@@ -1,7 +1,7 @@

 Package: lisaClust

 Type: Package

 Title: lisaClust: Clustering of Local Indicators of Spatial Association

-Version: 1.5.4

+Version: 1.5.5

 Authors@R: c(

     person("Ellis", "Patrick", email = "[email protected]",

     role = c("aut", "cre")),

@@ -22,6 +22,6 @@ BugReports: https://github.com/ellispatrick/lisaClust/issues

 Imports: ggplot2, class, concaveman, grid, BiocParallel, spatstat.core,

         spatstat.geom, BiocGenerics, S4Vectors, methods, spicyR,

         purrr, stats, data.table, dplyr, tidyr, SingleCellExperiment, SpatialExperiment,

-        SummarizedExperiment

+        SummarizedExperiment, pheatmap

 Suggests: BiocStyle, knitr, rmarkdown

 RoxygenNote: 7.2.0

@@ -4,6 +4,7 @@ export(geom_hatching)

 export(hatchingPlot)

 export(lisa)

 export(lisaClust)

+export(regionMap)

 export(scale_region)

 export(scale_region_manual)

 import(SingleCellExperiment)

@@ -26,6 +27,7 @@ importFrom(data.table,setkey)

 importFrom(dplyr,.data)

 importFrom(dplyr,bind_rows)

 importFrom(dplyr,left_join)

+importFrom(dplyr,mutate)

 importFrom(ggplot2,aes)

 importFrom(ggplot2,discrete_scale)

 importFrom(ggplot2,facet_wrap)

@@ -33,6 +35,7 @@ importFrom(ggplot2,geom_point)

 importFrom(ggplot2,ggplot)

 importFrom(ggplot2,labs)

 importFrom(ggplot2,layer)

+importFrom(ggplot2,scale_colour_gradient2)

 importFrom(ggplot2,theme_minimal)

 importFrom(grid,gList)

 importFrom(grid,gpar)

@@ -41,6 +44,7 @@ importFrom(grid,grobTree)

 importFrom(grid,linesGrob)

 importFrom(grid,polylineGrob)

 importFrom(methods,is)

+importFrom(pheatmap,pheatmap)

 importFrom(purrr,map)

 importFrom(purrr,map_dfr)

 importFrom(spatstat.core,density.ppp)

@@ -537,3 +537,78 @@ prepCellSummary <- function(cells, spatialCoords, cellType, imageID){

 }

+

+

+#' Plot heatmap of cell type enrichment for lisaClust regions

+#'

+#' @param cells SegmentedCells, SingleCellExperiment, SpatialExperiment or data.frame

+#' @param type Make a "bubble" or "heatmap" plot.

+#' @param region The column storing the regions

+#' @param cellType The column storing the cell types

+#' @param limit limits to the lower and upper relative frequencies

+#' @param ... Any arguments to be passed to the pheatmap package

+#'

+#' @return A bubble plot or heatmap

+#'

+#'

+#' @examples

+#' set.seed(51773)

+#'x <- round(c(runif(200),runif(200)+1,runif(200)+2,runif(200)+3,

+#'             runif(200)+3,runif(200)+2,runif(200)+1,runif(200)),4)*100

+#'y <- round(c(runif(200),runif(200)+1,runif(200)+2,runif(200)+3,

+#'             runif(200),runif(200)+1,runif(200)+2,runif(200)+3),4)*100

+#'cellType <- factor(paste('c',rep(rep(c(1:2),rep(200,2)),4),sep = ''))

+#'imageID <- rep(c('s1', 's2'),c(800,800))

+#'

+#'cells <- data.frame(x, y, cellType, imageID)

+#'

+#'cellExp <- spicyR::SegmentedCells(cells, cellTypeString = 'cellType')

+#'

+#'cellExp <- lisaClust(cellExp, k = 2)

+#'

+#'regionMap(cellExp)

+#'

+#' @export

+#' @importFrom SummarizedExperiment colData

+#' @importFrom pheatmap pheatmap

+#' @importFrom ggplot2 ggplot aes geom_point scale_colour_gradient2 theme_minimal labs

+#' @importFrom dplyr mutate

+#' @import SpatialExperiment SingleCellExperiment

+regionMap <- function(cells, type = "bubble", cellType = "cellType", region = "region", limit = c(0.33,3), ...) {

+  

+  if (is.data.frame(cells)) {

+    df <- cells[,c(cellType, region)]

+  }

+  

+  if (is(cells, "SingleCellExperiment")|is(cells, "SpatialExperiment")) {

+    df <- as.data.frame(SummarizedExperiment::colData(cells))[,c(cellType, region)]

+  }

+  

+  if (is(cells, "SegmentedCells")) {

+    cellSummary <- cellSummary(cells, bind = TRUE)

+    df <- as.data.frame(cellSummary[,c(cellType, region)])

+  }

+  

+  tab <- table(df[,cellType], df[,region])

+  tab <- tab/rowSums(tab)%*%t(colSums(tab))*sum(tab)

+  

+  ph <- pheatmap::pheatmap(pmax(pmin(tab,limit[2]),limit[1]), cluster_cols = FALSE, silent = TRUE, ...)

