read.cel.complete {affxparser} | R Documentation |
Parsing an Affymetrix CEL file using the Fusion SDK. The intention is to let users obtain all (but possibly a subset of) information in the CEL file.
read.cel.complete(fname, indices = NULL, read.intensities = TRUE, read.stdvs = TRUE, read.pixels = TRUE, read.xy = FALSE, read.outliers = TRUE, read.masked = TRUE, verbose = 0)
fname |
the name of the CEL file. |
indices |
a vector of indices indicating which features to
read. If the argument is NULL all features will be returned. |
read.intensities |
a logical: will the intensities be returned. |
read.stdvs |
a logical: will the standard deviations be returned. |
read.pixels |
a logical: will the number of pixels be returned. |
read.xy |
a logical: will the (x,y) coordinates be returned. |
read.outliers |
a logical: will the outliers be return. |
read.masked |
a logical: will the masked features be returned. |
verbose |
how verbose do we want to be. 0 is no verbosity, higher numbers mean more verbose output. At the moment the values 1 and 2 are supported. |
This function reads everything from a CEL file. It is considered a bug if the file contains information not accessible by this function, please report it.
The (input and output) interface makes heavily use of the concept of indices. An (x,y) coordinate is converted to an integer by the formula (y + 1) times numberOfColsInCelFile + (x + 1), assuming that the (x,y) coordinates start at (0,0).
The file returns a list with components (possible empty
depending on the input flags) corresponding to the various flags. The
outliers
and masked
components are special in that they
are vectors of indices of features flagged as respectively
outlier/masked by the Affymetrix image software.
A named list with components described
below. The order of the intensities
, stdvs
and
pixels
corresponds to the ordering of the indices
argument.
header |
The header of the CEL file. Equivalent to the output
from read.cel.header , see the documentation for that function. |
intensities |
A vector of mode nummeric containing the
intensity associated with each feature, unless read.intensities
= FALSE in which case it will be NULL . Restricted to features
within the indices range. |
stdvs |
A vector of mode nummeric containing the
standard deviation associated with each feature, unless
read.stdvs = FALSE in which case it will be
NULL . Restricted to features within the indices range. |
pixels |
A vector of mode integer containing the
number of pixels associated with each feature, unless
read.pixels = FALSE in which case it will be
NULL . Restricted to features within the indices range. |
x |
A vector of mode integer containing the x coordinate
associated with each feature, unless read.xy = FALSE
in which case it will be NULL . Restricted to features with the
indices range. |
y |
A vector of mode integer containing the y coordinate
associated with each feature, unless read.xy = FALSE
in which case it will be NULL . Restricted to features with the
indices range. |
outliers |
A vector of mode integer which the indices of
the features flagged as outliers, unless read.outliers = NULL
in which case it will be NULL . Note that there is a difference
between outliers = NULL and outliers = integer(0) - the
last case happens when read.outliers = TRUE but there are no
outliers. In case an indices argument is given, only indices
within the indices argument are returned. |
masked |
A vector of mode integer which the indices of
the features flagged as masked, unless read.masked = NULL
in which case it will be NULL . Note that there is a difference
between masked = NULL and masked = integer(0) - the
last case happens when read.masked = TRUE but there are no
masked features. In case an indices argument is given, only indices
within the indices argument are returned. |
Memory usage: the Fusion SDK allocates memory for the entire
CEL file, when the file is accessed (but does not actually read the
file into memory). Using the indices
argument will therefore
only affect the memory use of the final object (as well as speed), not
the memory allocated in the C function used to parse the file. This
should be a minor problem however.
The outlier/masked flag are computed by the Affymetrix image analysis software. The current community view seems to be that this should be done based on statistical modelling of the actual probe intensities and should be based on the choice of preprocessing algorithm. Mopst algorithms are only using the intensities from the CEL file.
James Bullard, bullard@stat.berkeley.edu and Kasper Daniel Hansen, khansen@stat.berkeley.edu
affxparserInfo
for a package overview and
read.cel.header
for a description of the header
output. Often a user only wants to read the intensities, look at
read.cel.intensities
for a function specialized for that
use. See xy2indices
from affy and
xy2i
from makePlatformDesign for a discussion of
the index approach.
## Not run: read.cel.complete("~/testFile.CEL", read.npixels = FALSE) ## End(Not run)