R: Pre-defined colors for microarray plots

semantic colors {oompaBase} | R Documentation

## Pre-defined colors for microarray plots

### Description

A collection of predefined color names to help ensure consistency in multiple graphical displays of microarray data.

`oompaColor`:

  a list containing named components allowing the user to systematically use colors for different interpretations.

`oompaColor$BORING`:

  Used to mark uninteresting points in a plot; gray.

`oompaColor$SIGNIFICANT`:

  Used to mark points that are statistically significant; red

`oompaColor$EXPECTED`:

  Used to draw curves representing an expected distribution; blue

`oompaColor$OBSERVED`:

  Used to draw curves indicating the observed distribution; darkgreen

`oompaColor$PERMTEST`:

  Used to draw curves indicating distributions derived from a permutation test; magenta

`oompaColor$FITTED`:

  Used to draw curves obtained by some fitting procedure, such as loess; orange

`oompaColor$CENTRAL.LINE`:

  Used to draw lines through the centers of distributions or expected values; blue

`oompaColor$CONFIDENCE.CURVE`:

  Used to draw confidence bounds around curves; red3

`oompaColor$BAD.REPLICATE`:

  Used to indicate highly variable points; purple1

`oompaColor$WORST.REPLICATE`:

  Used to mark extraordinarily variable points; purple3

`oompaColor$FOLD.DIFFERENCE`:

  Used to indicate points with large fold difference; skyblue

`oompaColor$BAD.REPLICATE.RATIO`:

  Used to flag points for which the ratios at replicate spots are highly variable; violetred

`oompaColor$TOP.TEN`:

  Used to mark points in the "top ten" list; cadetblue

`oompaColor$BOTTOM.TEN`:

  Used to mark points in "bottom ten" list of most underexpressed genes; pink

`oompaColor$BOTTOM.TEN.SOLO`:

  Use unknown; palegreen

`oompaColor$TOP.TEN.SOLO`:

  Use unknown; deeppink

### Examples

    oompaColor
    x <- seq(0, 2*pi, by=0.1)
    plot(x, sin(x), col=oompaColor$BORING)

[Package oompaBase version 3.2.6 Index]