+  

+  if(type == "bubble"){

+  

+  p1 <- tab |>

+    as.data.frame() |>

+    dplyr::mutate(cellType = factor(Var1, levels = levels(Var1)[ph$tree_row$order]), region = Var2, Freq2 = pmax(pmin(Freq,limit[2]),limit[1])) |>

+    ggplot2::ggplot(ggplot2::aes(x = region, y = cellType, colour = Freq2, size = Freq2)) + 

+    ggplot2::geom_point() + 

+    ggplot2::scale_colour_gradient2(low ="#4575B4", mid = "grey90", high = "#D73027", midpoint = 1, guide = "legend") + 

+    ggplot2::theme_minimal() + 

+    ggplot2::labs(x = "Region", y = "Cell-type", colour = "Relative\nFrequency", size = "Relative\nFrequency") 

+  

+  return(p1)

+  }

+  

+  pheatmap::pheatmap(pmax(pmin(tab,limit[2]),limit[1]), cluster_cols = FALSE, ...)

+  

+}

+

@@ -21,7 +21,7 @@ lisa(

 )

 }

 \arguments{

-\item{cells}{A SegmentedCells or data frame that contains at least the 

+\item{cells}{A SegmentedCells, SingleCellExperiment, SpatialExperiment or data frame that contains at least the 

 variables x and y, giving the  coordinates of each cell, imageID and cellType.}

 \item{Rs}{A vector of the radii that the measures of association should be calculated.}

@@ -23,7 +23,7 @@ lisaClust(

 )

 }

 \arguments{

-\item{cells}{A SegmentedCells or data frame that contains at least the 

+\item{cells}{A SegmentedCells, SingleCellExperiment, SpatialExperiment or data frame that contains at least the 

 variables x and y, giving the  coordinates of each cell, imageID and cellType.}

 \item{k}{The number of regions to cluster.}

new file mode 100644

@@ -0,0 +1,52 @@

+% Generated by roxygen2: do not edit by hand

+% Please edit documentation in R/LISA.R

+\name{regionMap}

+\alias{regionMap}

+\title{Plot heatmap of cell type enrichment for lisaClust regions}

+\usage{

+regionMap(

+  cells,

+  type = "bubble",

+  cellType = "cellType",

+  region = "region",

+  limit = c(0.33, 3),

+  ...

+)

+}

+\arguments{

+\item{cells}{SegmentedCells, SingleCellExperiment, SpatialExperiment or data.frame}

+

+\item{type}{Make a "bubble" or "heatmap" plot.}

+

+\item{cellType}{The column storing the cell types}

+

+\item{region}{The column storing the regions}

+

+\item{limit}{limits to the lower and upper relative frequencies}

+

+\item{...}{Any arguments to be passed to the pheatmap package}

+}

+\value{

+A bubble plot or heatmap

+}

+\description{

+Plot heatmap of cell type enrichment for lisaClust regions

+}

+\examples{

+set.seed(51773)

+x <- round(c(runif(200),runif(200)+1,runif(200)+2,runif(200)+3,

+            runif(200)+3,runif(200)+2,runif(200)+1,runif(200)),4)*100

+y <- round(c(runif(200),runif(200)+1,runif(200)+2,runif(200)+3,

+            runif(200),runif(200)+1,runif(200)+2,runif(200)+3),4)*100

+cellType <- factor(paste('c',rep(rep(c(1:2),rep(200,2)),4),sep = ''))

+imageID <- rep(c('s1', 's2'),c(800,800))

+

+cells <- data.frame(x, y, cellType, imageID)

+

+cellExp <- spicyR::SegmentedCells(cells, cellTypeString = 'cellType')

+

+cellExp <- lisaClust(cellExp, k = 2)

+

+regionMap(cellExp)

+

+}

@@ -286,6 +286,16 @@ cellAnnotation(cellExp, "region") |>

 ```

+## Examine cell type enrichment

+

+We should check to see which cell types appear more frequently in each region than

+expected by chance. 

+

+```{r}

+regionMap(cellExp, type = "bubble")

+```

+

+

 ## Plot identified regions