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Bioinformatics Training

Bioinformatics course timetable

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Mon 15 Jul – Fri 11 Oct

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July 2024

Mon 15
Linear mixed effects models (IN-PERSON) (1 of 2) Finished 09:30 - 17:00 Bioinformatics Training Room, Craik-Marshall Building

This course gives an introduction to linear mixed effects models, also called multi-level models or hierarchical models, for the purposes of using them in your own research or studies.

We emphasise the practical skills and key concepts needed to work with these models, using applied examples and real datasets.

After completing the course, you should have:

  • A conceptual understanding of what mixed effects models are, and when they should be used
  • Familiarity with fitting and interpreting mixed effects models using the lme4 package in R

Please note that this course builds on knowledge of linear modelling, therefore should not be considered a general introduction to statistical modelling.


If you do not have a University of Cambridge Raven account please book or register your interest here.

Additional information
  • ♿ The training room is located on the first floor and there is currently no wheelchair or level access.
  • Our courses are only free for registered University of Cambridge students. All other participants will be charged according to our charging policy.
  • Attendance will be taken on all courses and a charge is applied for non-attendance. After you have booked a place, if you are unable to attend any of the live sessions, please email the Bioinfo Team.
  • Further details regarding eligibility criteria are available here.
  • Guidance on visiting Cambridge and finding accommodation is available here.
Tue 16
Linear mixed effects models (IN-PERSON) (2 of 2) Finished 09:30 - 17:00 Bioinformatics Training Room, Craik-Marshall Building

This course gives an introduction to linear mixed effects models, also called multi-level models or hierarchical models, for the purposes of using them in your own research or studies.

We emphasise the practical skills and key concepts needed to work with these models, using applied examples and real datasets.

After completing the course, you should have:

  • A conceptual understanding of what mixed effects models are, and when they should be used
  • Familiarity with fitting and interpreting mixed effects models using the lme4 package in R

Please note that this course builds on knowledge of linear modelling, therefore should not be considered a general introduction to statistical modelling.


If you do not have a University of Cambridge Raven account please book or register your interest here.

Additional information
  • ♿ The training room is located on the first floor and there is currently no wheelchair or level access.
  • Our courses are only free for registered University of Cambridge students. All other participants will be charged according to our charging policy.
  • Attendance will be taken on all courses and a charge is applied for non-attendance. After you have booked a place, if you are unable to attend any of the live sessions, please email the Bioinfo Team.
  • Further details regarding eligibility criteria are available here.
  • Guidance on visiting Cambridge and finding accommodation is available here.
Thu 18
Extracting biological information from gene lists (IN-PERSON) Finished 09:30 - 17:30 Bioinformatics Training Room, Craik-Marshall Building

Many experimental designs end up producing lists of hits, usually based around genes or transcripts. Sometimes these lists are small enough that they can be examined individually, but often it is useful to do a more structured functional analysis to try to automatically determine any interesting biological themes which turn up in the lists.

This course looks at the various software packages, databases and statistical methods which may be of use in performing such an analysis. As well as being a practical guide to performing these types of analysis the course will also look at the types of artefacts and bias which can lead to false conclusions about functionality and will look at the appropriate ways to both run the analysis and present the results for publication.


If you do not have a University of Cambridge Raven account please book or register your interest here.

Additional information
  • Our courses are only free for registered University of Cambridge students. All other participants will be charged according to our charging policy.
  • Attendance will be taken on all courses and a charge is applied for non-attendance, including for University of Cambridge students. After you have booked a place, if you are unable to attend any of the live sessions, please email the Bioinfo Team.
  • Further details regarding eligibility criteria are available here.
  • Guidance on visiting Cambridge and finding accommodation is available here.
Mon 22
Working with Bacterial Genomes (IN-PERSON) new (1 of 5) Finished 09:30 - 17:30 Bioinformatics Training Room, Craik-Marshall Building

