SegmentedCellExperiment: The SegmentedCellExperiment class

In ellispatrick/SegmentedCellExperiment: S4 Class for segmented spatial 'omics data

Description

The SegmentedCellExperiment class

Usage

SegmentedCellExperiment(
  cellData,
  cellProfiler = FALSE,
  spatialCoords = NULL,
  cellTypeString = NULL,
  intensityString = NULL,
  morphologyString = NULL,
  cellIDString = NULL,
  imageCellIDString = NULL,
  imageIDString = NULL
)

Arguments

cellData	A data frame that contains at least the columns x and y giving the location of each cell.
cellProfiler	A logical indicating that cellData is in a format similar to what cellProfiler outputs.
spatialCoords	The column names corresponding to spatial coordinates. eg. x, y, z...
cellTypeString	The name of the column that contains cell type calls.
intensityString	A string which can be used to identify the columns which contain marker intensities. (This needs to be extended to take the column names themselves.)
morphologyString	A string which can be used to identify the columns which contains morphology information.
cellIDString	The column name for cellID.
imageCellIDString	The column name for imageCellID.
imageIDString	The column name for imageIDString

Value

A SegmentedCellExperiment object

Examples

### Something that resembles cellProfiler data

set.seed(51773)

n = 10

cells <- data.frame(row.names = seq_len(n))
cells$ObjectNumber <- seq_len(n)
cells$ImageNumber <- rep(1:2,c(n/2,n/2))
cells$AreaShape_Center_X <- runif(n)
cells$AreaShape_Center_Y <- runif(n)
cells$AreaShape_round <- rexp(n)
cells$AreaShape_diameter <- rexp(n, 2)
cells$Intensity_Mean_CD8 <- rexp(n, 10)
cells$Intensity_Mean_CD4 <- rexp(n, 10)

cellExp <- SegmentedCellExperiment(cells, cellProfiler = TRUE)

### Cluster cell types
intensities <- intensity(cellExp)
kM <- kmeans(intensities,2)
cellType(cellExp) <- paste('cluster',kM$cluster, sep = '')
location(cellExp)

ellispatrick/SegmentedCellExperiment documentation built on Feb. 24, 2020, 3:14 p.m.