Recap Lab 4

Leon Eyrich Jessen

A Few Meta Points…

Paths

The .Rproj-file defines your project root, i.e. everything is relative to where this file is
In your .Qmd-file you need to think about where files you need are
To load something from data, you need to specify data/my_data.csv
To load from _raw in data, you specify data/_raw/my_raw_data.xlsx

Qmd

Load libraries before calling needed functions
Do a Run All check (Menu above Quarto doc \(\rightarrow\) Run \(\rightarrow\) Run All)
When getting errors, make sure read the error message

Group work

Each student must have a and work in a project on the RStudio Cloud Server
Each student must to actively write code (no one has ever gotten good at football by watching others play \(\rightarrow\) Learning by actively doing)
Make sure to talk together in your groups, you will learn something by explaining
Group work is a Learning Objective element in this course \(\rightarrow\) Outlook to collaboratice bio data science!

Recap

Task 1 - Recreate the following plot

pl <- ggplot(data = SPE_ENV,
             mapping = aes(x = OTU_Count,
                           y = Taxa,
                           fill = site)) +
  geom_boxplot()

Task 2 - Recreate the following plot

pl <- ggplot(data = SPE_ENV,
             mapping = aes(x = site,
                           y = Temp)) +
  geom_boxplot()

Task 3 - Recreate the following plot

pl <- ggplot(data = SPE_ENV,
             mapping = aes(x = Temp,
                           y = pH,
                           colour = site)) +
  geom_point()

Task 4 - Recreate the following plot

pl <- ggplot(data = SPE_ENV,
             mapping = aes(x = Temp,
                           y = pH,
                           colour = site,
                           label = Samples)) +
  geom_label(size = 3)

Task 5 - Recreate the following plot

pl <- ggplot(data = SPE_ENV,
             mapping = aes(x = NH4,
                           fill = site)) +
  geom_density()

Task 5 - Recreate the following plot - OR

pl <- pl +
  scale_x_log10()

Note this syntax and think about what it means

Task 6 - Recreate the following plot

pl <- ggplot(data = SPE_ENV,
             mapping = aes(x = CODt,
                           y = CODs,
                           colour = site)) +
  geom_point() +
  geom_smooth(method = "lm")

Task 7 - Recreate the following plot

pl <- ggplot(data = SPE_ENV,
             mapping = aes(x = Taxa,
                           y = Samples,
                           fill = OTU_Count)) +
  geom_tile() +
  scale_fill_gradient2(midpoint = 10000,
                       low = "blue",
                       mid = "white",
                       high = "red") +
  theme_classic(base_size = 8) +
  theme(legend.position = "bottom",
        axis.text.x = element_text(angle = 45,
                                   hjust = 1))

Task 8 - Recreate the following plot

library("ggridges")
pl <- ggplot(data = SPE_ENV_targets,
             mapping = aes(x = OTU_Count,
                           y = Taxa,
                           fill = Taxa)) +
  geom_density_ridges(alpha = 0.5) +
  scale_fill_viridis_d() +
  labs(x = "OTU Count",
       y = "Taxa Identified",
       title = "OTU Count Distribution for 5 Taxa Stratified on Site",
       caption = "Data from doi.org/10.1111/1751-7915.12334") +
  theme_minimal(base_family = "Avenir",
                base_size = 12) +
  theme(legend.position = "bottom") +
  facet_wrap(vars(site),
             ncol = 2)

Task 9 - GROUP ASSIGNMENT

Let us take a look at this years submissions…