Using the example from readNanoStringGeoMxSet and the example data provided by the GeomxTools package, can you show how one can construct the count, sample, and annotation data needed for the standR readGeoMx() function?
Here is the example from the docs:
datadir <- system.file("extdata", "DSP_NGS_Example_Data",
package="GeomxTools")
dccFiles <- dir(datadir, pattern=".dcc$", full.names=TRUE)
pkc <- unzip(zipfile = file.path(datadir, "/pkcs.zip"))
sampleAnnotationFile <- file.path(datadir, "annotations.xlsx")
dccFileColumn <- "Sample_ID"
dccSet <- readNanoStringGeoMxSet(dccFiles, pkcFile = pkc,
phenoDataFile = sampleAnnotationFile,
phenoDataSheet="CW005")
I have been going in circles for weeks now..
counts <- assayData(dccSet)[["exprs"]]
produces gene counts for each dcc file, not counts for each combination of ROI.
Using the example from
readNanoStringGeoMxSetand the example data provided by the GeomxTools package, can you show how one can construct the count, sample, and annotation data needed for the standR readGeoMx() function?Here is the example from the docs:
I have been going in circles for weeks now..
counts <- assayData(dccSet)[["exprs"]]produces gene counts for each dcc file, not counts for each combination of ROI.