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
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
Geom subclass or as a string naming the
stat stripped of the
stat_ prefix (e.g.
"count" rather than
describes how the position of different plotted features are adjusted. By default it uses
but different ggplot2 position adjustments, such as
"jitter" can be used as well.
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
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.
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.
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