This comprehensive course equips you with essential skills and knowledge in bacterial genomics analysis, primarily using Illumina-sequenced samples. You'll gain an understanding of how to select the most appropriate analysis workflow, tailored to the genome diversity of a given bacterial species. Through hands-on training, you'll apply both de novo assembly and reference-based mapping approaches to obtain bacterial genomes for your isolates. You will apply standardised workflows for genome assembly and annotation, including quality assessment criteria to ensure the reliability of your results. Along with typing bacteria using methods such as MLST, you'll learn how to construct phylogenetic trees using whole genome and core genome alignments, enabling you to explore the evolutionary relationships among bacterial isolates. You’ll extend this to estimate a time-scaled phylogeny using a starting phylogenetic tree. Lastly, you'll apply methods to detect antimicrobial resistance genes. As examples we will use Mycobacterium tuberculosis, Staphylococcus aureus and Streptococcus pneumoniae, allowing you to become well-equipped to conduct bacterial genomics analyses on a range of species.


If you do not have a University of Cambridge Raven account please book or register your interest here.

Additional information
  • ♿ The training room is located on the first floor and there is currently no wheelchair or level access.
  • Our courses are only free for registered University of Cambridge students. All other participants will be charged according to our charging policy.
  • Attendance will be taken on all courses and a charge is applied for non-attendance, including for University of Cambridge students. After you have booked a place, if you are unable to attend any of the live sessions, please email the Bioinfo Team.
  • Further details regarding eligibility criteria are available here.
  • Guidance on visiting Cambridge and finding accommodation is available here.
Tue 23
Working with Bacterial Genomes (IN-PERSON) new (2 of 5) Finished 09:30 - 17:30 Bioinformatics Training Room, Craik-Marshall Building

This comprehensive course equips you with essential skills and knowledge in bacterial genomics analysis, primarily using Illumina-sequenced samples. You'll gain an understanding of how to select the most appropriate analysis workflow, tailored to the genome diversity of a given bacterial species. Through hands-on training, you'll apply both de novo assembly and reference-based mapping approaches to obtain bacterial genomes for your isolates. You will apply standardised workflows for genome assembly and annotation, including quality assessment criteria to ensure the reliability of your results. Along with typing bacteria using methods such as MLST, you'll learn how to construct phylogenetic trees using whole genome and core genome alignments, enabling you to explore the evolutionary relationships among bacterial isolates. You’ll extend this to estimate a time-scaled phylogeny using a starting phylogenetic tree. Lastly, you'll apply methods to detect antimicrobial resistance genes. As examples we will use Mycobacterium tuberculosis, Staphylococcus aureus and Streptococcus pneumoniae, allowing you to become well-equipped to conduct bacterial genomics analyses on a range of species.


If you do not have a University of Cambridge Raven account please book or register your interest here.

Additional information
  • ♿ The training room is located on the first floor and there is currently no wheelchair or level access.
  • Our courses are only free for registered University of Cambridge students. All other participants will be charged according to our charging policy.
  • Attendance will be taken on all courses and a charge is applied for non-attendance, including for University of Cambridge students. After you have booked a place, if you are unable to attend any of the live sessions, please email the Bioinfo Team.
  • Further details regarding eligibility criteria are available here.
  • Guidance on visiting Cambridge and finding accommodation is available here.
Wed 24
Working with Bacterial Genomes (IN-PERSON) new (3 of 5) Finished 09:30 - 17:30 Bioinformatics Training Room, Craik-Marshall Building

This comprehensive course equips you with essential skills and knowledge in bacterial genomics analysis, primarily using Illumina-sequenced samples. You'll gain an understanding of how to select the most appropriate analysis workflow, tailored to the genome diversity of a given bacterial species. Through hands-on training, you'll apply both de novo assembly and reference-based mapping approaches to obtain bacterial genomes for your isolates. You will apply standardised workflows for genome assembly and annotation, including quality assessment criteria to ensure the reliability of your results. Along with typing bacteria using methods such as MLST, you'll learn how to construct phylogenetic trees using whole genome and core genome alignments, enabling you to explore the evolutionary relationships among bacterial isolates. You’ll extend this to estimate a time-scaled phylogeny using a starting phylogenetic tree. Lastly, you'll apply methods to detect antimicrobial resistance genes. As examples we will use Mycobacterium tuberculosis, Staphylococcus aureus and Streptococcus pneumoniae, allowing you to become well-equipped to conduct bacterial genomics analyses on a range of species.


