lecture_lab03.qmd

---
title: "Lecture Lab 3"
author: "Leon Eyrich Jessen"
format:
  revealjs:
    embed-resources: true
    theme: moon
    slide-number: c/t
    width: 1600
    height: 900
    mainfont: avenir
    logo: images/r4bds_logo_small.png
    footer: "R for Bio Data Science"
---



<!--# ---------------------------------------------------------------------- -->
<!--# SLIDE ---------------------------------------------------------------- -->
<!--# ---------------------------------------------------------------------- -->
# Recap of Lab 2

```{r}
#| echo: false
#| eval: true
#| message: false
#| warning: false
library("tidyverse")
cancer_data <- read_tsv(file = "data/cancer_data.tsv")
top10_pharma <- tribble(
  ~Company, ~Revenue,
  "Bristol-Myers Squibb", 22.6,
  "GlaxoSmithKline", 23,
  "Amgen", 23.7,
  "Abbvie", 32.8,
  "Novartis", 34.9,
  "Merck", 39.7,
  "Sanofi", 39.3,
  "Johnson-Johnson", 40.7,
  "Roche", 45.6,
  "Pfizer", 53.7) |> 
  mutate(Company = factor(Company, levels = Company),
         lbl = str_c("$", Revenue))
```



<!--# ---------------------------------------------------------------------- -->
<!--# SLIDE ---------------------------------------------------------------- -->
<!--# ---------------------------------------------------------------------- -->
## What is wrong with this visualisation?

![](images/bad_viz_11.png){fig-align="center"}



## What is wrong with this visualisation?

```{r}
top10_pharma |>  
  ggplot(aes(x = Company,
             y = Revenue,
             fill = Company,
             label = lbl)) +
  geom_col() +
  geom_point(aes(colour = Company),
             size = 20) +
  geom_text(colour = "white",
            size = 6) +
  scale_y_continuous(expand = expansion(mult = c(0, .1))) +
  scale_colour_manual(
    values = c("Bristol-Myers Squibb" = "#2E80AD",
               "GlaxoSmithKline" = "#F18532",
               "Amgen" = "#1E5898",
               "Abbvie" = "#000000",
               "Novartis" = "#29607A",
               "Merck" = "#006F68",
               "Sanofi" = "#43599E",
               "Johnson-Johnson" = "#CF181F",
               "Roche" = "#0E6DB2",
               "Pfizer" = "#33B7E9")) +
  scale_fill_manual(
    values = c("Bristol-Myers Squibb" = "#8AB5DA",
               "GlaxoSmithKline" = "#C1BDB8",
               "Amgen" = "#83A9D5",
               "Abbvie" = "#97AABC",
               "Novartis" = "#84AAC8",
               "Merck" = "#82AFC3",
               "Sanofi" = "#8AAAD7",
               "Johnson-Johnson" = "#BBA4A8",
               "Roche" = "#84B0DC",
               "Pfizer" = "#90C7EB")) +
  labs(x = NULL,
       y = NULL,
       title = "Top 10 pharmaceutical companies in 2019",
       subtitle = "Total revenue from pharmaceutical segment\n(USD billions)") +
  theme_classic(base_size = 18,
                base_family = "Helvetica") +
  theme(axis.text = element_blank(),
        axis.ticks = element_blank(),
        axis.line = element_blank(),
        legend.position = "none",
        panel.background = element_rect(fill = "#C7DFF3"),
        plot.background = element_rect(fill = "#C7DFF3"),
        plot.title = element_text(hjust = 0.1,
                                  vjust = 0.1,
                                  colour = "#1C4E6D",
                                  face = "bold"),
        plot.subtitle = element_text(hjust = 0.1,
                                     vjust = 0.1,
                                     colour = "#7F8285"),
        plot.margin = unit(c(1, -0.5, -0.1, -0.5), "cm"))
```



<!--# ---------------------------------------------------------------------- -->
<!--# SLIDE ---------------------------------------------------------------- -->
<!--# ---------------------------------------------------------------------- -->
## The Cancer Data

:::: {.columns}

::: {.column width="50%"}
```{r}
cancer_data
```

:::

::: {.column width="50%"}
### Dimensions of data

```{r}
#| echo: true
dim(cancer_data)
nrow(cancer_data)
ncol(cancer_data)
```
:::

