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

 Package: lisaClust

 Type: Package

 Title: lisaClust: Clustering of Local Indicators of Spatial Association

-Version: 1.5.2

+Version: 1.5.3

 Authors@R: c(

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

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

@@ -1,6 +1,6 @@

 #' Generate local indicators of spatial association

 #'

-#' @param cells A SegmentedCells or data frame that contains at least the 

+#' @param 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.

 #' @param Rs A vector of the radii that the measures of association should be calculated.

 #' @param BPPARAM A BiocParallelParam object.

@@ -1,6 +1,6 @@

 #' Use k-means clustering to cluster local indicators of spatial association. For other clustering use lisa.

 #'

-#' @param cells A SegmentedCells or data frame that contains at least the 

+#' @param 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.

 #' @param k The number of regions to cluster.

 #' @param Rs A vector of the radii that the measures of association should be calculated.

@@ -126,6 +126,31 @@ lisaClust <-

         cellAnnotation(cells, regionName) <- regions

         }

+        

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

+            cd <- cells

+            cd <- cd[,c(cellType, imageID, spatialCoords)]

+            colnames(cd) <- c("cellType", "imageID", "x", "y")

+            cd$cellID <- as.character(seq_len(nrow(cd)))

+            cd$imageCellID <- as.character(seq_len(nrow(cd)))

+            cd <- spicyR::SegmentedCells(cd)

+            lisaCurves <- lisa(cd,

+                               Rs = Rs,

+                               BPPARAM = BPPARAM,

+                               window = window,

+                               window.length = window.length,

+                               whichParallel = whichParallel,

+                               sigma = sigma,

+                               lisaFunc = lisaFunc,

+                               minLambda = minLambda,

+                               fast = fast)

+            

+            kM <- kmeans(lisaCurves,k)

+            regions <- paste('region',kM$cluster,sep = '_')

+            cells[regionName] <- regions

+        }

+        

+        

      cells   

 }