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Bioinformatics course timetable

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Thu 3 Oct – Mon 2 Dec

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October 2024

Fri 4
Bulk RNA-seq analysis (IN-PERSON) (3 of 3) In progress 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 [Full] 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) [Full] 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 16
Introduction to the Unix command line (ONLINE LIVE TRAINING) (1 of 2) [Places] 09:30 - 13:00 Bioinformatics Training Facility - Online LIVE Training

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.
Thu 17
Introduction to the Unix command line (ONLINE LIVE TRAINING) (2 of 2) [Places] 09:30 - 13:00 Bioinformatics Training Facility - Online LIVE Training

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.
Fri 18
Linear mixed effects models (IN-PERSON) (2 of 2) [Full] 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.
Mon 21
Working on HPC clusters (ONLINE LIVE TRAINING) (1 of 3) [Full] 09:30 - 13:00 Bioinformatics Training Facility - Online LIVE Training

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
  • 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 22
Working on HPC clusters (ONLINE LIVE TRAINING) (2 of 3) [Full] 09:30 - 13:00 Bioinformatics Training Facility - Online LIVE Training

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
  • 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.
Wed 23
Working on HPC clusters (ONLINE LIVE TRAINING) (3 of 3) [Full] 09:30 - 13:00 Bioinformatics Training Facility - Online LIVE Training

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
  • 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 24
Foundations of phylogenetic inference (ONLINE LIVE TRAINING) [Places] 09:30 - 17:30 Bioinformatics Training Facility - Online LIVE Training

This course will teach you how to use molecular data to construct and interpret phylogenies. We will start by introducing basic concepts in phylogenetic analysis, what trees represent and how to interpret them. We will then cover how to produce a multiple sequence alignment from DNA and protein sequences, and the pros and cons of different alignment algorithms. You will then learn about different methods of phylogenetic inference, with a particular focus on maximum likelihood and how to assess confidence in your tree using bootstrap resampling. Finally, we will introduce how Bayesian methods can help to estimate the uncertainty in the inferred tree parameters as well as incorporate information for more advanced/bespoke phylogenetic analysis.


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.
Mon 28
Quality control in sequencing experiments (ONLINE LIVE TRAINING) [Full] 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.

Note that the main focus of this course is on how to interpret quality reports produced by these tools, not on how to run them (although we do provide the basic commands you need to do it).


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.
Wed 30
Extracting biological information from gene lists (ONLINE LIVE TRAINING) [Full] 09:30 - 17:30 Bioinformatics Training Facility - Online LIVE Training

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.

Course materials are available here.


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.

November 2024

Fri 1
Metagenomics data analysis (ONLINE LIVE TRAINING) (1 of 3) [Places] 09:30 - 17:30 Bioinformatics Training Facility - Online LIVE Training

This workshop will focus on the theory and applications of metagenomics for the analysis of complex microbiomes (microbial communities). We will cover a range of methods from the fastest, simplest and cheapest amplicon-based methods up to Hi-C metagenomics techniques that give highly detailed results on complex microbial communities. In addition to the theory, we will introduce several bioinformatic software packages suited for the analysis of metagenomic data, quality control and downstream analysis and interpretation of the results.


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.
Mon 4
Core Statistics using R (IN-PERSON) (1 of 6) [Places] 09:30 - 13:00 Bioinformatics Training Facility - The Pembroke Teaching Rooms

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.
  • Guidance on visiting Cambridge and finding accommodation is available here.
Wed 6
Core Statistics using R (IN-PERSON) (2 of 6) [Places] 09:30 - 13:00 Bioinformatics Training Facility - The Pembroke Teaching Rooms

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.
  • Guidance on visiting Cambridge and finding accommodation is available here.
Fri 8
Metagenomics data analysis (ONLINE LIVE TRAINING) (2 of 3) [Places] 09:30 - 17:30 Bioinformatics Training Facility - Online LIVE Training

This workshop will focus on the theory and applications of metagenomics for the analysis of complex microbiomes (microbial communities). We will cover a range of methods from the fastest, simplest and cheapest amplicon-based methods up to Hi-C metagenomics techniques that give highly detailed results on complex microbial communities. In addition to the theory, we will introduce several bioinformatic software packages suited for the analysis of metagenomic data, quality control and downstream analysis and interpretation of the results.


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.
Mon 11
Core Statistics using R (IN-PERSON) (3 of 6) [Places] 09:30 - 13:00 Bioinformatics Training Facility - The Pembroke Teaching Rooms

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.
  • Guidance on visiting Cambridge and finding accommodation is available here.
Wed 13
Core Statistics using R (IN-PERSON) (4 of 6) [Places] 09:30 - 13:00 Bioinformatics Training Facility - The Pembroke Teaching Rooms

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.
  • Guidance on visiting Cambridge and finding accommodation is available here.
Fri 15
Metagenomics data analysis (ONLINE LIVE TRAINING) (3 of 3) [Places] 09:30 - 17:30 Bioinformatics Training Facility - Online LIVE Training

This workshop will focus on the theory and applications of metagenomics for the analysis of complex microbiomes (microbial communities). We will cover a range of methods from the fastest, simplest and cheapest amplicon-based methods up to Hi-C metagenomics techniques that give highly detailed results on complex microbial communities. In addition to the theory, we will introduce several bioinformatic software packages suited for the analysis of metagenomic data, quality control and downstream analysis and interpretation of the results.


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.
Mon 18
Core Statistics using R (IN-PERSON) (5 of 6) [Places] 09:30 - 13:00 Bioinformatics Training Facility - The Pembroke Teaching Rooms

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.
  • Guidance on visiting Cambridge and finding accommodation is available here.
Wed 20
Core Statistics using R (IN-PERSON) (6 of 6) [Places] 09:30 - 13:00 Bioinformatics Training Facility - The Pembroke Teaching Rooms

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.
  • Guidance on visiting Cambridge and finding accommodation is available here.
Thu 21
Introduction to R for Biologists (ONLINE LIVE TRAINING) (1 of 2) [Places] 09:30 - 17:30 Bioinformatics Training Facility - Online LIVE Training

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
  • 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.
Fri 22
Introduction to R for Biologists (ONLINE LIVE TRAINING) (2 of 2) [Places] 09:30 - 17:30 Bioinformatics Training Facility - Online LIVE Training

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
  • 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.
Fri 29
Reproducible Research with R (IN-PERSON) [Places] 09:30 - 17:00 Bioinformatics Training Room, Craik-Marshall Building

This course introduces concepts about reproducibility that can be used when you are programming in R. We will explore how to create notebooks - a way to integrate your R analyses into reports using Rmarkdown. The course also introduces the concept of version control. We will learn how to create a repository on GitHub and how to work together on the same project collaboratively without creating conflicting versions of files.


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.

December 2024

Mon 2
Single-cell RNA-seq analysis (ONLINE LIVE TRAINING) (1 of 3) [Full] 09:30 - 17:30 Bioinformatics Training Facility - Online LIVE Training

Recent technological advances have made it possible to obtain genome-wide transcriptome data from single cells using high-throughput sequencing. This course offers an introduction to single-cell RNA sequencing (scRNA-seq) analysis. Participants will gain hands-on experience with key software packages and methodologies for processing, analyzing, and interpreting scRNA-seq data. Key topics include data preprocessing, quality control, normalization, dimensionality reduction, batch correction and data integration, cell clustering and differential expression and abundance analysis. By the end of the course, students will be equipped with the skills to independently conduct and critically analyse data from scRNA-seq experiments.


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.