In vladpetyuk/vp.misc: Miscellaneous functions used by Vlad Petyuk for proteomics data analysis

library("vp.misc")
suppressPackageStartupMessages(library("MSnbase"))

data(srm_msnset)

# match.group, subject.type, msex, Visible blood contamination
columnCol <- pData(msnset)[,c("subject.type", "match.group", "msex", 
                              "Visible blood contamination")]
columnCol <- as.data.frame(lapply(columnCol, as.factor))
columnCol$subject.type <- 
    c('red','orange','blue')[columnCol$subject.type]
columnCol$match.group <- 
    jet.colors(nlevels(columnCol$match.group))[columnCol$match.group]
columnCol$msex <- 
    c('pink','olivedrab')[columnCol$msex]
columnCol$Visible.blood.contamination <- 
    c('black','lightgrey')[columnCol$Visible.blood.contamination]

heatmap.plus.2(exprs(msnset), 
               hclustfun = function(x, ...) hclust(x, method="average", ...),
               dist = function(x, ...) dist(x, method="pearson", ...),
               propColSide=0.1,
               scale="none",
               ColSideColors=as.matrix(columnCol),
               breaks=c(-4,seq(-2,+2,length=100),+4),
               col=gplots::bluered(102-1)
               )

# power scaled breaks
pwr = 2
lim = 4
breaks = lim * abs(seq(-1,+1,length=100))^pwr * sign(seq(-1,+1,length=100))
msnset <- msnset[,order(msnset$subject.type)]
ColSideColors <- c("yellow","magenta","green")[as.numeric(factor(msnset$subject.type, levels=c("case","control.1","control.2")))]

library(gplots)
heatmap.2(exprs(msnset),
          Colv=FALSE,
          colsep = cumsum(table(msnset$subject.type)),
          sepwidth=c(0.2,0.2),
          dendrogram = "row",
          hclustfun = function(x, ...) hclust(x, method="average", ...),
          dist = function(x, ...) dist(x, method="pearson", ...),
          trace="none",
          ColSideColors=ColSideColors,
          breaks=breaks,
          col=bluered(length(breaks)-1))

vladpetyuk/vp.misc documentation built on June 25, 2021, 6:35 a.m.