Updated

DESCRIPTION

@@ -2,8 +2,8 @@ Package: espresso
 Type: Package
 Title: Enhanced spatial reconstruction by stochastic self-organizing
         map
-Version: 1.0.0
-Date: 2022-01-21
+Version: 1.0.1
+Date: 2022-03-04
 Authors@R: person("Tomoya", "Mori", role = c("aut", "cre"), email = "[email protected]")
 Description: This is a package for domain estimation of cells only from gene expression profile based on graph-structured stochastic self-organizing map (GraphSOM) and Markov chain Monte Carlo (MCMC) method.
 License: GPL-3
@@ -18,6 +18,6 @@ LazyData: true
 Suggests: knitr, rmarkdown
 VignetteBuilder: knitr
 NeedsCompilation: no
-Packaged: 2022-01-21 06:50:12 UTC; tmori
+Packaged: 2022-03-31 07:45:12 UTC; tmori
 Author: Tomoya Mori [aut, cre]
 Maintainer: Tomoya Mori <[email protected]>

NAMESPACE

@@ -18,6 +18,7 @@ import(Boruta)
 import(RColorBrewer)
 import(doParallel)
 import(foreach)
+import(grid)
 import(parallel)
 import(progress)
 import(rFerns)

NEWS.md

@@ -1,3 +1,9 @@
+## 1.0.1
+* Modify the argument name from `version="0.2.17` to `version="0"` to run SOM in the previous version.
+* Default output format of `plotUMAP` is changed from "pdf" to "png".
+* Modify labels of legend in distance map to discrete ones.
+
+
 ## 1.0.0
 * Add an option `version` to `graphSOM` and `rxmcmc` functions in order to enable us to perform SOM computations based on the previous version (= 0.2.17).
 

R/distancemap.R

@@ -10,6 +10,7 @@
 #' @importFrom pheatmap pheatmap
 #' @importFrom grDevices colorRampPalette
 #' @import RColorBrewer
+#' @import grid unit
 #' @export
 #' 
 plotDistMap <- function(obj, type = "b", size_d = NULL, size_s = 5) {
@@ -22,16 +23,27 @@ plotDistMap <- function(obj, type = "b", size_d = NULL, size_s = 5) {
 
