geom_feat()
allows the user to draw (additional) features to the plot/graph.
For example, specific regions within a sequence (e.g. transposons, introns, mutation hotspots)
can be highlighted by color, size, etc..
geom_feat(
mapping = NULL,
data = feats(),
stat = "identity",
position = "pile",
na.rm = FALSE,
show.legend = NA,
inherit.aes = TRUE,
...
)
Set of aesthetic mappings created by aes()
. If specified and
inherit.aes = TRUE
(the default), it is combined with the default mapping
at the top level of the plot. You must supply mapping
if there is no plot
mapping.
feat_layout: Uses first data frame stored in the feats
track by default.
The statistical transformation to use on the data for this
layer, either as a ggproto
Geom
subclass or as a string naming the
stat stripped of the stat_
prefix (e.g. "count"
rather than
"stat_count"
)
describes how the position of different plotted features are adjusted. By default it uses "pile"
,
but different ggplot2 position adjustments, such as "identity
or "jitter"
can be used as well.
If FALSE
, the default, missing values are removed with
a warning. If TRUE
, missing values are silently removed.
logical. Should this layer be included in the legends?
NA
, the default, includes if any aesthetics are mapped.
FALSE
never includes, and TRUE
always includes.
It can also be a named logical vector to finely select the aesthetics to
display.
If FALSE
, overrides the default aesthetics,
rather than combining with them. This is most useful for helper functions
that define both data and aesthetics and shouldn't inherit behaviour from
the default plot specification, e.g. borders()
.
Other arguments passed on to layer()
. These are
often aesthetics, used to set an aesthetic to a fixed value, like
colour = "red"
or size = 3
. They may also be parameters
to the paired geom/stat.
geom_feat
uses ggplot2::geom_segment
under the hood. As a result,
different aesthetics such as alpha, linewidth, color, etc.
can be called upon to modify the visualization of the data.
By default, the function uses the first feature track.
# Plotting data from the feats' track with adjusted linewidth and color
gggenomes(seqs = emale_seqs, feats = emale_ngaros) +
geom_seq() +
geom_feat(linewidth = 5, color = "darkred")
# Geom_feat can be called several times as well, when specified what data should be used
gggenomes(seqs = emale_seqs, feats = list(emale_ngaros, emale_tirs)) +
geom_seq() +
geom_feat(linewidth = 5, color = "darkred") + #uses first feature track
geom_feat(data = feats(emale_tirs))
# Additional notes to feats can be added with functions such as: geom_feat_note / geom_feat_text
gggenomes(seqs = emale_seqs, feats = list(emale_ngaros, emale_tirs)) +
geom_seq() +
geom_feat(color = "darkred") +
geom_feat(data=feats(emale_tirs), color = "darkblue") +
geom_feat_note(data = feats(emale_ngaros), label="repeat region", size = 4)
# Different position adjustments with a simple dataset
exampledata <- tibble::tibble(
seq_id = c(rep("A", 3), rep("B", 3), rep("C", 3)),
start = c(0, 30, 15, 40, 80, 20, 30, 50, 70),
end = c(30, 90, 60, 60, 100, 80, 60, 90, 120))
gggenomes(feats = exampledata) +
geom_feat(position = "identity", alpha = 0.5, linewidth = 0.5) +
geom_bin_label()
#> No seqs provided, inferring seqs from feats