Dose response assay plots.Rmd

---
title: "Dose response assay plots"
author: "Emily J Tallerday"
date: "`r Sys.Date()`"
output: github_document
---

# Setup

## Load packages to be used

```{r}
packages <- c("rmarkdown", "pandoc", "formatR", "tidyverse", "gridExtra", "ggpubr", "viridis", "ggthemes", "here", "gplots", "cowplot", "ggtext", "ggsignif", "ggokabeito")
pacman::p_load(char = packages, install = T, character.only = T)
```

## Set ggplot theme

My personal preference:

```{r}
theme_set(theme_light())
```

## Define functions

This section may be empty if functions are not needed.

# Data

## Import

```{r}
BA_response <- read.csv(here(r"(Data\06292023_Eva_BA response data.csv)"))
```

NOTE that this data was provided by Eva from a magenta box BA dose response assay done in Summer 2023.

## Tidy data for easy working

```{r}
BA_response$treatment[BA_response$treatment == "veh"] <- 0
```

```{r}
BA_response$genotype <- as.factor(BA_response$genotype)
```

```{r}
BA_response$treatment <- as.numeric(BA_response$treatment)
```

```{r}
colnames(BA_response) <- c("Genotype", "Conc. BA (ng/uL)", "Shoot length (cm)", "Root length (cm)")
```

# Plot

## Linear regression

The code for the following plot was modified from [this tutorial by datanovia](https://rpkgs.datanovia.com/ggpubr/reference/stat_regline_equation.html).

```{r, echo = F, include=F, dev = "png", dpi = 300}
## This is my messy, working, version. This will not be included in the knit document! Refer to the chunk below, instead.
BA_response %>%
  ggplot(aes(x = `Conc. BA (ng/uL)`, y = `Root length (cm)`, color = Genotype, fill = Genotype)) +
  geom_point(shape = 21, size = 2, alpha = 0.5, color = "black") +
  geom_smooth(method = "lm", se = T, alpha = 0.2) +
  facet_wrap(~Genotype,
    ncol = 4,
    nrow = 1,
    scales = "free"
  ) +
  theme(strip.background = element_blank()) +

  # stat_cor(#label.y = 8.8,
  #          #label.x = 10.5,
  #          color = "black") +
  stat_regline_equation( # label.y = 8,
    # label.x = 10.5,
    color = "black"
  ) +
  labs(
    color = "Genotype", # in legend
    fill = "Genotype" # in legend
  ) +
  # scale_color_hue(labels = Genotype) + # color variable
  # theme(legend.text = element_markdown()) +
  scale_color_okabe_ito() +
  scale_fill_okabe_ito() %>% # fill variable
  suppressWarnings() %>%
  suppressMessages()
```

```{r, echo = T, include=T, warning=F, message=F}
BA_response %>%
  ggplot(aes(x = `Conc. BA (ng/uL)`, y = `Root length (cm)`, color = Genotype, fill = Genotype)) +
  geom_point(shape = 21, size = 2, alpha = 0.5, color = "black") +
  geom_smooth(method = "lm", se = T, alpha = 0.2) +
  facet_wrap(~Genotype,
    ncol = 4,
    nrow = 1,
    scales = "free"
  ) +
  theme(strip.background = element_blank()) +
  stat_regline_equation(color = "black") +
  labs(
    color = "Genotype",
    fill = "Genotype"
  ) +
  scale_color_okabe_ito() +
  scale_fill_okabe_ito()
```

# Session info

```{r, include=T, echo=T}
sessionInfo()
```