
y<-ras2rasS(x)
## View the first ten rows
as.matrix(y[1:10,])
## View a set of SNPs
as.matrix(y[c("SNP_A-4192909", "SNP_A-4192918"),])
## Transfer the SNPMaP object from disk to memory
y<-disk2memory(y, tidy=TRUE)
## Run the analysis again from CEL files to RAS summaries without viewing intermediate stages
## This time in memory (may require a lot of RAM)
z<-snpmap(useMM=TRUE, RUN='cel2rasS', lowMemory=FALSE)
plot(z)
## Get the RAS summary scores as a standard matrix
rasSummaries<-as.matrix(z)
## Read all the sets into a list
allSets<-msnpmap(set=0)
## End(Not run)