myheat: Draw heatmap usig gplots

In shkonishi/rsko: This is my personal package of R functions

Draw heatmap usig gplots

Description

hierarchical clustering using amap::Dsit, and draw heatmap using by gplots::heatmap.2. Usinga a categorical data, consists from integer vectors.

Usage

myheat(d, squared, categorical, draw, cden, rden,
c.distm, c.clm, r.distm, r.clm, scale, color, ...)

Arguments

d	data.frame or matrix
squared	logical: squared matrix like a correlation matrix is TRUE. The default value is FALSE
categorical	logical: categorical data or not.
draw	"both","row","column", or "none"
cden	dendrogram object like a result of rsko::extendtree
rden	dendrogram object like a result of rsko::extendtree
c.distm	A distance measure for column side dendrogram. The default value is "spearman". If categorical was TRUE, the default value is "jaccard", and select from these "jaccard", "simpson", "dice" , and "smc".
c.clm	A clustering method for column side dendrogram.
r.distm	A distance measure for row side dendrogram.
r.clm	A clustering method for row side dendrogram.
scale	character "row", "column", "none"
color	character select from "bluered", "greenred", "heat.colors", "BuRd". If categorical was TRUE, colour vectors which lengh same as levels of 'd'.
...	additional optioins for gplots::heatmap.2. E.g. cexRow = 0.8, cexCol = 0.8, labRow = FALSE = F, labCol = F

Examples

## Not run: 
# clustering and draw heatmap
dat = iris[-5]
myheat(d = dat, scale = "column", cexCol = 1)
myheat(d = dat, draw = "both", scale = "column", color = "BuRd", labRow = FALSE, labCol = FALSE)
myheat(d = dat, draw = "both", scale = "column", color = "bluered", cexRow = 0.8, cexCol = 0.8)

# give dendrogram object
rden <- rsko::extendtree(dat = dat, extend = TRUE,
                         distm = "euclidean", clm = "average",
                         lab = as.character(iris[[5]]),
                         gp = iris[,5], vcol = 1:3)

cden <- rsko::extendtree(dat = t(dat), extend = FALSE,
                         distm = "correlation", clm = "average")

myheat(d = t(dat), categorical = FALSE, squared = FALSE, draw = "both",
       cden = rden[[2]], rden = cden[[2]],  scale = "row", cexRow = 0.8)

# squared matrix
cormat <- as.data.frame(cor(t(dat)))
myheat(cormat, squared = TRUE, draw = "both", scale = "none",
c.distm = "correlation", r.distm = "correlation", c.clm = "average", r.clm = "average",
color = "heat.colors")

# categorical data, which converted from character to integer
scale_col <- function(x) as.vector(scale(x, center = min(x), scale = max(x)-min(x)))
fct_col <- function(x) {
   cut(x, breaks = seq(0, 1, 0.25), labels = letters[1:4], include.lowest = TRUE)
   }
dat <- as.data.frame(do.call(cbind, lapply(iris[-5], function(x) { fct_col(scale_col(x))})))
col <- RColorBrewer::brewer.pal(4, "Dark2")
myheat(d=dat, categorical=TRUE, c.distm="smc", r.distm="smc", color=col, cexCol=0.8)


# categorical data
data("listeria", package = "qtl")
dat <- listeria$geno[[1]][[1]]
col <- c("steelblue", "darkseagreen1","violetred2")
rsko::myheat(d=dat, categorical = T, color = col, c.distm="jaccard", r.distm="smc")
legend("topleft", legend = c(levels(factor(dat)),"null"), col = c(col,NA), pch = 15, cex = 0.8)

## End(Not run)

shkonishi/rsko documentation built on Feb. 21, 2023, 5:12 a.m.