imcExperiment-class: a summarized experiment of IMC runs, dimensions of the...
In arcolombo/imcExperiment: Mass Cytometry S4 Class Structure Pipeline for Images

Description Usage Arguments Value Slots Examples

a summarized experiment of IMC runs, dimensions of the spatial and intensity data are regulated.#'

finds the network information.

assigns cell cluster assignment to the container. rows are cells and column is the cluster ID

finds the distance information.

distance matrix can be stored in the distance slot for pairwise distance

finds the morphology information.

morphological features can be stored (matrix) rows are cells and columns are Area, etc.

finds the label information.

unique cell labels can be assigned (vector)

getNetwork(object)

## S4 method for signature 'imcExperiment'
getNetwork(object)

## S4 replacement method for signature 'imcExperiment,data.frame'
getNetwork(object) <- value

getDistance(object)

## S4 method for signature 'imcExperiment'
getDistance(object)

## S4 replacement method for signature 'imcExperiment,matrix'
getDistance(object) <- value

getMorphology(object)

## S4 method for signature 'imcExperiment'
getMorphology(object)

## S4 replacement method for signature 'imcExperiment,matrix'
getMorphology(object) <- value

getLabel(object)

## S4 method for signature 'imcExperiment'
getLabel(object)

`object`	imcExperiment
`value`	matrix rows cells, columns are Area, etc.

imcExperiment container

coordinates: matrix class containing x,y coordinates
cellIntensity: matrix class containing intensity
neighborHood: matrix class containing x,y neighbor
network: data frame class containing network
distance: matrix class containing x,y distances
morphology: matrix class containing morphology
uniqueLabel: labels

x<-imcExperiment(cellIntensity=matrix(1,nrow=10,ncol=10),
coordinates=matrix(1,nrow=10,ncol=2),
neighborHood=matrix(1,nrow=10,ncol=10),
network=data.frame(matrix(1,nrow=10,ncol=10)),
distance=matrix(1,nrow=10,ncol=10),
morphology=matrix(1,nrow=10,ncol=10),
uniqueLabel=paste0("A",seq_len(10)),
panel=letters[1:10],
ROIID=data.frame(ROIID=rep("A",10)))
data(imcdata)
getNetwork(imcdata)
data(imcdata)
getNetwork(imcdata)
data(imcdata)
x<-data.frame(ID=seq_len(ncol(imcdata)))
getNetwork(imcdata)<-x
data(imcdata)
getDistance(imcdata)
data(imcdata)
getDistance(imcdata)
data(imcdata)
newD<-matrix(1,nrow=ncol(imcdata),ncol=1)
getDistance(imcdata)<-newD
data(imcdata)
getMorphology(imcdata)
data(imcdata)
getMorphology(imcdata)
data(imcdata)
x<-matrix(1,nrow=ncol(imcdata),ncol=4)
getMorphology(imcdata)<-x
data(imcdata)
getLabel(imcdata)
data(imcdata)
getLabel(imcdata)