Creates a plot showing the clustering and profiles of a
TRAMPknowns
object (a “knowns database”). The
plot has three vertical panels;
The leftmost contains a dendrogram, showing
how similar the profiles of knowns are (see
group.knowns
for details).
The rightmost displays the TRFLP profile for each individual (with a different colour symbol for each different enzyme/primer combination).
The middle panel displays information on the species names and groups of the knowns.
# S3 method for TRAMPknowns
plot(x, cex=1, name="species", pch=1, peaks.col, p=.02,
group.clusters=TRUE, groups.col=1:4, grid.by=5, grid.col="gray",
widths=c(1, 2, 1), ...)
A TRAMPknowns
object.
Character size for the plot. Because knowns databases can be large, this should be small and may need to be adjusted. Most aspects of the plot will scale with this.
Column name to use when generating species names; must be
one of species
or group.name
.
Plotting symbol to use for peaks in the peak profiles.
Vector of colours to plot the different enzymes in
the peak profiles. These will be used in the order of the columns
of summary(x)
.
Scaling factor for the middle plot; this specifies the
proportion of the width that elements are spaced horizontally from
one another. Columns of text are p
apart, brackets grouping
knowns are p/2
apart, and cluster groups (if present) are
p*2/3
apart.
Logical: Should groups of clusters (determined
by group.strict
- see group.knowns
) be joined
together?
Vector of colours to plot different group clusters in. This will be recycled as neccessary.
Interval between horizontal grid lines. Grid lines
start at ceiling(grid.by/2)
from the bottom of the plot. A
value of NA
suppresses grid lines.
Colour of the horizontal grid lines.
Relative widths of the three panels of the plot (see
layout
). widths
must be a vector of 3 elements,
corresponding to the three panels from left to right.
Additional arguments (ignored).
group.knowns
, which controls the grouping of
knowns, and TRAMPknowns
, which constructs
TRAMPknowns
objects.
# NOT RUN {
data(demo.knowns)
plot(demo.knowns)
# }
# NOT RUN {
pdf("knowns_summary.pdf", paper="default", width=8, height=11)
plot(demo.knowns)
plot(demo.knowns, group.clusters=FALSE)
dev.off()
# }
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