If you do not have a University of Cambridge Raven account please book or register your interest here.

Additional information
  • ♿ The training room is located on the first floor and there is currently no wheelchair or level access.
  • Our courses are only free for registered University of Cambridge students. All other participants will be charged according to our charging policy.
  • Attendance will be taken on all courses and a charge is applied for non-attendance, including for University of Cambridge students. After you have booked a place, if you are unable to attend any of the live sessions, please email the Bioinfo Team.
  • Further details regarding eligibility criteria are available here.
  • Guidance on visiting Cambridge and finding accommodation is available here.
Thu 25
Working with Bacterial Genomes (IN-PERSON) new (4 of 5) Finished 09:30 - 17:30 Bioinformatics Training Room, Craik-Marshall Building

This comprehensive course equips you with essential skills and knowledge in bacterial genomics analysis, primarily using Illumina-sequenced samples. You'll gain an understanding of how to select the most appropriate analysis workflow, tailored to the genome diversity of a given bacterial species. Through hands-on training, you'll apply both de novo assembly and reference-based mapping approaches to obtain bacterial genomes for your isolates. You will apply standardised workflows for genome assembly and annotation, including quality assessment criteria to ensure the reliability of your results. Along with typing bacteria using methods such as MLST, you'll learn how to construct phylogenetic trees using whole genome and core genome alignments, enabling you to explore the evolutionary relationships among bacterial isolates. You’ll extend this to estimate a time-scaled phylogeny using a starting phylogenetic tree. Lastly, you'll apply methods to detect antimicrobial resistance genes. As examples we will use Mycobacterium tuberculosis, Staphylococcus aureus and Streptococcus pneumoniae, allowing you to become well-equipped to conduct bacterial genomics analyses on a range of species.


If you do not have a University of Cambridge Raven account please book or register your interest here.

Additional information
  • ♿ The training room is located on the first floor and there is currently no wheelchair or level access.
  • Our courses are only free for registered University of Cambridge students. All other participants will be charged according to our charging policy.
  • Attendance will be taken on all courses and a charge is applied for non-attendance, including for University of Cambridge students. After you have booked a place, if you are unable to attend any of the live sessions, please email the Bioinfo Team.
  • Further details regarding eligibility criteria are available here.
  • Guidance on visiting Cambridge and finding accommodation is available here.
Fri 26
Working with Bacterial Genomes (IN-PERSON) new (5 of 5) Finished 09:30 - 17:30 Bioinformatics Training Room, Craik-Marshall Building

This comprehensive course equips you with essential skills and knowledge in bacterial genomics analysis, primarily using Illumina-sequenced samples. You'll gain an understanding of how to select the most appropriate analysis workflow, tailored to the genome diversity of a given bacterial species. Through hands-on training, you'll apply both de novo assembly and reference-based mapping approaches to obtain bacterial genomes for your isolates. You will apply standardised workflows for genome assembly and annotation, including quality assessment criteria to ensure the reliability of your results. Along with typing bacteria using methods such as MLST, you'll learn how to construct phylogenetic trees using whole genome and core genome alignments, enabling you to explore the evolutionary relationships among bacterial isolates. You’ll extend this to estimate a time-scaled phylogeny using a starting phylogenetic tree. Lastly, you'll apply methods to detect antimicrobial resistance genes. As examples we will use Mycobacterium tuberculosis, Staphylococcus aureus and Streptococcus pneumoniae, allowing you to become well-equipped to conduct bacterial genomics analyses on a range of species.


If you do not have a University of Cambridge Raven account please book or register your interest here.

Additional information
  • ♿ The training room is located on the first floor and there is currently no wheelchair or level access.
  • Our courses are only free for registered University of Cambridge students. All other participants will be charged according to our charging policy.
  • Attendance will be taken on all courses and a charge is applied for non-attendance, including for University of Cambridge students. After you have booked a place, if you are unable to attend any of the live sessions, please email the Bioinfo Team.
  • Further details regarding eligibility criteria are available here.
  • Guidance on visiting Cambridge and finding accommodation is available here.

