An Introduction to R graphics

Cody Chiuzan

Division of Biostatistics and EpidemiologyComputing for Research I, 2012

R graphics – Nice and Simple

R has powerful graphics facilities for the production of publication-quality diagrams and plots.

Can produce traditional plots as well as grid graphics.

Great reference: Murrell P., R Graphics

Topics for today

Histograms

Plot, points, lines, legend, xlab, ylab, main, xlim, ylim, pch, lty, lwd.

Scatterplot matrix

Individual profiles

3D graphs

Data Puromycin – Before and After

R code

Data available in R; for a full description: help(Puromycin). We will start with the basic command plot() and tackle each

parameter.

Generate multiple graphs in the same window using: par(mfrow).

For a better understanding use help().

Change parameters using par()

A list of graphical parameters that define the default behavior of all plot functions.

Just like other R objects, par elements are similarly modifiable, with slightly different syntax. e.g. par(“bg”=“lightcyan”) This would change the background color of all subsequent

plots to light cyan

When par elements are modified directly (as above, this changes all subsequent plotting behavior.

Par examples modifiable from within plotting functions

bg – plot background color lty – line type (e.g. dot, dash, solid) lwd – line width col – color cex – text size inside plot xlab, ylab – axes labels main – title pch – plotting symbol … and many more (learn as you need them)

Plotting symbols for pch

Great website for choosing colors:

http://research.stowers-institute.org/efg/R/Color/Chart/ColorChart.pdf

Multiple plots

The number of plots on a page, and their placement on the page, can be controlled using par() or layout().

The number of figure regions can be controlled using mfrow and mfcol.

e.g. par(mfrow=c(3,2)) # Creates 6 figures arranged in 3 rows and 2 columns

Layout() allows the creation of multiple figure regions of unequal sizes.

e.g. layout(matrix(c(1,2)), heights=c(2,1))

Graph using statistical function output

Many statistical functions (regression, cluster analysis) create special objects. These arguments will automatically format graphical output in a specific way.

e.g. Produce diagnostic plots from a linear model analysis (see R code)

# Reg = lm() # plot(Reg)

hclust() agnes() # hierarchical cluster analysis

Save the output

Specify destination of graphics output or simply right click and copy

Could be files Not Scalable

JPG # not recommended, introduces blurry artifacts around the lines BMP PNG

Scalable: Postscript # preferred in LaTex Pdf # great for posters

Save the output

setwd("") # this is where the plot will be savedpdf(file="Puromycin.pdf“, width = , height = , res = )dev.off()

Next - 3D graphs