In MAFDash: Create an HTML Dashboard to Visualize Data from MAF File

Interactive Heatmap

snp_mat <- mutCountMatrix(maf = maf)
snp_mat$total <- rowSums(snp_mat)
snp_mat <- snp_mat[with(snp_mat,order(-total)),]
snp_mat <- snp_mat[1:50,]
mat1 <-subset(snp_mat, select=-(total))
mat1 <- log2(mat1 +1)
mat1<- t(mat1)


### This makes the "waterfall" effect for the gene/sample matrix
# source("scripts/helper_functions/helper_functions.oncoplot.R")
oncomat <- createOncoMatrix(maf, g=colnames(mat1))$oncoMatrix
mat1 <- mat1[match(colnames(oncomat), rownames(mat1)), match(rownames(oncomat), colnames(mat1))]

### Set up sizing parameters
minsize=200
maxsize=850
nsample=ncol(mat1)
px_per_sample=13
hm_height=paste0(
        min(c(maxsize, max(c(minsize,nsample*px_per_sample)))),
        "px")

ngenes=nrow(mat1)
px_per_gene=px_per_sample
hm_width=paste0(
        min(c(maxsize, max(c(minsize,ngenes*px_per_gene)))),
        "px")

#require(canvasXpress)
### Render plot
canvasXpress(
  data = mat1,
  colorSpectrum = list("black","blue","magenta","red","gold"),
  graphType = "Heatmap",
  # samplesClustered = TRUE,
  # variablesClustered = TRUE,
  samplesClustered = FALSE,
  variablesClustered = FALSE,
  showTransition = FALSE,
  smpLabelScaleFontFactor = 0.5,
  varLabelScaleFontFactor = 0.5,
  width = hm_width,
  height = hm_height,
  # titleFont="10px Verdana",
  legendScaleFontFactor=1,
  # showLegendTitle=T#,
  titleScaleFontFactor=0.3,
  title="log2(Num Variants)"
  )