September 2024

Mon 16
Introduction to Python (ONLINE LIVE TRAINING) (1 of 2) Finished 09:30 - 17:00 Bioinformatics Training Facility - Online LIVE Training

This course provides a practical introduction to the writing of Python programs for the complete novice. Participants are lead through the core concepts of Python including Python syntax, data structures and reading/writing files. These are illustrated by a series of example programs. Upon completion of the course, participants will be able to write simple Python programs.


If you do not have a University of Cambridge Raven account please book or register your interest here.

Additional information
  • Our courses are only free for registered University of Cambridge students. All other participants will be charged according to our charging policy.
  • Attendance will be taken on all courses and a charge is applied for non-attendance. After you have booked a place, if you are unable to attend any of the live sessions, please email the Bioinfo Team.
  • Further details regarding eligibility criteria are available here.
Introduction to R (IN-PERSON) (1 of 2) Finished 09:30 - 17:30 Bioinformatics Training Room, Craik-Marshall Building

R is one of the leading programming languages in Data Science. It is widely used to perform statistics, machine learning, visualisations and data analyses. It is an open source programming language so all the software we will use in the course is free. This course is an introduction to R designed for participants with no programming experience. We will start from scratch by introducing how to start programming in R and progress our way and learn how to read and write to files, manipulate data and visualise it by creating different plots - all the fundamental tasks you need to get you started analysing your data. During the course we will be working with one of the most popular packages in R; tidyverse that will allow you to manipulate your data effectively and visualise it to a publication level standard.


If you do not have a University of Cambridge Raven account please book or register your interest here.

Additional information
  • ♿ The training room is located on the first floor and there is currently no wheelchair or level access.
  • Our courses are only free for registered University of Cambridge students. All other participants will be charged according to our charging policy.
  • Attendance will be taken on all courses and a charge is applied for non-attendance. After you have booked a place, if you are unable to attend any of the live sessions, please email the Bioinfo Team.
  • Further details regarding eligibility criteria are available here.
  • Guidance on visiting Cambridge and finding accommodation is available here.
Tue 17
Introduction to R (IN-PERSON) (2 of 2) Finished 09:30 - 17:30 Bioinformatics Training Room, Craik-Marshall Building

R is one of the leading programming languages in Data Science. It is widely used to perform statistics, machine learning, visualisations and data analyses. It is an open source programming language so all the software we will use in the course is free. This course is an introduction to R designed for participants with no programming experience. We will start from scratch by introducing how to start programming in R and progress our way and learn how to read and write to files, manipulate data and visualise it by creating different plots - all the fundamental tasks you need to get you started analysing your data. During the course we will be working with one of the most popular packages in R; tidyverse that will allow you to manipulate your data effectively and visualise it to a publication level standard.


If you do not have a University of Cambridge Raven account please book or register your interest here.

Additional information
  • ♿ The training room is located on the first floor and there is currently no wheelchair or level access.
  • Our courses are only free for registered University of Cambridge students. All other participants will be charged according to our charging policy.
  • Attendance will be taken on all courses and a charge is applied for non-attendance. After you have booked a place, if you are unable to attend any of the live sessions, please email the Bioinfo Team.
  • Further details regarding eligibility criteria are available here.
  • Guidance on visiting Cambridge and finding accommodation is available here.
Mon 23
Introduction to the Unix command line (IN-PERSON) Finished 09:30 - 17:30 Bioinformatics Training Facility - The Pembroke Teaching Rooms

The Unix shell (command line) is a powerful and essential tool for modern researchers, in particular those working in computational disciplines such as bioinformatics and large-scale data analysis. In this course we will explore the basic structure of the Unix operating system and how we can interact with it using a basic set of commands. You will learn how to navigate the filesystem, manipulate text-based data and combine multiple commands to quickly extract information from large data files. You will also learn how to write scripts and use programmatic techniques to automate task repetition.


If you do not have a University of Cambridge Raven account please book or register your interest here.

