Draw coding sequences, mRNAs and other non-coding features. Supports
multi-exon features. CDS and mRNAs in the same group are plotted together.
They can therefore also be positioned as a single unit using the
geom_gene( mapping = NULL, data = genes(), stat = "identity", position = "identity", na.rm = FALSE, show.legend = NA, inherit.aes = TRUE, size = 2, rna_size = size, shape = size, rna_shape = shape, intron_shape = size, intron_types = c("CDS", "mRNA", "tRNA", "tmRNA", "ncRNA", "rRNA"), cds_aes = NULL, rna_aes = NULL, intron_aes = NULL, ... )
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
The data to be displayed in this layer. There are three options:
NULL, the default, the data is inherited from the plot
data as specified in the call to
data.frame, or other object, will override the plot
data. All objects will be fortified to produce a data frame. See
fortify() for which variables will be created.
function will be called with a single argument,
the plot data. The return value must be a
will be used as the layer data. A
function can be created
~ head(.x, 10)).
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
Position adjustment, either as a string naming the adjustment
"jitter" to use
position_jitter), or the result of a call to a
position adjustment function. Use the latter if you need to change the
settings of the adjustment.
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.
the size of the gene model, aka the height of the
rna_size only applies to non-coding parts of the gene model,
defaults to size.
vector of height and width of the arrow tip, defaults
to size. If only one value is provided it is recycled. Set '0' to
deactivates arrow-shaped tips.
rna_shape only applies to non-coding parts
of the gene model, defaults to shape.
single value controlling the kink of the intron line. Defaults to size. Set 0 for straight lines between exons.
introns will only be computed/drawn for features with types listed here. Set to "CDS" to plot mRNAs as continous features, and set to NA to completely ignore introns.
overwrite aesthetics for different model
parts. Need to be wrapped in
ggplot2::aes(). NOTE: These remappings are
applied after the data has been transformed and mapped by the plot scales
ggplot2::after_scale()). So you need to map between aesthetic names
(not data columns) and with standardized names, i.e. British English
spelling. These mappings can be used to dynamically change parts of the
gene model. For example, to change the color of introns from a hard-coded
"black" to the same color used to fill the CDS you could specify
intron_aes=aes(colour = fill). By default,
rna_aes is remapped with
aes(fill=colorspace::lighten(fill, .5), colour=colorspace::lighten(colour, .5)) to give it a lighter appearence than the corresponding CDS but in the
geom_gene() understands the following aesthetics (required aesthetics are in bold):
Learn more about setting these aesthetics in
'type' and 'group' (mapped to 'type' and 'geom_id' by default) power the proper recognition of CDS and their corresponding mRNAs so that they can be drawn as one composite object. Overwrite 'group' to plot CDS and mRNAs independently.
'introns' (mapped to 'introns') is used to compute intron/exon boundaries.
Use the parameter
intron_types if you want to disable introns.
gggenomes(genes=emale_genes) + geom_gene() #> No seqs provided, inferring seqs from feats gggenomes(genes=emale_genes) + geom_gene(aes(fill=as.numeric(gc_content)),position="strand") + scale_fill_viridis_b() #> No seqs provided, inferring seqs from feats g0 <- read_gff3(ex("eden-utr.gff")) #> Harmonizing attribute names #> • ID -> feat_id #> • Name -> name #> • Parent -> parent_ids #> • Target -> target #> Features read #> # A tibble: 8 × 3 #> source type n #> <chr> <chr> <int> #> 1 NA CDS 5 #> 2 NA TF_binding_site 1 #> 3 NA cDNA_match 1 #> 4 NA exon 5 #> 5 NA five_prime_UTR 1 #> 6 NA gene 1 #> 7 NA mRNA 5 #> 8 NA three_prime_UTR 1 gggenomes(genes=g0) + # all features in the "genes" regardless of type geom_feat(data=feats(genes)) + annotate("text", label="geom_feat", x=-15, y=.9) + xlim(-20, NA) + # only features in the "genes" of geneish type (implicit `data=genes()`) geom_gene() + geom_gene_tag(aes(label=ifelse(is.na(type), "<NA>", type)), data=genes(.gene_types = NULL)) + annotate("text", label="geom_gene", x=-15, y=1) + # control which types are returned from the track geom_gene(aes(y=1.1), data=genes(.gene_types = c("CDS", "misc_RNA"))) + annotate("text", label="gene_types", x=-15, y=1.1) + # control which types can have introns geom_gene(aes(y=1.2, yend=1.2), data=genes(.gene_types = c("CDS", "misc_RNA")), intron_types = "misc_RNA") + annotate("text", label="intron_types", x=-15, y=1.2) #> No seqs provided, inferring seqs from feats #> Warning: Ignoring unknown aesthetics: yend # spliced genes library(patchwork) gg <- gggenomes(genes=g0) #> No seqs provided, inferring seqs from feats gg + geom_gene(position="pile") + gg + geom_gene(aes(fill=type), position="pile", shape = 0, intron_shape = 0, color="white") + # some fine-control on cds/rna/intron after_scale aesthetics gg + geom_gene(aes(fill=geom_id), position="pile", size = 2, shape = c(4,3), rna_size = 2, intron_shape = 4, stroke=0, cds_aes=aes(fill="black"), rna_aes=aes(fill=fill), intron_aes=aes(colour=fill, stroke=2)) + scale_fill_viridis_d() + # fun with introns gg + geom_gene(aes(fill=geom_id), position="pile", size = 3, shape=c(4,4)) + gg + geom_gene(aes(fill=geom_id), position="pile", size = 3, shape=c(4,4), intron_types=c()) + gg + geom_gene(aes(fill=geom_id), position="pile", size = 3, shape=c(4,4), intron_types="CDS")