fixed indentation in the report template

federicomarini · Sep 11, 2024 · 19630ae · 19630ae
1 parent 25e21d5
commit 19630ae
Showing 1 changed file with 31 additions and 31 deletions.
diff --git a/inst/extdata/reportTemplate.Rmd b/inst/extdata/reportTemplate.Rmd
@@ -115,11 +115,11 @@ This plot shows how the samples are related to each other by plotting PC `r inpu
 
 ```{r}
 res <- pcaplot(values$mydst,intgroup = input$color_by,ntop = input$pca_nrgenes,
-                     pcX = as.integer(input$pc_x),pcY = as.integer(input$pc_y),
-                     text_labels = input$sample_labels,
-                     point_size = input$pca_point_size, title="Samples PCA - zoom in",
-                     ellipse = input$pca_ellipse, ellipse.prob = input$pca_cislider
-      )
+               pcX = as.integer(input$pc_x),pcY = as.integer(input$pc_y),
+               text_labels = input$sample_labels,
+               point_size = input$pca_point_size, title="Samples PCA - zoom in",
+               ellipse = input$pca_ellipse, ellipse.prob = input$pca_cislider
+)
 res <- res + theme_bw()
 res
 ```
@@ -154,14 +154,14 @@ This plot illustrates how the top `r input$pca_nrgenes` variant genes are distri
 
 ```{r}
 if(!is.null(input$color_by)) {
-        expgroups <- as.data.frame(colData(values$mydst)[,input$color_by])
-        expgroups <- interaction(expgroups)
-        expgroups <- factor(expgroups,levels=unique(expgroups))
-
-      } else {
-        expgroups <- colnames(values$mydst)
-      }
-      colGroups <- colSel()[factor(expgroups)]
+  expgroups <- as.data.frame(colData(values$mydst)[,input$color_by])
+  expgroups <- interaction(expgroups)
+  expgroups <- factor(expgroups,levels=unique(expgroups))
+  
+} else {
+  expgroups <- colnames(values$mydst)
+}
+colGroups <- colSel()[factor(expgroups)]
 
 res <- genespca(values$mydst,
                 ntop = input$pca_nrgenes,
@@ -180,10 +180,10 @@ For the selected genes, this is the overall profile across all samples
 
 ```{r}
 if(!is.null(input$pcagenes_brush) & length(input$color_by)>0)
-      geneprofiler(values$mydst,
-                   genelist = curData_brush()$ids,
-                   intgroup = input$color_by,
-                   plotZ = input$zprofile)
+  geneprofiler(values$mydst,
+               genelist = curData_brush()$ids,
+               intgroup = input$color_by,
+               plotZ = input$zprofile)
 ```
 
 And here is an interactive heatmap for that subset
@@ -197,9 +197,9 @@ if(!is.null(input$pcagenes_brush))
     selectedGenes <- brushedObject$ids
     toplot <- assay(values$mydst)[selectedGenes,]
     rownames(toplot) <- values$myannotation$gene_name[match(rownames(toplot),rownames(values$myannotation))]
-  
+    
     mycolss <- c("#313695","#4575b4","#74add1","#abd9e9","#e0f3f8","#fee090","#fdae61","#f46d43","#d73027","#a50026") # to be consistent with red/blue usual coding
-  
+    
     heatmaply(toplot,Colv = as.logical(input$heatmap_colv),colors = mycolss)
   }
 }
@@ -311,23 +311,23 @@ if(input$composemat > 0){
   tcol <- obj3()[[2]]
   tcol2 <- obj3()[[3]]
   pres <- prcomp(t(pcmat),scale=FALSE)
-
+  
   plot.index <- c(as.integer(input$pc_x_multifac),as.integer(input$pc_y_multifac))
   offset <- ncol(pcmat)/2
   gene.no <- offset
   pcx <- pres$x
   # set.seed(11)
-    # for (i in 1:ncol(pcx)) {
-    #   pcx[,i] <- pcx[,i] + rnorm(nrow(pcx),sd=diff(range(pcx[,i]))/100)
-    # }
-    plot(pcx[(offset+1):ncol(pcmat),plot.index[1]][1:gene.no],pcx[(offset+1):ncol(pcmat),plot.index[2]][1:gene.no],xlim=range(pcx[,plot.index[1]]),ylim=range(pcx[,plot.index[2]]),pch=20,col=tcol,cex=0.3)#,type="n")
-    #plot(0,type="n",xlim=range(pres$x[,plot.index]),ylim=range(pres$x[,plot.index]))
-    lcol <- ifelse(tcol != tcol2,"black","grey")
-    for (i in 1:gene.no) {
-      lines(pcx[c(i,offset+i),plot.index[1]],pcx[c(i,offset+i),plot.index[2]],col=lcol[i])
-    }
-    points(pcx[1:offset,plot.index[1]][1:gene.no],pcx[1:offset,plot.index[2]][1:gene.no],pch=20,col=tcol,cex=0.3)
-    points(pcx[(offset+1):ncol(pcmat),plot.index[1]][1:gene.no],pcx[(offset+1):ncol(pcmat),plot.index[2]][1:gene.no],pch=20,col=tcol2,cex=0.3)}
+  # for (i in 1:ncol(pcx)) {
+  #   pcx[,i] <- pcx[,i] + rnorm(nrow(pcx),sd=diff(range(pcx[,i]))/100)
+  # }
+  plot(pcx[(offset+1):ncol(pcmat),plot.index[1]][1:gene.no],pcx[(offset+1):ncol(pcmat),plot.index[2]][1:gene.no],xlim=range(pcx[,plot.index[1]]),ylim=range(pcx[,plot.index[2]]),pch=20,col=tcol,cex=0.3)#,type="n")
+  #plot(0,type="n",xlim=range(pres$x[,plot.index]),ylim=range(pres$x[,plot.index]))
+  lcol <- ifelse(tcol != tcol2,"black","grey")
+  for (i in 1:gene.no) {
+    lines(pcx[c(i,offset+i),plot.index[1]],pcx[c(i,offset+i),plot.index[2]],col=lcol[i])
+  }
+  points(pcx[1:offset,plot.index[1]][1:gene.no],pcx[1:offset,plot.index[2]][1:gene.no],pch=20,col=tcol,cex=0.3)
+  points(pcx[(offset+1):ncol(pcmat),plot.index[1]][1:gene.no],pcx[(offset+1):ncol(pcmat),plot.index[2]][1:gene.no],pch=20,col=tcol2,cex=0.3)}
 ```
 
 # About pcaExplorer