08_4_kpna2.Rmd

---
title: "8.4. Multiple Regression: KPNA2 example"
author: "Lieven Clement"
date: "statOmics, Ghent University (https://statomics.github.io)"
---

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# Background

Background: Histologic grade in breast cancer provides clinically important
prognostic information. Researchers examined whether histologic grade was
associated with gene expression profiles of breast cancers and whether such
profiles could be used to improve histologic grading. In this tutorial we
will assess the association between histologic grade and the expression of
the KPNA2 gene that is known to be associated with poor breast cancer prognosis.
The patients, however, do not only differ in the histologic grade,
but also on their lymph node status. The lymph nodes were not affected (0)
or surgically removed (1).

# Import data

```{r}

```

# Data wrangling

Transform the variable grade and node to a factor.

```{r}

```

# Data exploration

Histologic grade and lymph node status can be associated with the KPNA2 gene
expression. Moreover, it is also possible that the differential expression
associated with histological grade is different in patients that have
unaffected lymph nodes and patients for which the lymph nodes had to be removed.

Make a relevant plot that contains information on KPNA2 expression and both
explanatory variables grade and node.

```{r}

```

What does the plot suggest?

# Linear regression

1. Specify the model, interpret each model parameter in the model.

2. Formulate the relevant research questions

3. Translate them in a null and alternative hyptheses.

4. Perform the hypothesis tests  and calculate the confidence intervals.

# Formulate your conclusions in terms of the research question