Additional information
  • Our courses are only free for registered University of Cambridge students. All other participants will be charged according to our charging policy.
  • Attendance will be taken on all courses and a charge is applied for non-attendance. After you have booked a place, if you are unable to attend any of the live sessions, please email the Bioinfo Team.
  • Further details regarding eligibility criteria are available here.
  • Guidance on visiting Cambridge and finding accommodation is available here.
Introduction to Python (ONLINE LIVE TRAINING) (2 of 2) Finished 09:30 - 17:00 Bioinformatics Training Facility - Online LIVE Training

This course provides a practical introduction to the writing of Python programs for the complete novice. Participants are lead through the core concepts of Python including Python syntax, data structures and reading/writing files. These are illustrated by a series of example programs. Upon completion of the course, participants will be able to write simple Python programs.


If you do not have a University of Cambridge Raven account please book or register your interest here.

Additional information
  • Our courses are only free for registered University of Cambridge students. All other participants will be charged according to our charging policy.
  • Attendance will be taken on all courses and a charge is applied for non-attendance. After you have booked a place, if you are unable to attend any of the live sessions, please email the Bioinfo Team.
  • Further details regarding eligibility criteria are available here.
Tue 24
Managing bioinformatics software and pipelines (IN-PERSON) new Finished 09:30 - 17:30 Bioinformatics Training Room, Craik-Marshall Building

Setting up a computer for running bioinformatic analysis can be a challenging process. Most bioinformatic applications involve the use of many different software packages, which are often part of long data processing pipelines. In this course we will teach you how to overcome these challenges by using package managers and workflow management software.

We will have examples of software and pipelines for processing different types of data (RNA-seq, ChIP-seq, variant calling and viral genomes), making this course appealing to researchers working in a wide range of applications.

However, please note that we will not cover the details of any specific type of bioinformatic analysis. The idea of this course is to introduce the computational tools to get your work done, not to teach how those tools work. We will also not teach you how to write your own pipelines, or create your own software containers, but rather on how to use existing tools to boost your bioinformatic analysis.


If you do not have a University of Cambridge Raven account please book or register your interest here.

Additional information
  • ♿ The training room is located on the first floor and there is currently no wheelchair or level access.
  • Our courses are only free for registered University of Cambridge students. All other participants will be charged according to our charging policy.
  • Attendance will be taken on all courses and a charge is applied for non-attendance. After you have booked a place, if you are unable to attend any of the live sessions, please email the Bioinfo Team.
  • Further details regarding eligibility criteria are available here.
  • Guidance on visiting Cambridge and finding accommodation is available here.
Wed 25
Core Statistics using R (ONLINE LIVE TRAINING) (1 of 3) Finished 09:30 - 17:30 Bioinformatics Training Facility - Online LIVE Training

This award winning course is intended to provide a strong foundation in practical statistics and data analysis using the R software environment. The underlying philosophy of the course is to treat statistics as a practical skill rather than as a theoretical subject and as such the course focuses on methods for addressing real-life issues in the biological sciences.

There are three core goals for this course:

  1. Use R confidently for statistics and data analysis
  2. Be able to analyse datasets using standard statistical techniques
  3. Know which tests are and are not appropriate

R is an open source programming language so all of the software we will use in the course is free.

In this course, we explore classical statistical analysis techniques starting with simple hypothesis testing and building up to linear models and power analyses. The focus of the course is on practical implementation of these techniques and developing robust statistical analysis skills rather than on the underlying statistical theory.

After the course you should feel confident to be able to select and implement common statistical techniques using R and moreover know when, and when not, to apply these techniques.


If you do not have a University of Cambridge Raven account please book or register your interest here.

Additional information
  • Our courses are only free for registered University of Cambridge students. All other participants will be charged according to our charging policy.
  • Attendance will be taken on all courses and a charge is applied for non-attendance. After you have booked a place, if you are unable to attend any of the live sessions, please email the Bioinfo Team.
  • Further details regarding eligibility criteria are available here.
Thu 26
Core Statistics using R (ONLINE LIVE TRAINING) (2 of 3) Finished 09:30 - 17:30 Bioinformatics Training Facility - Online LIVE Training

This award winning course is intended to provide a strong foundation in practical statistics and data analysis using the R software environment. The underlying philosophy of the course is to treat statistics as a practical skill rather than as a theoretical subject and as such the course focuses on methods for addressing real-life issues in the biological sciences.

