# Generalised linear models

This course is about counting: we will learn how to analyse data
on how many times a certain experimental outcome is observed.
We focus on generalised linear models (GLMs).
**Please note that we cannot go into the specific data analysis problems of your particular project.**

**Instructor:** András Aszódi.

## Topics

- How many mice will die? Fitting dose-response curves with a binomial GLM
- How many reads are sequenced? The Poisson GLM
- What to do when extra noise is present? Quasi-Poisson and negative binomial GLM

## Out of scope

This course will not teach you bioinformatics.
In particular, *no high-throughput sequencing data will be used* because they are impractically large,
and not everyone on campus is working with sequencing.

If you are interested in the statistical background of gene expression analysis with high-throughput sequencing, then please take our RNA-Seq data analysis course.

## Prerequisites

Participants should have a good understanding of basic statistics. Our Statistics with R course helps you refresh your stats skills.

Basic familiarity with R is advantageous, in particular:

- Using the R Studio environment
- How to invoke R functions, pass optional/named parameters
- Some familiarity with simple plotting commands

If you have attended our R as a programming language training then you are well equipped to take this course, but this is not a strict pre-requisite.

## Practical information

**Number of participants:** minimum 5, maximum 10.

**Length:** The course takes one half-day,
from 09:00 to 13:00 with 2 breaks.