::::



<!--# ---------------------------------------------------------------------- -->
<!--# SLIDE ---------------------------------------------------------------- -->
<!--# ---------------------------------------------------------------------- -->
## ggplot - The Very Basics

```{r}
#| echo: true
#| eval: false
ggplot(data = my_data,
       mapping = aes(x = v1,
                     y = v2)) +
  geom_point()
```

![](images/vis_ggplot_components.png){fig-align="center"}



<!--# ---------------------------------------------------------------------- -->
<!--# SLIDE ---------------------------------------------------------------- -->
<!--# ---------------------------------------------------------------------- -->
## Basic Examples

### Scatter-plot: `geom_point()`

:::: {.columns}

::: {.column width="50%"}
```{r}
#| echo: true
#| eval: true
my_plot <- ggplot(data = cancer_data,
                  mapping = aes(x = g2E09,
                                y = g7F07)) +
  geom_point()
```
:::

::: {.column width="50%"}
```{r}
#| echo: false
#| eval: true
my_plot
```

:::

::::



<!--# ---------------------------------------------------------------------- -->
<!--# SLIDE ---------------------------------------------------------------- -->
<!--# ---------------------------------------------------------------------- -->
## Basic Examples

### Line-plot: `geom_line()`

:::: {.columns}

::: {.column width="50%"}
```{r}
#| echo: true
#| eval: true
my_plot <- ggplot(data = cancer_data,
                  mapping = aes(x = g2E09,
                                y = g7F07)) +
  geom_line()
```
:::

::: {.column width="50%"}
```{r}
#| echo: false
#| eval: true
my_plot
```

:::

::::



<!--# ---------------------------------------------------------------------- -->
<!--# SLIDE ---------------------------------------------------------------- -->
<!--# ---------------------------------------------------------------------- -->
## Basic Examples

### Box-plot: `geom_boxplot()`

:::: {.columns}

::: {.column width="50%"}
```{r}
#| echo: true
#| eval: true
my_plot <- ggplot(data = cancer_data,
                  mapping = aes(x = g2E09)) +
  geom_boxplot()
```
:::

::: {.column width="50%"}
```{r}
#| echo: false
#| eval: true
my_plot
```

:::

::::



<!--# ---------------------------------------------------------------------- -->
<!--# SLIDE ---------------------------------------------------------------- -->
<!--# ---------------------------------------------------------------------- -->
## Basic Examples

### Histogram-plot: `geom_histogram()`

:::: {.columns}

::: {.column width="50%"}
```{r}
#| echo: true
#| eval: true
my_plot <- ggplot(data = cancer_data,
                  mapping = aes(x = g2E09)) +
  geom_histogram(binwidth = 0.1)
```
:::

::: {.column width="50%"}
```{r}
#| echo: false
#| eval: true
my_plot
```

:::

::::

_Note! Here, you'll get a warning if you do not state your choice of bin_



<!--# ---------------------------------------------------------------------- -->
<!--# SLIDE ---------------------------------------------------------------- -->
<!--# ---------------------------------------------------------------------- -->
## Basic Examples

### Densitogram-plot: `geom_density()`

:::: {.columns}

::: {.column width="50%"}
```{r}
#| echo: true
#| eval: true
my_plot <- ggplot(data = cancer_data,
                  mapping = aes(x = g2E09)) +
  geom_density()
```
:::

::: {.column width="50%"}
```{r}
#| echo: false
#| eval: true
my_plot
```

:::

::::



<!--# ---------------------------------------------------------------------- -->
<!--# SLIDE ---------------------------------------------------------------- -->
<!--# ---------------------------------------------------------------------- -->
## Extended Examples

### boxplot of expression levels stratified on the variable `age_group` 

:::: {.columns}

::: {.column width="50%"}
```{r}
#| echo: true
#| eval: true
my_plot <- ggplot(data = cancer_data,
                  mapping = aes(x = event_label,
                                y = g2E09)) +
  geom_boxplot()
```
:::

::: {.column width="50%"}
```{r}
#| echo: false
#| eval: true
my_plot
```

:::

::::



