---
title: "Introduction to 'gggenes'"
author: "David Wilkins"
date: "`r Sys.Date()`"
output: rmarkdown::html_vignette
vignette: >
  %\VignetteIndexEntry{Introduction to 'gggenes'}
  %\VignetteEngine{knitr::rmarkdown}
  %\VignetteDepends{ggplot2}
  %\VignetteDepends{gggenes}
---

```{r, echo = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.width = 6,
  fig.height = 10
)
```

'gggenes' is ggplot2 extension for drawing gene arrow maps.

## Drawing gene arrows with `geom_gene_arrow()`

`geom_gene_arrow()` is a 'ggplot2' geom that represents genes with arrows. The
start and end locations of the genes within their molecule(s) are mapped to the
`xmin` and `xmax` aesthetics respectively. These start and end locations are
used to determine the directions in which the arrows point. The `y` aesthetic
must be mapped to the molecule(s). If you are drawing more than one molecule,
and the numerical locations of the genes are not similar across molecules, you
almost certainly want to facet the plot with `scales = "free"` to avoid drawing
ridiculously large molecules with ridiculously tiny genes.

```{r geom_gene_arrow, message = FALSE}
library(ggplot2)
library(gggenes)
ggplot(example_genes, aes(xmin = start, xmax = end, y = molecule, fill = gene)) +
  geom_gene_arrow() +
  facet_wrap(~ molecule, scales = "free", ncol = 1) +
  scale_fill_brewer(palette = "Set3")
```

## Beautifying the plot with `theme_genes()`

Because the resulting plot can look cluttered, a 'ggplot2' theme
`theme_genes()` is provided with some sensible defaults.

```{r theme_genes}
ggplot(example_genes, aes(xmin = start, xmax = end, y = molecule, fill = gene)) +
  geom_gene_arrow() +
  facet_wrap(~ molecule, scales = "free", ncol = 1) +
  scale_fill_brewer(palette = "Set3") +
  theme_genes()
```

## Aligning genes across facets with `make_alignment_dummies()`

Often you will want a certain gene to be vertically aligned across the faceted
molecules. `make_alignment_dummies()` generates a set of 'dummy' genes that if
added to the plot with `ggplot2::geom_blank()` will extend the range of each facet to
visually align the selected gene across facets.

```{r make_alignment_dummies}
dummies <- make_alignment_dummies(
  example_genes,
  aes(xmin = start, xmax = end, y = molecule, id = gene),
  on = "genE"
)

ggplot(example_genes, aes(xmin = start, xmax = end, y = molecule, fill = gene)) +
  geom_gene_arrow() +
  geom_blank(data = dummies) +
  facet_wrap(~ molecule, scales = "free", ncol = 1) +
  scale_fill_brewer(palette = "Set3") +
  theme_genes()
```

## Labelling genes with `geom_gene_label()`

To label individual genes, provide a `label` aesthetic and use
`geom_gene_label()`. `geom_gene_label()` uses the
['ggfittext'](https://github.com/wilkox/ggfittext) package to fit the label
text inside the gene arrows; see the 'ggfittext' documentation for more details
on how it resizes and reflows text to make it fit.

```{r labelled_genes}
ggplot(example_genes, aes(xmin = start, xmax = end, y =
                                            molecule, fill = gene, label = gene)) +
  geom_gene_arrow(arrowhead_height = unit(3, "mm"), arrowhead_width = unit(1, "mm")) +
  geom_gene_label(align = "left") +
  geom_blank(data = dummies) +
  facet_wrap(~ molecule, scales = "free", ncol = 1) +
  scale_fill_brewer(palette = "Set3") +
  theme_genes()
```

## Reversing gene direction with the optional `forward` aesthetic

By default, genes arrows are drawn pointing in the direction implied by `xmin`
and `xmax`. You can override this with the optional `forward` aesthetic, which
can be useful when the gene coordinates and orientation are encoded as separate
variables.

If `forward` is TRUE (the default), or any value that coerces to TRUE such as
1, the gene will be drawn pointing in the implied direction, i.e. from `xmin`
to `xmax`. If `forward` is FALSE, or any value that coerces to FALSE such as
0, the gene will be drawn in the reverse of this implied direction:

```{r reversing_direction}
ggplot(example_genes, aes(xmin = start, xmax = end, y = molecule, fill = gene, 
                          forward = orientation)) +
  geom_gene_arrow() +
  facet_wrap(~ molecule, scales = "free", ncol = 1) +
  scale_fill_brewer(palette = "Set3") +
  theme_genes()
```

## Viewing subgene segments

We can highlight subgene segments, such as protein domains or local alignments,
using `geom_subgene_arrow()`.

This works similarly to `geom_gene_arrow()`, but in addition to `xmin` and `xmax`
(which determine the gene boundaries), we need the aesthetics `xsubmin` and
`xsubmax` to determine the subgene boundaries. `geom_gene_arrow()` will produce
pretty arrowheads, as long as `xmin >= xsubmin` and `xmax >= xsubmax` for all
subgenes (subgenes that break gene boundaries will be skipped with a warning).

The suggested usage is to use `geom_gene_arrow()` with no fill, and then add a
subgene layer over this:

```{r subgenes}
ggplot(example_genes, aes(xmin = start, xmax = end, y = molecule)) +
  facet_wrap(~ molecule, scales = "free", ncol = 1) +
  geom_gene_arrow(fill = "white") +
  geom_subgene_arrow(data = example_subgenes,
    aes(xmin = start, xmax = end, y = molecule, fill = gene,
        xsubmin = from, xsubmax = to), color="black", alpha=.7) +
  theme_genes()
```

To label subgenes, we can use `geom_subgene_label()`, which works similarly to
`geom_gene_label()` with the major difference that it requires `xsubmin` and
`xsubmax` aesthetics (not `xmin` and `xmax`).

```{r subgene labels, fig.height = 2}
ggplot(subset(example_genes, molecule == "Genome4" & gene == "genA"),
       aes(xmin = start, xmax = end, y = strand)
  ) +
  geom_gene_arrow() +
  geom_gene_label(aes(label = gene)) +
  geom_subgene_arrow(
    data = subset(example_subgenes, molecule == "Genome4" & gene == "genA"),
    aes(xsubmin = from, xsubmax = to, fill = subgene)
  ) +
  geom_subgene_label(
    data = subset(example_subgenes, molecule == "Genome4" & gene == "genA"),
    aes(xsubmin = from, xsubmax = to, label = subgene),
    min.size = 0
  )
```

## Drawing point genetic features

We can draw point genetic features, such as restriction sites or transcription
start sites, with `geom_feature()`, and label them with `geom_feature_label()`.
Both of these geoms take an optional `forward` aesthetic to indicate whether a
feature is oriented and, if so, in what direction (`TRUE` meaning oriented
towards the right and `FALSE` meaning towards the left).

```{r}
ggplot(example_genes, aes(xmin = start, xmax = end, y = molecule, fill = gene)) +
  geom_feature(
    data = example_features,
    aes(x = position, y = molecule, forward = forward)
  ) +
  geom_feature_label(
    data = example_features,
    aes(x = position, y = molecule, label = name, forward = forward)
  ) +
  geom_gene_arrow() +
  geom_blank(data = example_dummies) +
  facet_wrap(~ molecule, scales = "free", ncol = 1) +
  scale_fill_brewer(palette = "Set3") +
  theme_genes()
```