       # Plot distance maps of domains before GraphSOM ------------------------
       if (!is.null(size_d)) {
-        pheatmap(distmat, cluster_cols = F, cluster_rows = F, 
-                 color = colorRampPalette(brewer.pal(n = 7, name = "Blues"))(100), na_col = "black",
-                 main = "Distance of domains", 
-                 fontsize_row = size_d, fontsize_col = size_d,
-                 cellheight = size_d, cellwidth = size_d
-                 )
+        p <- pheatmap(distmat, cluster_cols = F, cluster_rows = F, 
+                      color = colorRampPalette(brewer.pal(n = 7, name = "Blues"))(max(eobj@dist[eobj@dist != Inf]) + 1), na_col = "black",
+                      main = "Distance of domains", 
+                      fontsize_row = size_d, fontsize_col = size_d,
+                      cellheight = size_d, cellwidth = size_d, silent = T,
+                      legend_breaks = 0:max(eobj@dist[eobj@dist != Inf]),
+                      legend_labels = 0:max(eobj@dist[eobj@dist != Inf])
+                      )
+        p <- .modLabelPositions(p)
+        plot.new()
+        print(p)
       } else {
-        pheatmap(distmat, cluster_cols = F, cluster_rows = F, 
-                 color = colorRampPalette(brewer.pal(n = 7, name = "Blues"))(100), na_col = "black",
-                 main = "Distance of domains")
+        p <- pheatmap(distmat, cluster_cols = F, cluster_rows = F, 
+                      color = colorRampPalette(brewer.pal(n = 7, name = "Blues"))(max(eobj@dist[eobj@dist != Inf]) + 1), na_col = "black",
+                      main = "Distance of domains", silent = T, 
+                      legend_breaks = 0:max(eobj@dist[eobj@dist != Inf]),
+                      legend_labels = 0:max(eobj@dist[eobj@dist != Inf])
+                      )
+        p <- .modLabelPositions(p)
+        plot.new()
+        print(p)
       }
     } 
     if (type == "s" || type == "b") {
@@ -55,13 +67,19 @@ plotDistMap <- function(obj, type = "b", size_d = NULL, size_s = 5) {
         } else {
           main_title <- paste("Distance of sample cells\n(rept.", i, ")", sep ="")
         }
-        pheatmap(sample_dist, 
-                 cluster_cols = F, cluster_rows = F, 
-                 fontsize_row = size_s, fontsize_col = size_s, 
-                 cellheight = size_s, cellwidth = size_s, 
-                 color = colorRampPalette(brewer.pal(n = 7, name = "Blues"))(100), na_col = "black",
-                 main = main_title
+        p <- pheatmap(sample_dist, 
+                      cluster_cols = F, cluster_rows = F, 
+                      fontsize_row = size_s, fontsize_col = size_s, 
+                      cellheight = size_s, cellwidth = size_s, 
+                      color = colorRampPalette(brewer.pal(n = 7, name = "Blues"))(max(eobj@dist[eobj@dist != Inf]) + 1), na_col = "black",
+                      main = main_title,  silent = T,
+                      legend_breaks = 0:max(eobj@dist[eobj@dist != Inf]),
+                      legend_labels = 0:max(eobj@dist[eobj@dist != Inf])
         )
+        p <- .modLabelPositions(p)
+        plot.new()
+        print(p)
+
         for (repl in names(obj@bmu)) {
           # Plot distance maps of samples after GraphSOM -------------------------
           if (!is.null(obj@bmu)) {
@@ -97,13 +115,18 @@ plotDistMap <- function(obj, type = "b", size_d = NULL, size_s = 5) {
             }
             vec <- as.vector(sample_dist2)
             if (length(unique(vec[!is.na(vec)])) != 1) {
-              pheatmap(sample_dist2,
-                       cluster_cols = F, cluster_rows = F, 
-                       fontsize_row = size_s, fontsize_col = size_s, 
-                       cellheight = size_s, cellwidth = size_s,  
-                       color = colorRampPalette(brewer.pal(n = 7, name = "Blues"))(100), na_col = "black",
-                       main = main_title
+              p <- pheatmap(sample_dist2,
+                            cluster_cols = F, cluster_rows = F, 
+                            fontsize_row = size_s, fontsize_col = size_s, 
+                            cellheight = size_s, cellwidth = size_s,  
+                            color = colorRampPalette(brewer.pal(n = 7, name = "Blues"))(max(eobj@dist[eobj@dist != Inf]) + 1), na_col = "black",
+                            main = main_title, silent = T,
+                            legend_breaks = 0:max(eobj@dist[eobj@dist != Inf]),
+                            legend_labels = 0:max(eobj@dist[eobj@dist != Inf])
               )
+              p <- .modLabelPositions(p)
+              plot.new()
+              print(p)
               # Plot distance maps of samples before/after GraphSOM -------------------
               ds <- sample_dist
               ds[upper.tri(ds)] <- sample_dist2[upper.tri(sample_dist2)]
@@ -124,13 +147,18 @@ plotDistMap <- function(obj, type = "b", size_d = NULL, size_s = 5) {
                   main_title <- paste("Distance of sample cells \nin original (lower) and after GraphSOM (upper)\n(rept.", i, ")", sep = "")
                 }
               }
-              pheatmap(ds, 
-                       cluster_cols = F, cluster_rows = F, 
-                       fontsize_row = size_s, fontsize_col = size_s, 
-                       cellheight = size_s, cellwidth = size_s, 
-                       color = colorRampPalette(brewer.pal(n = 7, name = "Blues"))(100), na_col = "black",
-                       main = main_title
+              p <- pheatmap(ds, 
+                            cluster_cols = F, cluster_rows = F, 
+                            fontsize_row = size_s, fontsize_col = size_s, 
+                            cellheight = size_s, cellwidth = size_s, 
+                            color = colorRampPalette(brewer.pal(n = 7, name = "Blues"))(max(eobj@dist[eobj@dist != Inf]) + 1), na_col = "black",
+                            main = main_title, silent = T,
+                            legend_breaks = 0:max(eobj@dist[eobj@dist != Inf]),
+                            legend_labels = 0:max(eobj@dist[eobj@dist != Inf])
               )
+              p <- .modLabelPositions(p)
+              plot.new()
+              print(p)
             } else {
               warning("Distance map after graph-SOM clustering cannot be drown since only one cluseter was generated.")
             }
@@ -139,4 +167,29 @@ plotDistMap <- function(obj, type = "b", size_d = NULL, size_s = 5) {
       }
     }
   }
+}
+
+
+
+# =============================================================================
+#' @title Modify label positions.
+#' @description This function modifies positions of labels
+#' @param p \code{pheatmap} object.
+#' @importFrom pheatmap pheatmap
+#' @import grid unit
+#' 
+.modLabelPositions <- function(p) {
+  N_col_areas <- length(p$gtable$grobs[[5]]$children[[1]]$y)
+  N_labels <- length(p$gtable$grobs[[5]]$children[[2]]$label)
+  yseq1 <- seq(0, 1, length.out=N_col_areas)
+  center <- yseq1[2]/2
+  yseq2 <- seq(center, 1-center, length.out=N_labels)
+
+  for (k in 1:(N_labels)) {
+    p$gtable$grobs[[5]]$children[[2]]$y[[k]] <- 
+      sum(yseq2[k]*min(unit(1,"npc"), unit(150,"bigpts")), 
+          unit(1,"npc"), 
+          -1*min(unit(1,"npc"), unit(150,"bigpts")))
+  }
+  return(p)
 }

