06_1_puromycin.Rmd

---
title: "Exercise 6.1: Linear regression on puromycin data"
author: "Lieven Clement, Alexandre Segers and Milan Malfait"
date: "statOmics, Ghent University (https://statomics.github.io)"
---

<a rel="license" href="https://creativecommons.org/licenses/by-nc-sa/4.0"><img alt="Creative Commons License" style="border-width:0" src="https://i.creativecommons.org/l/by-nc-sa/4.0/88x31.png" /></a>

# Puromycin dataset

Data on the velocity of an enzymatic reaction were obtained by Treloar (1974).
The number of counts per minute of radioactive product from the reaction was
measured as a function of substrate concentration in parts per million (ppm) and
from these counts the initial rate (or velocity) of the reaction was calculated (counts/min/min). The experiment was conducted once with the enzyme treated
with Puromycin, and once with the enzyme untreated.

# Goal

Assess if there is an association between the substrate concentration and rate
for the **treated** enzyme.

Import libraries

```{r, message=FALSE, warning=FALSE}

```

# Import data

In contrast to the other datasets we have worked with so far, this dataset is
not available through a URL link. In stead, the data is directly available from
an R package that was pre-installed in your R working environment. As such, we
can simply do

```{r}
data(Puromycin)
```

and an object called `Puromycin` is immediately available in your working
environment.

# Data wrangling

For this exercise, we only want to assess if there is an association between
the substrate concentration and rate for the **treated** enzyme. As such, we
should filter the data so that we are left with only the treated enzymes.

```{r}

```

# Data exploration

Make a visualization that allows for exploring if there is a linear relationship
between the substrate concentration and enzyme's rate.

```{r, eval=FALSE}
Puromycin %>%
  ggplot(...) + # select which elements of the dataset we need to visualize
  ... # use a relevant plotting geometry
... # you can add some extra elements like axis labels, title, ...
```

Does the relationship look linear? Can you think of any other steps that we
might take to assess this relationship?

```{r}

```

Now may we assume a linear relationship between the substrate concentration and
the enzyme's rate?

# Linear regression

## Formulate the research question

## Check the assumptions

## Interpret the model parameters of the linear model

## Interpret the results, both for the intercept as well as for the slope

## Write a conclusion that answers the research hypothesis.