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Bioinformatics Training

Bioinformatics course timetable

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Wed 12 Jun – Wed 17 Jul

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June 2024

Fri 14
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 might take place at the Craik-Marshall training room. This is located on the first floor and there is currently no wheelchair or level access. Please put level access requirements in the "Special requirements" section, so we can take that into consideration when allocating the room.
  • 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 17
Introduction to working with UNIX and bash (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, 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
  • ♿ 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 18
Introduction to Metabolomics (IN-PERSON) (1 of 2) Finished 09:30 - 17:30 Bioinformatics Training Room, Craik-Marshall Building

The goal of metabolomics is to identify and quantify the complete biochemical composition of a biological sample. With the increase in genomic, transcriptomic and proteomic information there is a growing need to understand the metabolic phenotype that these genes and proteins ultimately control.

The aim of this course is to provide an introductory overview of metabolomics and its applications in life sciences and environmental settings. We will introduce different techniques used to extract metabolites and analyse samples to collect metabolomic data (such as HPLC or GC-based MS and NMR), present how to analyse such data, how to identify metabolites using online databases and how to map the metabolomic data to metabolic 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, 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 19
Introduction to Metabolomics (IN-PERSON) (2 of 2) Finished 09:30 - 17:30 Bioinformatics Training Room, Craik-Marshall Building

The goal of metabolomics is to identify and quantify the complete biochemical composition of a biological sample. With the increase in genomic, transcriptomic and proteomic information there is a growing need to understand the metabolic phenotype that these genes and proteins ultimately control.

The aim of this course is to provide an introductory overview of metabolomics and its applications in life sciences and environmental settings. We will introduce different techniques used to extract metabolites and analyse samples to collect metabolomic data (such as HPLC or GC-based MS and NMR), present how to analyse such data, how to identify metabolites using online databases and how to map the metabolomic data to metabolic 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, 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 20
Quality Control in Sequencing Experiments (ONLINE LIVE TRAINING) new Finished 09:30 - 13:00 Bioinformatics Training Facility - Online LIVE Training

This course covers the potential pitfalls of short-read sequencing studies and provides options for visualisation and quality control (QC) for early detection and diagnosis of issues. You will gain an understanding of Illumina sequencing and different QC metrics that can be extracted from sequencing reads, such as base quality scores. The course also covers how QC metrics vary across different library types and thus distinguish between expected and unexpected QC results. You will be introduced to key software tools including FastQC, FastQ Screen, and MultiQC to carry out quality assessment of your sequencing data.


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.
Fri 21
Analysis of bulk RNA-seq data (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, 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 24
Analysis of bulk RNA-seq data (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, 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 25
Analysis of bulk RNA-seq data (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, 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 26
Analysis of expression Proteomics data in R (IN-PERSON) (1 of 2) Finished 09:30 - 17:30 Bioinformatics Training Room, Craik-Marshall Building

This workshop focuses on expression proteomics, which aims to characterise the protein diversity and abundance in a particular system. You will learn about the bioinformatic analysis steps involved when working with these kind of data, in particular several dedicated proteomics Bioconductor packages, part of the R programming language. We will use real-world datasets obtained from label free quantitation (LFQ) as well as tandem mass tag (TMT) mass spectrometry. We cover the basic data structures used to store and manipulate protein abundance data, how to do quality control and filtering of the data, as well as several visualisations. Finally, we include statistical analysis of differential abundance across sample groups (e.g. control vs. treated) and further evaluation and biological interpretation of the results via gene ontology analysis. By the end of this workshop you should have the skills to make sense of expression proteomics data, from start to finish.


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 27
Analysis of expression Proteomics data in R (IN-PERSON) (2 of 2) Finished 09:30 - 17:30 Bioinformatics Training Room, Craik-Marshall Building

This workshop focuses on expression proteomics, which aims to characterise the protein diversity and abundance in a particular system. You will learn about the bioinformatic analysis steps involved when working with these kind of data, in particular several dedicated proteomics Bioconductor packages, part of the R programming language. We will use real-world datasets obtained from label free quantitation (LFQ) as well as tandem mass tag (TMT) mass spectrometry. We cover the basic data structures used to store and manipulate protein abundance data, how to do quality control and filtering of the data, as well as several visualisations. Finally, we include statistical analysis of differential abundance across sample groups (e.g. control vs. treated) and further evaluation and biological interpretation of the results via gene ontology analysis. By the end of this workshop you should have the skills to make sense of expression proteomics data, from start to finish.


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.

July 2024

Mon 1
Intermediate Supervised Machine Learning (ONLINE LIVE TRAINING) (1 of 2) Finished 09:30 - 17:00 Bioinformatics Training Facility - Online LIVE Training

The vast majority of data produced fits the criteria of labelled data (with either continuous of categorical labels); the machine learning task of discriminating classes (for categorical outputs) or predicting future values (continuous outputs) will be discussed in detail, focusing both on classical methods – k nearest neighbours, decision tree based methods and support vector machine – and on the importance and discriminative power of features.

