Bioinformatics course timetable

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.

• 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.

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.

• 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.

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.

• 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.

This award winning course is intended to provide a strong foundation in practical statistics and data analysis using the R or Python 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 life sciences.

There are three core goals for this course:

1. Use R or Python 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 and Python are open source programming languages 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 or Python 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.

• 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.

This award winning course is intended to provide a strong foundation in practical statistics and data analysis using the R or Python 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 life sciences.

There are three core goals for this course:

1. Use R or Python 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 and Python are open source programming languages 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 or Python 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.

• 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.

This award winning course is intended to provide a strong foundation in practical statistics and data analysis using the R or Python 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 life sciences.

There are three core goals for this course:

1. Use R or Python 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 and Python are open source programming languages 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 or Python 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.

• 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.

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.

• 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.

The Ensembl Project provides an interface and an infrastructure for accessing genomic information, including genes, variants, comparative genomics and gene regulation data, covering over 300 vertebrate species. This workshop offers a comprehensive practical introduction to the use of the Ensembl Genome Browser as well as essential background information.

This course will focus on the vertebrate genomes in Ensembl, however much of what will be covered is also applicable to the non-vertebrates (plants, bacteria, fungi, metazoa and protists) in Ensembl Genomes.

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

• 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.

The Ensembl project provides an interface and an infrastructure for accessing genomic information, including genes, variants, comparative genomics and gene regulation data, covering over 300 vertebrate species.

This workshop is aimed at researchers and developers interested in exploring Ensembl beyond the website. The workshop covers how to use the Ensembl REST APIs, including understanding the major endpoints and how to write scripts to call them.

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

• 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.

This course introduces the basic theory and concepts of network analysis. Attendees will learn how to construct protein-protein interaction networks and subsequently use these to overlay large-scale data such as that obtained through RNA-Seq or mass-spec proteomics. The course will focus on giving attendees hands-on experience in the use of one of the most used open-source Network Visualisation Platforms, Cytoscape. The course will also access and analyse the data through Cytoscape apps, including IntAct app.

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

• 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.

This course introduces the basic theory and concepts of network analysis. Attendees will learn how to construct protein-protein interaction networks and subsequently use these to overlay large-scale data such as that obtained through RNA-Seq or mass-spec proteomics. The course will focus on giving attendees hands-on experience in the use of one of the most used open-source Network Visualisation Platforms, Cytoscape. The course will also access and analyse the data through Cytoscape apps, including IntAct app.

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

• 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.

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.

• 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.

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.

• 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.

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.

• 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.

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.

• 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.

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.

• 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.

As the use of AI chatbots continues to rise, it is crucial to understand what they are, how they work, and how to make the most of them. Prompting is the method of interacting with AI, and as AI chatbots become more openly and widely available, a good and effective prompt could make all the difference.

In this course, we will provide background on the history of AI chatbots as well as an understanding of how they work. We will provide hands-on use cases of how to prompt like a bioinformatician/software engineer as well as providing strategies and tactics of prompting to unleash the full potential of AI chatbots in biological data analysis. This course is aimed at researchers with no computational background.

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

• ♿ 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.

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.

• 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.

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.

• 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.