There are three core goals for this course:

  1. Use R confidently for statistics and data analysis
  2. Be able to analyse datasets using standard statistical techniques
  3. Know which tests are and are not appropriate

R is an open source programming language so all of the software we will use in the course is free.

In this course, we explore classical statistical analysis techniques starting with simple hypothesis testing and building up to linear models and power analyses. The focus of the course is on practical implementation of these techniques and developing robust statistical analysis skills rather than on the underlying statistical theory.

After the course you should feel confident to be able to select and implement common statistical techniques using R and moreover know when, and when not, to apply these techniques.


If you do not have a University of Cambridge Raven account please book or register your interest here.

Additional information
  • Our courses are only free for registered University of Cambridge students. All other participants will be charged according to our charging policy.
  • Attendance will be taken on all courses and a charge is applied for non-attendance. After you have booked a place, if you are unable to attend any of the live sessions, please email the Bioinfo Team.
  • Further details regarding eligibility criteria are available here.
Working on HPC clusters (IN-PERSON) (1 of 2) Finished 09:30 - 17:30 Bioinformatics Training Room, Craik-Marshall Building

Knowing how to use High Performance Computing (HPC) systems is crucial for fields such as bioinformatics, big data analysis, image processing, machine learning, parallel task execution, and other high-throughput applications.

In this introductory course, you will learn the fundamentals of HPC, including what it is and how to effectively utilise it. We will cover best practices for working with HPC systems, explain the roles of "login" and "compute" nodes, outline the typical filesystem organization on HPC clusters, and cover job scheduling with the widely-used SLURM scheduler.

This hands-on workshop is designed to be accessible to researchers from various backgrounds, providing numerous opportunities to practice and apply the skills you acquire.

As an optional session for those interested, we will also introduce the (free) HPC facilities available at Cambridge University (the course is not otherwise Cambridge-specific).


If you do not have a University of Cambridge Raven account please book or register your interest here.

Additional information
  • ♿ The training room is located on the first floor and there is currently no wheelchair or level access.
  • Our courses are only free for registered University of Cambridge students. All other participants will be charged according to our charging policy.
  • Attendance will be taken on all courses and a charge is applied for non-attendance. After you have booked a place, if you are unable to attend any of the live sessions, please email the Bioinfo Team.
  • Further details regarding eligibility criteria are available here.
  • Guidance on visiting Cambridge and finding accommodation is available here.
Fri 27
Core Statistics using R (ONLINE LIVE TRAINING) (3 of 3) Finished 09:30 - 17:30 Bioinformatics Training Facility - Online LIVE Training

This award winning course is intended to provide a strong foundation in practical statistics and data analysis using the R software environment. The underlying philosophy of the course is to treat statistics as a practical skill rather than as a theoretical subject and as such the course focuses on methods for addressing real-life issues in the biological sciences.

There are three core goals for this course:

  1. Use R confidently for statistics and data analysis
  2. Be able to analyse datasets using standard statistical techniques
  3. Know which tests are and are not appropriate

R is an open source programming language so all of the software we will use in the course is free.

In this course, we explore classical statistical analysis techniques starting with simple hypothesis testing and building up to linear models and power analyses. The focus of the course is on practical implementation of these techniques and developing robust statistical analysis skills rather than on the underlying statistical theory.

After the course you should feel confident to be able to select and implement common statistical techniques using R and moreover know when, and when not, to apply these techniques.


If you do not have a University of Cambridge Raven account please book or register your interest here.

Additional information
  • Our courses are only free for registered University of Cambridge students. All other participants will be charged according to our charging policy.
  • Attendance will be taken on all courses and a charge is applied for non-attendance. After you have booked a place, if you are unable to attend any of the live sessions, please email the Bioinfo Team.
  • Further details regarding eligibility criteria are available here.
Working on HPC clusters (IN-PERSON) (2 of 2) Finished 09:30 - 13:00 Bioinformatics Training Room, Craik-Marshall Building

Knowing how to use High Performance Computing (HPC) systems is crucial for fields such as bioinformatics, big data analysis, image processing, machine learning, parallel task execution, and other high-throughput applications.

In this introductory course, you will learn the fundamentals of HPC, including what it is and how to effectively utilise it. We will cover best practices for working with HPC systems, explain the roles of "login" and "compute" nodes, outline the typical filesystem organization on HPC clusters, and cover job scheduling with the widely-used SLURM scheduler.

