hca.plot: Dendrogram with according sample annotations

Description Usage Arguments Details Note Author(s) Examples

View source: R/hca.plot.R

Description

The function plots the dendrogram from hierarchical cluster analysis with colorcoded sample annotations below.

Usage

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hca.plot(g, o, method = "correlation", link = "ward", colored = palette(), 
         border = NA, code = colnames(o), cex.code = 1, 
         breaks = round(nrow(oreihe)/4), 
         cutcolors = colorpanel(breaks, low = "green", mid = "black", high = "red"))

Arguments

g

the input data in form of a matrix with features as rows and samples as columns.

o

the corresponding sample annotations in the form of a data.frame. A single sample annotation variable as a vector is allowed and will be transformed to a data.frame. rownames (o) must be identical to colnames (g). o can contain factors and numeric variables. No character variables are allowed. NAs are allowed and blank spaces are plotted.

method

the distance method for the clustering. default="correlation". hcluster from the package amap is used and method must be one of "euclidean", "maximum", "manhattan", "canberra" "binary" "pearson", "correlation", "spearman" or "kendall".

link

the agglomeration principle for the clustering. default="ward". hcluster from the package amap is used and link must be one of "ward", "single", "complete", "average", "mcquitty", "median" or "centroid".

colored

a vector of colors in which factor variables of o will be colorcoded. default are the 8 colors of palette(). the first level is plotted in the first color, the second in the second color and so on. for annotation with more than 8 levels colors should be added here.

border

a color for the borders in the annotation rectangels rect(). default=NA.

code

vector containing names of the sample annotations. default=colnames(o).

cex.code

font size of code.

breaks

a number that determines in how many bins a numeric annotation is cut using the cut() function.

cutcolors

a vector of color in which numeric variables will be colored. length(cutcolors) has to be the number of breaks. a colorpanel is default to plot the numeric values as a color gradient, with low values in green and high values in red.

Details

The data is clustered using the amap package. The plot works for sample annotations as a data.frame or as a single vector. NAs are allowed in both data matrix and sample annotation data.frame. If the annotation is a factor, the annotations come in the colororder specified by colored. If the annotation is numeric, breaks and cutcolors is used which is currently set to be a colorpanel().

Note

requires the packages amap and gplots

Author(s)

Martin Lauss

Examples

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# data as a matrix
set.seed(100)
g<-matrix(nrow=1000,ncol=50,rnorm(1000*50),dimnames=list(paste("Feature",1:1000),
   paste("Sample",1:50)))
g[1:100,26:50]<-g[1:100,26:50]+1 # the first 100 features show higher values in the samples 26:50
# patient annotations as a data.frame, annotations should be numbers and factor but not characters.
# rownames have to be the same as colnames of the data matrix 
set.seed(200)
o<-data.frame(Factor1=factor(c(rep("A",25),rep("B",25))),
              Factor2=factor(rep(c("A","B"),25)),
              Numeric1=rnorm(50),row.names=colnames(g))

## hca plot
hca.plot(g,o) 
 

Example output

Loading required package: impute
Loading required package: amap
Loading required package: gplots

Attaching package: 'gplots'

The following object is masked from 'package:stats':

    lowess

Loading required package: MASS

swamp documentation built on May 2, 2019, 2:14 p.m.