<!--# ---------------------------------------------------------------------- -->
<!--# SLIDE ---------------------------------------------------------------- -->
<!--# ---------------------------------------------------------------------- -->
## Extended Examples

### GROUP ASSIGNMENT

:::: {.columns}

::: {.column width="50%"}
```{r}
#| echo: true
#| eval: true
my_plot <- ggplot(data = cancer_data,
                  mapping = aes(x = g2E09,
                                fill = event_label)) +
  geom_density()
```
:::

::: {.column width="50%"}
```{r}
#| echo: false
#| eval: true
my_plot
```

:::

::::



<!--# ---------------------------------------------------------------------- -->
<!--# SLIDE ---------------------------------------------------------------- -->
<!--# ---------------------------------------------------------------------- -->
## Extended Examples

### GROUP ASSIGNMENT - Customisation

:::: {.columns}

::: {.column width="50%"}
```{r}
#| echo: false
#| eval: true
ggplot(data = cancer_data,
       mapping = aes(x = g2E09,
                     fill = event_label)) +
  geom_density()
```
:::

::: {.column width="50%"}
```{r}
#| echo: false
#| eval: true
ggplot(data = cancer_data,
       mapping = aes(x = g2E09,
                     y = event_label,
                     fill = event_label)) +
  geom_vline(xintercept = 0) +
  geom_violin(scale = "width",
              adjust = 0.5) +
  geom_boxplot(width = 0.2,
               fill = "grey95") +
  scale_fill_manual(values = c("#e3eaff", "#f8e3ff")) +
  theme_bw(base_family = "Avenir", base_size = 14) +
  theme(panel.grid.major.x = element_blank(),
        panel.grid.major.y = element_line(colour = "grey"),
        legend.position = "none",
        plot.background = element_rect(fill = "#fff8e3"),
        panel.background = element_rect(fill = "#eaffe3")) +
  labs(y = "Event Label")
```

:::

::::

_Same data in these plots! If you can think it - You can build it in `ggplot`_


<!--# ---------------------------------------------------------------------- -->
<!--# SLIDE ---------------------------------------------------------------- -->
<!--# ---------------------------------------------------------------------- -->
## Extended Examples

### Plot Recreation

:::: {.columns}

::: {.column width="50%"}
```{r}
#| echo: true
#| eval: true
my_plot <- ggplot(data = cancer_data,
                  aes(x = event_label,
                      y = g1CNS507,
                      fill = event_label)) +
  geom_boxplot(alpha = 0.5,
               show.legend = FALSE) +
  coord_flip() +
  labs(x = "Event After Diagnosis",
       y = str_c("Expression level of g1CNS507 ",
                 "(log2 transformed)"),
       title = str_c("A prognostic DNA signature ",
                     "for T1T2 node-negative ",
                     "breast cancer patients"),
       subtitle = str_c("Labelling: good = no ",
                        " event, poor = early ",
                        "metastasis"),
       caption = "Data from Gravier et al. (2010)")
```
:::

::: {.column width="50%"}
```{r}
#| echo: false
#| eval: true
my_plot
```

:::

::::




<!--# ---------------------------------------------------------------------- -->
<!--# SLIDE ---------------------------------------------------------------- -->
<!--# ---------------------------------------------------------------------- -->
## A Few Tips and Tricks

- Use a pen and paper to doodle your thoughts on a good visualisation

- When googling write e.g. "Custom legend labels" and then do an image search to find a plot that look somewhat like what you are looking for and then go to the page, most often, there will be some code

- Stick to the following syntaxical best-practises:

```{r}
#| echo: true
#| eval: false
ggplot(data = my_data,
       mapping = aes(x = v1,
                     y = v2,
                     fill = v3)) +
  geom_something() +
  labs(x = "My x",
       y = "My y")
```

- **NOTE! You are expected to adhere to a specific code style moving forward in this course**
- Because... Yes, syntax matters!



<!--# ---------------------------------------------------------------------- -->
<!--# SLIDE ---------------------------------------------------------------- -->
<!--# ---------------------------------------------------------------------- -->
# Data Visualisation II



<!--# ---------------------------------------------------------------------- -->
<!--# SLIDE ---------------------------------------------------------------- -->
<!--# ---------------------------------------------------------------------- -->
## First: Make sure you're on track!