This hands-on workshop is designed to be accessible to researchers from various backgrounds, providing numerous opportunities to practice and apply the skills you acquire.

As an optional session for those interested, we will also introduce the (free) HPC facilities available at Cambridge University (the course is not otherwise Cambridge-specific).


If you do not have a University of Cambridge Raven account please book or register your interest here.

Additional information
  • ♿ The training room is located on the first floor and there is currently no wheelchair or level access.
  • Our courses are only free for registered University of Cambridge students. All other participants will be charged according to our charging policy.
  • Attendance will be taken on all courses and a charge is applied for non-attendance. After you have booked a place, if you are unable to attend any of the live sessions, please email the Bioinfo Team.
  • Further details regarding eligibility criteria are available here.
  • Guidance on visiting Cambridge and finding accommodation is available here.

October 2024

Tue 1
Generalised linear models (IN-PERSON) Finished 09:30 - 17:00 Bioinformatics Training Room, Craik-Marshall Building

Generalised linear models are the kind of models we would use if we had to deal with non-continuous response variables. For example, this happens if you have count data or a binary outcome.

This course aims to introduce generalised linear models, using the R software environment. Similar to Core statistics using R this course addresses the practical aspects of using these models, so you can explore real-life issues in the biological sciences. The Generalised linear models using R course builds heavily on the knowledge gained in the core statistics sessions, which means that the Core statistics using R course is a firm prerequisite for joining.

There are several aims to this course:

1. Be able to distinguish between linear models and generalised linear models

2. Analyse binary outcome and count data using R

3. Critically assess model fit

R is an open-source programming language so all of the software we will use in the course is free. We will be using the R Studio interface throughout the course. Most of the code will be focussed around the tidyverse and tidymodels packages, so a basic understanding of the tidyverse syntax is essential.


If you do not have a University of Cambridge Raven account please book or register your interest here.

Additional information
  • ♿ The training room is located on the first floor and there is currently no wheelchair or level access.
  • Our courses are only free for registered University of Cambridge students. All other participants will be charged according to our charging policy.
  • Attendance will be taken on all courses and a charge is applied for non-attendance. After you have booked a place, if you are unable to attend any of the live sessions, please email the Bioinfo Team.
  • Further details regarding eligibility criteria are available here.
  • Guidance on visiting Cambridge and finding accommodation is available here.
Wed 2
Bulk RNA-seq analysis (IN-PERSON) (1 of 3) Finished 09:30 - 17:30 Bioinformatics Training Room, Craik-Marshall Building

In this course you will acquire practical skills in RNA-seq data analysis. You will learn about quality control, alignment, and quantification of gene expression against a reference transcriptome. Additionally, you will learn to conduct downstream analysis in R, exploring techniques like PCA and clustering for exploratory analysis. The course also covers differential expression analysis using the DESeq2 R/Bioconductor package. Furthermore, the course covers how to generate visualisations like heatmaps and performing gene set testing to link differential genes with established biological functions or pathways.


If you do not have a University of Cambridge Raven account please book or register your interest here.

Additional information
  • ♿ The training room is located on the first floor and there is currently no wheelchair or level access.
  • Our courses are only free for registered University of Cambridge students. All other participants will be charged according to our charging policy.
  • Attendance will be taken on all courses and a charge is applied for non-attendance. After you have booked a place, if you are unable to attend any of the live sessions, please email the Bioinfo Team.
  • Further details regarding eligibility criteria are available here.
  • Guidance on visiting Cambridge and finding accommodation is available here.
Thu 3
Bulk RNA-seq analysis (IN-PERSON) (2 of 3) Finished 09:30 - 17:30 Bioinformatics Training Room, Craik-Marshall Building

In this course you will acquire practical skills in RNA-seq data analysis. You will learn about quality control, alignment, and quantification of gene expression against a reference transcriptome. Additionally, you will learn to conduct downstream analysis in R, exploring techniques like PCA and clustering for exploratory analysis. The course also covers differential expression analysis using the DESeq2 R/Bioconductor package. Furthermore, the course covers how to generate visualisations like heatmaps and performing gene set testing to link differential genes with established biological functions or pathways.


