dotchart.uco {seqinr}R Documentation

Cleveland plot for codon usage tables

Description

Draw a Cleveland dot plot for codon usage tables

Usage

dotchart.uco(x, numcode = 1, aa3 = TRUE, cex = 0.7, alphabet = s2c("tcag"),
 pch = 21, gpch = 20, bg = par("bg"), color = par("fg"), gcolor = par("fg"),
lcolor = "gray", xlim, ...)

Arguments

x table of codon usage as computed by uco.
numcode the number of the code to be used by translate.
aa3 logical. If TRUE use the three-letter code for amino- acids. If FALSE use the one-letter code for amino-acids.
cex the character size to be used.
alphabet character for codons labels
pch the plotting character or symbol to be used.
gpch the plotting character or symbol to be used for group values.
bg the background color to be used.
color the color(s) to be used for points an labels.
gcolor the single color to be used for group labels and values.
lcolor the color(s) to be used for the horizontal lines.
xlim horizontal range for the plot
... graphical parameters can also be specified as arguments

Value

An invisible list with components:

x table of codon usage
labels codon names
groups amino acid factor
gdata sums by amino acid
ypg the y-axis coordinates for amino acids
ypi the y-axis coordinates for codons

Author(s)

J.R. Lobry

References

Cleveland, W. S. (1985) The Elements of Graphing Data. Monterey, CA: Wadsworth. citation("seqinr")

See Also

dotchart, uco, aaa, translate

Examples

# Load dataset:
data(ec999)
# Compute codon usage for all coding sequences:
ec999.uco <- lapply(ec999, uco, index="eff") 
# Put it in a dataframe:
df <- as.data.frame(lapply(ec999.uco, as.vector)) 
# Add codon names:
row.names(df) <- names(ec999.uco[[1]])
# Compute global codon usage:
global <- rowSums(df)
# Choose a title for the graph:
title <- "Codon usage in 999 E. coli coding sequences"
# Plot data:
dotchart.uco(global, main = title) 

[Package seqinr version 1.0-6 Index]