read.ilmn(files=NULL, ctrlfiles=NULL, path=NULL, ctrlpath=NULL, probeid="Probe", annotation=c("TargetID", "SYMBOL"), expr="AVG_Signal", other.columns="Detection", sep="\t", quote="\"", verbose=TRUE, ...)
Detection
is usually sufficient to identify the columns containing detection p-values.TRUE
to report names of profile files being read.read.columns
.EListRaw-class
object with the following components:
annotation
that are found in the input files.other.columns
found in the input files.files
and ctrlfiles
are not NULL
, this function will combine the data read from the two file types and save them to an EListRaw-class
object.
If one of them is NULL
, then only the required data are read in.Probe types are indicated in the Status
column of genes
, a component of the returned EListRaw-class
object.
There are totally seven types of control probes including negative
, biotin
, labeling
, cy3_hyb
, housekeeping
, high_stringency_hyb
or low_stringency_hyb
.
Regular probes have the probe type regular
.
The Status
column will not be created if ctrlfiles
is NULL
.
To read in columns other than probeid
, annotation
and expr
, users needs to specify keywords in other.columns
.
One keyword corresponds to one type of columns.
Examples of keywords are "Detection", "Avg_NBEADS", "BEAD_STDEV" etc.
read.ilmn.targets
reads in Illumina expression data using the file information extracted from a target data frame which is often created by the readTargets
function.
neqc
performs normexp by control background correction, log transformation and quantile between-array normalization for Illumina expression data.
normexp.fit.control
estimates the parameters of the normal+exponential convolution model with the help of negative control probes.
propexpr
estimates the proportion of expressed probes in a microarray.
## Not run:
# x <- read.ilmn(files="sample probe profile.txt",
# ctrlfiles="control probe profile.txt")
# ## End(Not run)
# See neqc and beadCountWeights for other examples using read.ilmn
Run the code above in your browser using DataLab