R/graphsom.R

@@ -607,7 +607,7 @@ initGraphSOM <- function(obj, nsamples = NULL, rept = 1,
 #' @param gset Gene set.
 #' @param seed Random seed.
 #' @param verbose Whether to show messages.
-#' @param version Character that specifies on which previous version GraphSOM computation should be performed. (e.g., "0.2.17")
+#' @param version Character that specifies on which previous version GraphSOM computation should be performed. (e.g., "0")
 #' @return \code{espresso} object
 #' @export 
 #' 
@@ -616,7 +616,7 @@ graphSOM <- function(obj, gset = NULL, seed = NULL, verbose = TRUE, version = NU
     if (!is.null(seed)) {
       set.seed(seed, kind = "L'Ecuyer-CMRG")
     }
-  } else if (version == "0.2.17") {
+  } else if (version == "0") {
     if (!is.null(seed)) {
       set.seed(seed, kind = "Mersenne-Twister")
     }

R/rxmcmc.R

@@ -207,7 +207,7 @@
 #' @param n_repl Number of replicas (default: \code{detectCores()}).
 #' @param n_ig Number of initial genes randomly selected for MCMC.
 #' @param fact Scaling factor for computing selection probability.
-#' @param version Character that specifies on which previous version GraphSOM computation should be performed. (e.g., "0.2.17")
+#' @param version Character that specifies on which previous version GraphSOM computation should be performed. (e.g., "0")
 #' @import doParallel
 #' @import parallel
 #' @import foreach
@@ -226,7 +226,7 @@ rxmcmc <- function(obj, gset = NULL, temp = 1.0, itr = 10, k = 1, seed = NULL,
     warning("Input `gset` to be optimized.")
     return(obj)
   }
-  if (version != "0.2.17" && !is.null(version)) {
+  if (version != "0" && !is.null(version)) {
     stop(paste("version", version, "is not available."))
     return(obj)
   }
@@ -297,9 +297,9 @@ rxmcmc <- function(obj, gset = NULL, temp = 1.0, itr = 10, k = 1, seed = NULL,
           score_tmp[[l]] <- res_tmp@score
           summary_tmp[[l]] <- res_tmp@summary
         }
-      } else if (version == "0.2.17"){
+      } else if (version == "0"){
         for (l in 1:n_sets) {
-          res_tmp <- graphSOM(obj, gset = cand_sets[[l]], verbose = FALSE, version = "0.2.17")
+          res_tmp <- graphSOM(obj, gset = cand_sets[[l]], verbose = FALSE, version = "0")
           res[l, ] <- c(as.numeric(unlist(res_tmp@summary)), length(cand_sets[[l]]))
           map_tmp[[l]] <- res_tmp@map
           bmu_tmp[[l]] <- res_tmp@bmu

R/umap.R

@@ -149,7 +149,7 @@ runUMAP <- function(obj, umap_param = NULL, gset = NULL, seed = 0) {
 #' @importFrom scatterplot3d scatterplot3d
 #' @importFrom tagcloud smoothPalette
 #' @export
-plotUMAP <- function(obj, file = "umap.pdf", 
+plotUMAP <- function(obj, file = "umap.png", 
                      movie = FALSE, dir = ".",
                      mname = "movie",
                      seed = 0,

README.md

@@ -1,6 +1,6 @@
 # eSPRESSO
 
-21-Jan-2022: espresso 1.0.0 released.
+31-Mar-2022: espresso 1.0.1 released.
 
