Using a for loop for getting class-specific outputs from a S4 object. The S4 object is called data and is a large object.
for loop consits of 5 classes namely: 'fat' 'inflammation' 'muscle' 'glands' 'lumen'
tissues = c("fat","inflammation","muscle","glands","lumen")
tissues
for (i in tissues) {
print(i)
print(data$i)
}
Output:
'fat' 'inflammation' 'muscle' 'glands' 'lumen'
[1] "fat"
$`m424_inflammation_tic-normalization`
An object of class 'MSContinuousImagingExperiment'
<53400 feature, 169 pixel> imaging dataset
imageData(1): intensity
featureData(0):
pixelData(0):
metadata(11): ibd binary type universally unique identifier ...
files name
run(1): m424_inflammation_tic-normalization
raster dimensions: 507 x 164 x 1
coord(3): x = 1..507, y = 1..164, z = 1..1
mass range: 599.9313 to 3200.0906
centroided: FALSE
$`m80_inflammation_tic-normalization`
An object of class 'MSContinuousImagingExperiment'
<53400 feature, 149 pixel> imaging dataset
imageData(1): intensity
featureData(0):
pixelData(0):
metadata(11): ibd binary type universally unique identifier ...
files name
run(1): m80_inflammation_tic-normalization
raster dimensions: 400 x 212 x 1
coord(3): x = 1..400, y = 1..212, z = 1..1
mass range: 599.6025 to 3200.7207
centroided: FALSE
[1] "inflammation"
$`m424_inflammation_tic-normalization`
An object of class 'MSContinuousImagingExperiment'
<53400 feature, 169 pixel> imaging dataset
imageData(1): intensity
featureData(0):
pixelData(0):
metadata(11): ibd binary type universally unique identifier ...
files name
run(1): m424_inflammation_tic-normalization
raster dimensions: 507 x 164 x 1
coord(3): x = 1..507, y = 1..164, z = 1..1
mass range: 599.9313 to 3200.0906
centroided: FALSE
$`m80_inflammation_tic-normalization`
An object of class 'MSContinuousImagingExperiment'
<53400 feature, 149 pixel> imaging dataset
imageData(1): intensity
featureData(0):
pixelData(0):
metadata(11): ibd binary type universally unique identifier ...
files name
run(1): m80_inflammation_tic-normalization
raster dimensions: 400 x 212 x 1
coord(3): x = 1..400, y = 1..212, z = 1..1
mass range: 599.6025 to 3200.7207
centroided: FALSE
[1] "muscle"
$`m424_inflammation_tic-normalization`
An object of class 'MSContinuousImagingExperiment'
<53400 feature, 169 pixel> imaging dataset
imageData(1): intensity
featureData(0):
pixelData(0):
metadata(11): ibd binary type universally unique identifier ...
files name
run(1): m424_inflammation_tic-normalization
raster dimensions: 507 x 164 x 1
coord(3): x = 1..507, y = 1..164, z = 1..1
mass range: 599.9313 to 3200.0906
centroided: FALSE
$`m80_inflammation_tic-normalization`
An object of class 'MSContinuousImagingExperiment'
<53400 feature, 149 pixel> imaging dataset
imageData(1): intensity
featureData(0):
pixelData(0):
metadata(11): ibd binary type universally unique identifier ...
files name
run(1): m80_inflammation_tic-normalization
raster dimensions: 400 x 212 x 1
coord(3): x = 1..400, y = 1..212, z = 1..1
mass range: 599.6025 to 3200.7207
centroided: FALSE
[1] "glands"
$`m424_inflammation_tic-normalization`
An object of class 'MSContinuousImagingExperiment'
<53400 feature, 169 pixel> imaging dataset
imageData(1): intensity
featureData(0):
pixelData(0):
metadata(11): ibd binary type universally unique identifier ...
files name
run(1): m424_inflammation_tic-normalization
raster dimensions: 507 x 164 x 1
coord(3): x = 1..507, y = 1..164, z = 1..1
mass range: 599.9313 to 3200.0906
centroided: FALSE
$`m80_inflammation_tic-normalization`
An object of class 'MSContinuousImagingExperiment'
<53400 feature, 149 pixel> imaging dataset
imageData(1): intensity
featureData(0):
pixelData(0):
metadata(11): ibd binary type universally unique identifier ...
files name
run(1): m80_inflammation_tic-normalization
raster dimensions: 400 x 212 x 1
coord(3): x = 1..400, y = 1..212, z = 1..1
mass range: 599.6025 to 3200.7207
centroided: FALSE
[1] "lumen"
$`m424_inflammation_tic-normalization`
An object of class 'MSContinuousImagingExperiment'
<53400 feature, 169 pixel> imaging dataset
imageData(1): intensity
featureData(0):
pixelData(0):
metadata(11): ibd binary type universally unique identifier ...
files name
run(1): m424_inflammation_tic-normalization
raster dimensions: 507 x 164 x 1
coord(3): x = 1..507, y = 1..164, z = 1..1
mass range: 599.9313 to 3200.0906
centroided: FALSE
$`m80_inflammation_tic-normalization`
An object of class 'MSContinuousImagingExperiment'
<53400 feature, 149 pixel> imaging dataset
imageData(1): intensity
featureData(0):
pixelData(0):
metadata(11): ibd binary type universally unique identifier ...
files name
run(1): m80_inflammation_tic-normalization
raster dimensions: 400 x 212 x 1
coord(3): x = 1..400, y = 1..212, z = 1..1
mass range: 599.6025 to 3200.7207
centroided: FALSE
The code should output data$fat followed by data$inflammation, data$muscle, data$glands, data$lumen.
However it only outputs data$inflammation
data$i is the problem. Use data[[i]] instead. data$i searches for the element of the list which is called "i", since there is no such element it autocompletes data$i to data$inflammation.
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