### Lab II Learning Objectives

-   Explains the basic theory of data visualisation

-   Decipher the components of a ggplot

-   Use ggplot to do basic data visualisation

*Making sure you are in tune with the LOs as we progress is essential for tracking your learning!*



<!--# ---------------------------------------------------------------------- -->
<!--# SLIDE ---------------------------------------------------------------- -->
<!--# ---------------------------------------------------------------------- -->
## Customisation

- If you can think it, ggplot can plot

- The trick is to build experience, practice makes perfect!

- Let us go over a few examples



<!--# ---------------------------------------------------------------------- -->
<!--# SLIDE ---------------------------------------------------------------- -->
<!--# ---------------------------------------------------------------------- -->
## Customisation Examples

### Adding text to data points

:::: {.columns}

::: {.column width="50%"}
```{r}
#| echo: true
#| eval: true
my_plot <- ggplot(data = cancer_data,
                  mapping = aes(x = age,
                                y = g7E05,
                                label = pt_id)) +
  geom_text()
```
:::

::: {.column width="50%"}
```{r}
#| echo: false
#| eval: true
my_plot
```
:::

::::



<!--# ---------------------------------------------------------------------- -->
<!--# SLIDE ---------------------------------------------------------------- -->
<!--# ---------------------------------------------------------------------- -->
## Customisation Examples

### Adding labels to data points

:::: {.columns}

::: {.column width="50%"}
```{r}
#| echo: true
#| eval: true
my_plot <- ggplot(data = cancer_data,
                  mapping = aes(x = age,
                                y = g7E05,
                                label = pt_id)) +
  geom_label()
```
:::

::: {.column width="50%"}
```{r}
#| echo: false
#| eval: true
my_plot
```
:::

::::



<!--# ---------------------------------------------------------------------- -->
<!--# SLIDE ---------------------------------------------------------------- -->
<!--# ---------------------------------------------------------------------- -->
## Customisation Examples

### `age_group` stratification

:::: {.columns}

::: {.column width="50%"}
```{r}
#| echo: true
#| eval: true
my_plot <- ggplot(data = cancer_data,
                  mapping = aes(x = age_group,
                                y = g7E05)) +
  geom_boxplot()
```
:::

::: {.column width="50%"}
```{r}
#| echo: false
#| eval: true
my_plot
```
:::

::::



<!--# ---------------------------------------------------------------------- -->
<!--# SLIDE ---------------------------------------------------------------- -->
<!--# ---------------------------------------------------------------------- -->
## Customisation Examples

### `event_label` stratification

:::: {.columns}

::: {.column width="50%"}
```{r}
#| echo: true
#| eval: true
my_plot <- ggplot(data = cancer_data,
                  mapping = aes(x = age_group,
                                y = g7E05,
                                fill = event_label)) +
  geom_boxplot()
```
:::

::: {.column width="50%"}
```{r}
#| echo: false
#| eval: true
my_plot
```
:::

::::



<!--# ---------------------------------------------------------------------- -->
<!--# SLIDE ---------------------------------------------------------------- -->
<!--# ---------------------------------------------------------------------- -->
## Customisation Examples

### Adding a theme (A collection of settings)

:::: {.columns}

::: {.column width="50%"}
```{r}
#| echo: true
#| eval: true
my_plot <- ggplot(data = cancer_data,
                  mapping = aes(x = age_group,
                                y = g7E05,
                                fill = event_label)) +
  geom_boxplot() +
  theme_classic()
```
:::

::: {.column width="50%"}
```{r}
#| echo: false
#| eval: true
my_plot
```
:::

::::



<!--# ---------------------------------------------------------------------- -->
<!--# SLIDE ---------------------------------------------------------------- -->
<!--# ---------------------------------------------------------------------- -->
## Customisation Examples

### Changing the font size

:::: {.columns}

::: {.column width="50%"}
```{r}
#| echo: true
#| eval: true
my_plot <- ggplot(data = cancer_data,
                  mapping = aes(x = age_group,
                                y = g7E05,
                                fill = event_label)) +
  geom_boxplot() +
  theme_classic(base_size = 18)
```
:::

::: {.column width="50%"}
```{r}
#| echo: false
#| eval: true
my_plot
```
:::