If you do not have a University of Cambridge Raven account please book or register your interest here.

Additional information
  • ♿ The training room is located on the first floor and there is currently no wheelchair or level access.
  • Our courses are only free for registered University of Cambridge students. All other participants will be charged according to our charging policy.
  • Attendance will be taken on all courses and a charge is applied for non-attendance. After you have booked a place, if you are unable to attend any of the live sessions, please email the Bioinfo Team.
  • Further details regarding eligibility criteria are available here.
  • Guidance on visiting Cambridge and finding accommodation is available here.
Fri 4
Bulk RNA-seq analysis (IN-PERSON) (3 of 3) Finished 09:30 - 17:30 Bioinformatics Training Room, Craik-Marshall Building

In this course you will acquire practical skills in RNA-seq data analysis. You will learn about quality control, alignment, and quantification of gene expression against a reference transcriptome. Additionally, you will learn to conduct downstream analysis in R, exploring techniques like PCA and clustering for exploratory analysis. The course also covers differential expression analysis using the DESeq2 R/Bioconductor package. Furthermore, the course covers how to generate visualisations like heatmaps and performing gene set testing to link differential genes with established biological functions or pathways.


If you do not have a University of Cambridge Raven account please book or register your interest here.

Additional information
  • ♿ The training room is located on the first floor and there is currently no wheelchair or level access.
  • Our courses are only free for registered University of Cambridge students. All other participants will be charged according to our charging policy.
  • Attendance will be taken on all courses and a charge is applied for non-attendance. After you have booked a place, if you are unable to attend any of the live sessions, please email the Bioinfo Team.
  • Further details regarding eligibility criteria are available here.
  • Guidance on visiting Cambridge and finding accommodation is available here.
Mon 7
Software Reproducibility using Containers (IN-PERSON) new Finished 09:30 - 17:30 Bioinformatics Training Room, Craik-Marshall Building

Congratulations! You have just created a new programme/script that is likely to be of use to other researchers. Naturally, you want to publish this software, others to use it and you to be cited. How hard can that step be? (SPOILER Alert – it’s harder than you think).

  • This course explores the myriad challenges in producing code that works on other researchers’ computers and not just yours.
  • We tour various possible software solutions and evaluate their suitability
  • We examine the potential solution that is Software Containers (focusing on Docker).


If you do not have a University of Cambridge Raven account please book or register your interest here.

Additional information
  • ♿ The training room is located on the first floor and there is currently no wheelchair or level access.
  • Our courses are only free for registered University of Cambridge students. All other participants will be charged according to our charging policy.
  • Attendance will be taken on all courses and a charge is applied for non-attendance, including for University of Cambridge students. After you have booked a place, if you are unable to attend any of the live sessions, please email the Bioinfo Team.
  • Further details regarding eligibility criteria are available here.
  • Guidance on visiting Cambridge and finding accommodation is available here.
Fri 11
Linear mixed effects models (IN-PERSON) (1 of 2) Finished 09:30 - 17:00 Bioinformatics Training Room, Craik-Marshall Building

This course gives an introduction to linear mixed effects models, also called multi-level models or hierarchical models, for the purposes of using them in your own research or studies.

We emphasise the practical skills and key concepts needed to work with these models, using applied examples and real datasets.

After completing the course, you should have:

  • A conceptual understanding of what mixed effects models are, and when they should be used
  • Familiarity with fitting and interpreting mixed effects models using the lme4 package in R

Please note that this course builds on knowledge of linear modelling, therefore should not be considered a general introduction to statistical modelling.


If you do not have a University of Cambridge Raven account please book or register your interest here.

Additional information
  • ♿ The training room is located on the first floor and there is currently no wheelchair or level access.
  • Our courses are only free for registered University of Cambridge students. All other participants will be charged according to our charging policy.
  • Attendance will be taken on all courses and a charge is applied for non-attendance. After you have booked a place, if you are unable to attend any of the live sessions, please email the Bioinfo Team.
  • Further details regarding eligibility criteria are available here.
  • Guidance on visiting Cambridge and finding accommodation is available here.