The module will provide support in generating models (using R as programming environment), critically assessing the optimisation of hyperparameters and evaluating the usefulness of the model with respect to the initial question. The examples presented throughout stem from biological examples, yet the skills and critical assessment of outputs are transferrable.


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.
Tue 2
Introduction to R for Biologists (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, 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.
Intermediate Supervised Machine Learning (ONLINE LIVE TRAINING) (2 of 2) Finished 09:30 - 17:00 Bioinformatics Training Facility - Online LIVE Training

The vast majority of data produced fits the criteria of labelled data (with either continuous of categorical labels); the machine learning task of discriminating classes (for categorical outputs) or predicting future values (continuous outputs) will be discussed in detail, focusing both on classical methods – k nearest neighbours, decision tree based methods and support vector machine – and on the importance and discriminative power of features.

The module will provide support in generating models (using R as programming environment), critically assessing the optimisation of hyperparameters and evaluating the usefulness of the model with respect to the initial question. The examples presented throughout stem from biological examples, yet the skills and critical assessment of outputs are transferrable.


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.
Wed 3
Introduction to R for Biologists (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, 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 4
Introduction to Python for Biologists (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, 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.
Fri 5
Introduction to Python for Biologists (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, 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.
Analysis of ChIP-seq Data with SeqMonk (IN-PERSON) new Finished 09:30 - 17:00 Bioinformatics Training Room, Craik-Marshall Building

Chromatin immunoprecipitation followed by sequencing (ChIP-seq) is a method used to identify binding sites for transcription factors, histone modifications and other DNA-binding proteins across the genome. In this course, we will cover the fundamentals of ChIP-seq data analysis, from raw data to downstream applications.

We will start with an introduction to ChIP-seq methods and cover the bioinformatic steps in processing ChIP-seq data. We will then introduce the use of the graphical program SeqMonk to explore and visualise your data. Finally, you will perform peak calling and perform differential enrichment 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, 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 8
High Performance Computing: An Introduction (IN-PERSON) (1 of 2) Finished 09:30 - 17:30 Bioinformatics Training Room, Craik-Marshall Building

Have you heard about High Performance Computing, but are not sure what it is or whether it is relevant for your work? Would you like to use a HPC, but are not sure where to start? Are you using your personal computer to run computationally demanding tasks, which take long and slow down your work? Do you need to use software that runs on Linux, but don't have access to a Linux computer? If any of these questions apply to you, then this course might be for you!

Knowing how to work on a High Performance Computing system is an essential skill for applications such as bioinformatics, big-data analysis, image processing, machine learning, parallelising tasks, and other high-throughput applications.

In this course we will cover the basics of High Performance Computing, what it is and how you can use it in practice. This is a hands-on workshop, which should be accessible to researchers from a range of backgrounds and offering several opportunities to practice the skills we learn along the way.

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, 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 9
High Performance Computing: An Introduction (IN-PERSON) (2 of 2) Finished 09:30 - 13:00 Bioinformatics Training Room, Craik-Marshall Building

Have you heard about High Performance Computing, but are not sure what it is or whether it is relevant for your work? Would you like to use a HPC, but are not sure where to start? Are you using your personal computer to run computationally demanding tasks, which take long and slow down your work? Do you need to use software that runs on Linux, but don't have access to a Linux computer? If any of these questions apply to you, then this course might be for you!

Knowing how to work on a High Performance Computing system is an essential skill for applications such as bioinformatics, big-data analysis, image processing, machine learning, parallelising tasks, and other high-throughput applications.

In this course we will cover the basics of High Performance Computing, what it is and how you can use it in practice. This is a hands-on workshop, which should be accessible to researchers from a range of backgrounds and offering several opportunities to practice the skills we learn along the way.

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, 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 10
Core Statistics using R (IN-PERSON) (1 of 3) Finished 09:30 - 17:00 Bioinformatics Training Room, Craik-Marshall Building

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
  • ♿ 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 11
Core Statistics using R (IN-PERSON) (2 of 3) Finished 09:30 - 17:00 Bioinformatics Training Room, Craik-Marshall Building

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
  • ♿ 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 12
Core Statistics using R (IN-PERSON) (3 of 3) Finished 09:30 - 17:00 Bioinformatics Training Room, Craik-Marshall Building

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
  • ♿ 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.
Mon 15
Linear mixed effects models (IN-PERSON) (1 of 2) [Places] 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) [Places] 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.
Wed 17
Software Reproducibility using Containers (IN-PERSON) new [Places] 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.