::::



<!--# ---------------------------------------------------------------------- -->
<!--# SLIDE ---------------------------------------------------------------- -->
<!--# ---------------------------------------------------------------------- -->
## Customisation Examples

### Changing the font

:::: {.columns}

::: {.column width="50%"}
```{r}
#| echo: true
#| eval: true
my_plot <- ggplot(data = cancer_data,
                  mapping = aes(x = age_group,
                                y = g7E05,
                                fill = event_label)) +
  geom_boxplot() +
  theme_classic(base_size = 18,
                base_family = "Avenir")
```
:::

::: {.column width="50%"}
```{r}
#| echo: false
#| eval: true
my_plot
```
:::

::::



<!--# ---------------------------------------------------------------------- -->
<!--# SLIDE ---------------------------------------------------------------- -->
<!--# ---------------------------------------------------------------------- -->
## Customisation Examples

### Adding some labels

:::: {.columns}

::: {.column width="50%"}
```{r}
#| echo: true
#| eval: true
my_plot <- ggplot(data = cancer_data,
                  mapping = aes(x = age_group,
                                y = g7E05,
                                fill = event_label)) +
  geom_boxplot() +
  labs(x = "Patient Age Group",
       y = "log2 expression of g7E05") +
  theme_classic(base_size = 18,
                base_family = "Avenir")
```
:::

::: {.column width="50%"}
```{r}
#| echo: false
#| eval: true
my_plot
```
:::

::::



<!--# ---------------------------------------------------------------------- -->
<!--# SLIDE ---------------------------------------------------------------- -->
<!--# ---------------------------------------------------------------------- -->
## Customisation Examples

### Relocating the legend

:::: {.columns}

::: {.column width="50%"}
```{r}
#| echo: true
#| eval: true
my_plot <- ggplot(data = cancer_data,
                  mapping = aes(x = age_group,
                                y = g7E05,
                                fill = event_label)) +
  geom_boxplot() +
  labs(x = "Patient Age Group",
       y = "log2 expression of g7E05") +
  theme_classic(base_size = 18,
                base_family = "Avenir") +
  theme(legend.position = "bottom")
```
:::

::: {.column width="50%"}
```{r}
#| echo: false
#| eval: true
my_plot
```
:::

::::



<!--# ---------------------------------------------------------------------- -->
<!--# SLIDE ---------------------------------------------------------------- -->
<!--# ---------------------------------------------------------------------- -->
## Customisation Examples

### Customising the legend

- Note the colour mapping green is good, red is bad

:::: {.columns}

::: {.column width="50%"}
```{r}
#| echo: true
#| eval: true
my_plot <- ggplot(data = cancer_data,
                  mapping = aes(x = age_group,
                                y = g7E05,
                                fill = event_label)) +
  geom_boxplot() +
  scale_fill_manual(labels = c("No", "Yes"),
                    values = c("green", "red")) +
  labs(x = "Patient Age Group",
       y = "log2 expression of g7E05",
       fill = "Early Metastasis") +
  theme_classic(base_size = 18,
                base_family = "Avenir") +
  theme(legend.position = "bottom")
```
:::

::: {.column width="50%"}
```{r}
#| echo: false
#| eval: true
my_plot
```
:::

::::



<!--# ---------------------------------------------------------------------- -->
<!--# SLIDE ---------------------------------------------------------------- -->
<!--# ---------------------------------------------------------------------- -->
## Customisation Examples

### Adding transparency

:::: {.columns}

::: {.column width="50%"}
```{r}
#| echo: true
#| eval: true
my_plot <- ggplot(data = cancer_data,
                  mapping = aes(x = age_group,
                                y = g7E05,
                                fill = event_label)) +
  geom_boxplot(alpha = 0.5) +
  scale_fill_manual(labels = c("No", "Yes"),
                    values = c("green", "red")) +
  labs(x = "Patient Age Group",
       y = "log2 expression of g7E05",
       fill = "Early Metastasis") +
  theme_classic(base_size = 18,
                base_family = "Avenir") +
  theme(legend.position = "bottom")
```
:::

::: {.column width="50%"}
```{r}
#| echo: false
#| eval: true
my_plot
```
:::

::::



