User:Timothee Flutre/Notebook/Postdoc/2011/11/09

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m (Entry title: mention R "replace")
Current revision (12:24, 22 May 2014) (view source)
(Entry title: add custom heatmap)
 
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  rownames(mat) <- new.rownames
  rownames(mat) <- new.rownames
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Or it's maybe easier with the built-in [http://stat.ethz.ch/R-manual/R-patched/library/base/html/replace.html replace] function.
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Or it's maybe easier with the built-in [http://stat.ethz.ch/R-manual/R-patched/library/base/html/match.html match] function:
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new.rownames <- links$id2[ match(rownames(mat), links$id1) ]
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* in R, visualize the missing values (encoded as "NA") in a matrix:
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image(1:nrow(mat), 1:ncol(mat), is.na(mat), col=c("white","black"),
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      main="Missing values", xlab="Genes", ylab="Samples")
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[[Image:Visualize_missing_values_in_matrix.png|400px]]
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* in R, customize the built-in heatmap (inspired from [http://stackoverflow.com/questions/5687891/r-how-do-i-display-clustered-matrix-heatmap-similar-color-patterns-are-grouped/5694349 this]):
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S <- 3  # nb of subgroups
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V <- 7  # nb of observations
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z <- matrix(c(0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,0,1,1,1,0,0), nrow=V, ncol=S, byrow=TRUE)
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myheatmap <- function(z, out.file="") {
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  def.par <- par(no.readonly=TRUE)
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  par(mar=c(4,5,3,2), font=2, font.axis=2, font.lab=2, cex=1.5, lwd=2)
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  if (out.file != "")
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    pdf(out.file)
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  layout(mat=cbind(1, 2), width=c(7,1))  # plot +  legend
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  mycol <- rev(heat.colors(4))
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  image(x=1:NCOL(z), y=1:NROW(z), z=t(z),
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        xlim=0.5+c(0,NCOL(z)), ylim=0.5+c(0,NROW(z)),
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        xlab="", ylab="Observations sorted by cluster", main="Custom heatmap",
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        axes=FALSE, col=mycol)
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  axis(1, 1:NCOL(z), labels=paste("subgroup", 1:NCOL(z)), tick=0)
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  par(mar=c(0,0,0,0))
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  plot.new()
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  legend("center", legend=sprintf("%.2f", seq(from=min(z), to=max(z), length.out=5)[-1]),
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          fill=mycol, border=mycol, bty="n")
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  if (out.file != "")
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    dev.off()
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  par(def.par)
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  }
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myheatmap(mydata.sort)
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Entry title

  • in R, replace the row names of a matrix by their new names when the order is different (but assuming one-to-one mapping):
links <- data.frame(id1=c("a","b","c"), id2=c("1","2","3"), stringsAsFactors=FALSE)
mat <- matrix(runif(3*10), nrow=3)
rownames(mat) <- c("b","c","a")
new.rownames <- unlist(lapply(rownames(mat), function(i){links$id2[which(links$id1 == i)]}))
rownames(mat) <- new.rownames

Or it's maybe easier with the built-in match function:

new.rownames <- links$id2[ match(rownames(mat), links$id1) ]


  • in R, visualize the missing values (encoded as "NA") in a matrix:
image(1:nrow(mat), 1:ncol(mat), is.na(mat), col=c("white","black"),
      main="Missing values", xlab="Genes", ylab="Samples")


  • in R, customize the built-in heatmap (inspired from this):
S <- 3  # nb of subgroups
V <- 7  # nb of observations
z <- matrix(c(0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,0,1,1,1,0,0), nrow=V, ncol=S, byrow=TRUE)

myheatmap <- function(z, out.file="") {
  def.par <- par(no.readonly=TRUE)
  par(mar=c(4,5,3,2), font=2, font.axis=2, font.lab=2, cex=1.5, lwd=2)
  if (out.file != "")
    pdf(out.file)
  layout(mat=cbind(1, 2), width=c(7,1))  # plot +  legend
  mycol <- rev(heat.colors(4))
  image(x=1:NCOL(z), y=1:NROW(z), z=t(z),
        xlim=0.5+c(0,NCOL(z)), ylim=0.5+c(0,NROW(z)),
        xlab="", ylab="Observations sorted by cluster", main="Custom heatmap",
        axes=FALSE, col=mycol)
  axis(1, 1:NCOL(z), labels=paste("subgroup", 1:NCOL(z)), tick=0)
  par(mar=c(0,0,0,0))
  plot.new()
  legend("center", legend=sprintf("%.2f", seq(from=min(z), to=max(z), length.out=5)[-1]),
         fill=mycol, border=mycol, bty="n")
  if (out.file != "")
    dev.off()
  par(def.par)
 }

myheatmap(mydata.sort)


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