R: Visualize two-dimensional data clusters (add to an existing...

singlemsdplot {LSD}

R Documentation

Visualize two-dimensional data clusters (add to an existing plot)

Description

Depict a numeric matrix or list utilizing the underlying mean and standard deviation estimates of one dimension in a color encoded fashion (add to an existing plot).

Usage

singlemsdplot(input, col = "darkgreen", alpha = 50, bars = TRUE,
  length = 0.25, at = NULL)

Arguments

`input`	data as matrix or list.
`col`	a character vector of R build-in colors.
`alpha`	alpha value: a two-digit integer between 01 and 99 for color opacity, i.e. appearance of partial or full transparency (usage omitted by default).
`bars`	logical: if `TRUE` (by default), error bars are added at each position.
`length`	a numeric value scaling the width of the bars.
`at`	a integer vector containing the x-positions corresponding to the columns of 'input'.

Author(s)

Bjoern Schwalb

Examples

samples = 100
probes = 200
clus = matrix(rnorm(probes*samples,sd=1),ncol=probes)

clus = rbind(
	t(t(clus)+sin(1:probes/10))+1:nrow(clus)/samples,
	t(t(clus)+sin(pi/2+1:probes/10))+1:nrow(clus)/samples)

emptyplot(xlim = c(1,ncol(clus)),ylim = range(clus))
singlemsdplot(clus)
axis(1)
axis(2)
box()