Description Usage Arguments Details Value Author(s) See Also Examples
Instantiates an object of class CNSet for the Infinium
platforms. Elements of assayData
and
batchStatistics
will be ff
objects. See details.
1 2 3 |
sampleSheet |
|
arrayNames |
character vector containing names of arrays to be
read in. If |
path |
character string specifying the location of files to be read by the function |
arrayInfoColNames |
(used when |
highDensity |
logical (used when |
sep |
character string specifying separator used in .idat file names. |
fileExt |
list containing elements 'Green' and 'Red' which specify the .idat file extension for the Cy3 and Cy5 channels. |
XY |
an |
cdfName |
annotation package (see also |
verbose |
'logical.' Whether to print descriptive messages during processing. |
batch |
batch variable. See details. |
saveDate |
'logical'. Should the dates from each .idat be saved with sample information? |
This function initializes a container for storing the normalized intensities for the A and B alleles at polymorphic loci and the normalized intensities for the 'A' allele at nonpolymorphic loci. CRLMM genotype calls and confidence scores are also stored in the assayData. This function does not do any preprocessing or genotyping – it only creates an object of the appropriate size. The initialized values will all be 'NA'.
The ff package provides infrastructure for accessing and writing
data to disk instead of keeping data in memory. Each element of
the assayData
and batchStatistics
slot are ff
objects. ff objects in the R workspace contain pointers to
several files with the '.ff' extension on disk. The location of
where the data is stored on disk can be specified by use of the
ldPath
function. Users should not move or rename this
directory. If only output files are stored in ldPath
,
one can either remove the entire directory prior to rerunning
the analysis or all of the '.ff' files. Otherwise, one would
accumulate a large number of '.ff' files on disk that are no
longer in use.
We have adopted the ff
package in order to reduce crlmm's
memory footprint. The memory usage can be fine-tuned by the
utilities ocSamples
and ocProbesets
provided in
the oligoClasses
package. In most instances, the
user-level interface will be no different than accessing data
from ordinary matrices in R. However, the differences in the
underlying representation can become more noticeable for very
large datasets in which the I/O for accessing data from the disk
can be substantial.
A CNSet
object
R. Scharpf
ldPath
, ocSamples
, ocProbesets
, CNSet-class
, preprocessInf
, genotypeInf
1 2 | ## See the Illumina vignettes in inst/scripts of the
## source package for an example
|
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