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.
- 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.
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.
Number of participants: minimum 5, maximum 10.
Length: The course takes one half-day, from 09:00 to 13:00 with 2 breaks.