<!--# ---------------------------------------------------------------------- -->
<!--# SLIDE ---------------------------------------------------------------- -->
<!--# ---------------------------------------------------------------------- -->
## Customisation Examples

### Marking a threshold

:::: {.columns}

::: {.column width="50%"}
```{r}
#| echo: true
#| eval: true
my_plot <- ggplot(data = cancer_data,
                  mapping = aes(x = age_group,
                                y = g7E05,
                                fill = event_label)) +
  geom_hline(yintercept = 0,
             linetype = "dashed") +
  geom_boxplot(alpha = 0.5) +
  scale_fill_manual(labels = c("No", "Yes"),
                    values = c("green", "red")) +
  labs(x = "Patient Age Group",
       y = "log2 expression of g7E05",
       fill = "Early Metastasis") +
  theme_classic(base_size = 18,
                base_family = "Avenir") +
  theme(legend.position = "bottom")
```
:::

::: {.column width="50%"}
```{r}
#| echo: false
#| eval: true
my_plot
```
:::

::::

_Note! Layer order matters!_

<!--# ---------------------------------------------------------------------- -->
<!--# SLIDE ---------------------------------------------------------------- -->
<!--# ---------------------------------------------------------------------- -->
## Plotting multiple plots

:::: {.columns}

::: {.column width="50%"}
```{r}
#| echo: true
#| eval: true
pl1 <- ggplot(data = cancer_data,
              mapping = aes(x = age_group,
                            y = g7E05,
                            fill = event_label)) +
  geom_hline(yintercept = 0,
             linetype = "dashed") +
  geom_boxplot(alpha = 0.5) +
  scale_fill_manual(labels = c("No", "Yes"),
                    values = c("green", "red")) +
  labs(x = "Patient Age Group",
       y = "log2 expression of g7E05",
       fill = "Early Metastasis") +
  theme_classic(base_size = 12,
                base_family = "Avenir") +
  theme(legend.position = "bottom")
```
:::

::: {.column width="50%"}
```{r}
#| echo: true
#| eval: true
pl2 <- ggplot(data = cancer_data,
              mapping = aes(x = age_group,
                            y = g8C05,
                            fill = event_label)) +
  geom_hline(yintercept = 0,
             linetype = "dashed") +
  geom_boxplot(alpha = 0.5) +
  scale_fill_manual(labels = c("No", "Yes"),
                    values = c("green", "red")) +
  labs(x = "Patient Age Group",
       y = "log2 expression of g8C05",
       fill = "Early Metastasis") +
  theme_classic(base_size = 12,
                base_family = "Avenir") +
  theme(legend.position = "bottom")
```
:::

::::

_If you had not noticed before, everything is an object, even a plot!_

<!--# ---------------------------------------------------------------------- -->
<!--# SLIDE ---------------------------------------------------------------- -->
<!--# ---------------------------------------------------------------------- -->
## Plotting multiple plots

```{r}
#| echo: true
#| eval: true
#| out-width: 90%
#| fig-align: center
library("patchwork")
pl1 + pl2
```



<!--# ---------------------------------------------------------------------- -->
<!--# SLIDE ---------------------------------------------------------------- -->
<!--# ---------------------------------------------------------------------- -->
## Plotting multiple plots

```{r}
#| echo: true
#| eval: true
#| out-width: 90%
#| fig-align: center
pl1 / pl2
```




<!--# ---------------------------------------------------------------------- -->
<!--# SLIDE ---------------------------------------------------------------- -->
<!--# ---------------------------------------------------------------------- -->
## Plotting multiple plots

```{r}
#| echo: true
#| eval: true
#| out-width: 90%
#| fig-align: center
pl1 / (pl2 + pl1)
```



<!--# ---------------------------------------------------------------------- -->
<!--# SLIDE ---------------------------------------------------------------- -->
<!--# ---------------------------------------------------------------------- -->
## Summary

- ggplot is _very_ flexible

- Practise makes perfect

- Compare it with learning a langauge, initially there is a vocabulary boundary

- Return to these slides, but also remember a meta learning objective is to seek out the solutions online

- A VERY good place to go to get input is the RStudio community pages: [https://community.rstudio.com](https://community.rstudio.com)

- Also, have fun!

# Break, then exercises!