 <br/>
 

inst/doc/espresso.R

@@ -276,10 +276,10 @@ knitr::include_graphics("umap_3D_color3.png")
 knitr::include_graphics("umap.all.png")
 
 ## ---- eval = FALSE------------------------------------------------------------
-#  graphSOM(eobj, gset = fgenes, seed = 0, version = "0.2.17")
+#  graphSOM(eobj, gset = fgenes, seed = 0, version = "0")
 
 ## ---- eval = FALSE------------------------------------------------------------
-#  rxmcmc(eobj, gset = fgenes, itr = 2, n_ex = 5, n_repl = 4, n_cl = 4, seed = 0, version = "0.2.17")
+#  rxmcmc(eobj, gset = fgenes, itr = 2, n_ex = 5, n_repl = 4, n_cl = 4, seed = 0, version = "0")
 
 ## ---- eval=FALSE--------------------------------------------------------------
 #  library(biomaRt)

inst/doc/espresso.Rmd

@@ -1,6 +1,6 @@
 ---
 title: "espresso"
-date: "21-Jan-2022: espresso 1.0.0 released."
+date: "31-Mar-2022: espresso 1.0.1 released."
 output:
   rmarkdown::html_vignette:
   toc: true
@@ -613,7 +613,9 @@ dev.off()
 __Note__
 
 When the exported format is 'pdf' or 'eps', and `rgl = TRUE`, 
-the legend information is not printed due to the design of `rgl` package.
+the legend information is not printed due to the design of `rgl` package. 
+In addition, it often takes much time to draw UMAP plot as a PDF file when 
+the number of samples is large. In such case, please output as a PNG file.
 
 
 ### Other options of UMAP plotting
@@ -706,15 +708,15 @@ knitr::include_graphics("umap.all.png")
 
 ## Appendix
 
-### Run `graphSOM` and `rxmcmc` of previous version (0.2.17)
-In `espresso` of version 0.2.17 or earlier, the reproducibility between the results of `graphSOM` and `rxmcmc` was not guaranteed, and a random number generation method different from version 1.0.0 or later was employed. The followings are examples of the way to run `graphSOM` and `rxmcmc` of version 0.2.17.
+### Run `graphSOM` and `rxmcmc` of previous version (0)
+In `espresso` of version 0, the reproducibility between the results of `graphSOM` and `rxmcmc` was not guaranteed, and a random number generation method different from version 1.0.0 or later was employed. The followings are examples of the way to run `graphSOM` and `rxmcmc` of version 0.
 
 ```{r, eval = FALSE}
-graphSOM(eobj, gset = fgenes, seed = 0, version = "0.2.17")
+graphSOM(eobj, gset = fgenes, seed = 0, version = "0")
 ```
 
 ```{r, eval = FALSE}
-rxmcmc(eobj, gset = fgenes, itr = 2, n_ex = 5, n_repl = 4, n_cl = 4, seed = 0, version = "0.2.17")
+rxmcmc(eobj, gset = fgenes, itr = 2, n_ex = 5, n_repl = 4, n_cl = 4, seed = 0, version = "0")
 ```
 
 ### Get gene description via biomaRt

vignettes/espresso.Rmd

@@ -1,6 +1,6 @@
 ---
 title: "espresso"
-date: "21-Jan-2022: espresso 1.0.0 released."
+date: "31-Mar-2022: espresso 1.0.1 released."
 output:
   rmarkdown::html_vignette:
   toc: true
@@ -613,7 +613,9 @@ dev.off()
 __Note__
 
 When the exported format is 'pdf' or 'eps', and `rgl = TRUE`, 
-the legend information is not printed due to the design of `rgl` package.
+the legend information is not printed due to the design of `rgl` package. 
+In addition, it often takes much time to draw UMAP plot as a PDF file when 
+the number of samples is large. In such case, please output as a PNG file.
 
 
 ### Other options of UMAP plotting
@@ -706,15 +708,15 @@ knitr::include_graphics("umap.all.png")
 
 ## Appendix
 
-### Run `graphSOM` and `rxmcmc` of previous version (0.2.17)
-In `espresso` of version 0.2.17 or earlier, the reproducibility between the results of `graphSOM` and `rxmcmc` was not guaranteed, and a random number generation method different from version 1.0.0 or later was employed. The followings are examples of the way to run `graphSOM` and `rxmcmc` of version 0.2.17.
+### Run `graphSOM` and `rxmcmc` of previous version (0)
+In `espresso` of version 0, the reproducibility between the results of `graphSOM` and `rxmcmc` was not guaranteed, and a random number generation method different from version 1.0.0 or later was employed. The followings are examples of the way to run `graphSOM` and `rxmcmc` of version 0.
 
 ```{r, eval = FALSE}
-graphSOM(eobj, gset = fgenes, seed = 0, version = "0.2.17")
+graphSOM(eobj, gset = fgenes, seed = 0, version = "0")
 ```
 
 ```{r, eval = FALSE}
-rxmcmc(eobj, gset = fgenes, itr = 2, n_ex = 5, n_repl = 4, n_cl = 4, seed = 0, version = "0.2.17")
+rxmcmc(eobj, gset = fgenes, itr = 2, n_ex = 5, n_repl = 4, n_cl = 4, seed = 0, version = "0")
 ```
 
 ### Get gene description via biomaRt