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Question

I would like to be able to crop R plotly heatmap.

Here's what I mean: I have a hierarchical cluster dataset for gene expression:

require(permute)
set.seed(1)
mat <- rbind(cbind(matrix(rnorm(2500,2,1),nrow=25,ncol=500),matrix(rnorm(2500,-2,1),nrow=25,ncol=500)),
             cbind(matrix(rnorm(2500,-2,1),nrow=25,ncol=500),matrix(rnorm(2500,2,1),nrow=25,ncol=500)))
rownames(mat) <- paste("g",1:50,sep=".")
colnames(mat) <- paste("s",1:1000,sep=".")
hc.col <- hclust(dist(t(mat)))
dd.col <- as.dendrogram(hc.col)
col.order <- order.dendrogram(dd.col)
hc.row <- hclust(dist(mat))
dd.row <- as.dendrogram(hc.row)
row.order <- order.dendrogram(dd.row)
mat <- mat[row.order,col.order]

Then I discretize it in certain ranges of expressions, because it helps to resolve colors for my case. I also create other structures to help me build the colorbarway I want:

require(RColorBrewer)
mat.intervals <- cut(mat,breaks=6)
interval.mat <- matrix(mat.intervals,nrow=50,ncol=1000,dimnames=list(rownames(mat),colnames(mat)))
interval.cols <- brewer.pal(6,"Set2")
names(interval.cols) <- levels(mat.intervals)
require(reshape2)
interval.df <- reshape2::melt(interval.mat,varnames=c("gene","sample"),value.name="expr")
interval.cols2 <- rep(interval.cols, each=ncol(mat))
color.df <- data.frame(range=c(0:(2*length(interval.cols)-1)),colors=c(0:(2*length(interval.cols)-1)))
color.df <- setNames(data.frame(color.df$range,color.df$colors),NULL)
for (i in 1:(2*length(interval.cols))) {
  color.df[[2]][[i]] <- interval.cols[[(i + 1) / 2]]
  color.df[[1]][[i]] <-  i/(2*length(interval.cols))-(i %% 2)/(2*length(interval.cols))
}

How I generated data that I know that samples 1-500 are one cluster and samples 501: 1000 are different, so I denote them:

  interval.df$cluster <- NA
  interval.df$cluster[which(interval.df$sample %in% paste("s",1:500,sep="."))] <- "A"
  interval.df$cluster[which(interval.df$sample %in% paste("s",501:1000,sep="."))] <- "B"

I thought adding a sample with non-color and spacing would create a white column on the graph heatmapthat would look like a face of a face:

divider.df <- data.frame(gene=unique(interval.df$gene),sample=NA,expr=NA,cluster=NA)
interval.df <- rbind(dplyr::filter(interval.df,cluster == "A"),divider.df,dplyr::filter(interval.df,cluster == "B"))

And now I'm trying to build:

#add ticks for each cluster
tick.vals <- c("s.158","s.617")
tick.text <- c("A","B")

require(plotly)
plot_ly(z=c(interval.df$expr),x=interval.df$sample,y=interval.df$gene,colors=interval.cols2,type="heatmap",colorscale=color.df,
                          colorbar=list(title="score",tickmode="array",tickvals=c(1:6),ticktext=names(interval.cols),len=0.2,outlinecolor="white",bordercolor="white",borderwidth=5,bgcolor="white")) %>%
  layout(xaxis = list(title = 'Cluster',tickmode = 'array',tickvals = tick.vals,ticktext = tick.text))

But I do not see the separation between the clusters:

, ?

Answer 1

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library(plotly)

m <- matrix(rnorm(9), nrow = 3, ncol = 3)

p <- plot_ly(
  x = c("a", "b", "c"), y = c("d", "e", "f"),
  z = m, type = "heatmap"
)

subplot(p, p, p, p, shareX = TRUE, shareY = TRUE, nrows = 2)

plotly , subplot, , :

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