All Bioinformatics courses

This course will cover all aspects of the analysis of DNA methylation using sequencing, including primary analysis, mapping and quality control of BS-Seq data, common pitfalls and complications.

It will also include exploratory analysis of methylation, looking at different methods of quantitation, and a variety of ways of looking more widely at the distribution of methylation over the genome. Finally the course will look at statistical methods to predict differential methylation.

The course comprises of a mixture of theoretical lectures and practicals covering a range of different software packages.

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, 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.

PLEASE NOTE that until further notice, due to the evolving situation with Coronavirus no courses will be offered as classroom based at the Training Facility. The Bioinformatics Team will be teaching the course live online in conjunction with the presenters.

SeqMonk is a graphical program for the visualisation and analysis of large mapped sequencing datasets such as ChIP-Seq, RNA-Seq, and BS-Seq.

The program allows you to view your reads against an annotated genome and to quantitate and filter your data to let you identify regions of interest. It is a friendly way to explore and analysis very large datasets.

This course provides an introduction to the main features of SeqMonk and will run through the analysis of a couple of different datasets to show what sort of analysis options it provides.

Further information is available here.

Please note that if you are not eligible for a University of Cambridge Raven account you will need to book or register your interest by linking here.

Analysis of whole genome data unearths a multitude of variants of different classes, which need to be filtered, annotated and validated to arrive at a causative variant for a disease. The current short length sequences, whilst being excellent at identifying single nucleotide variants and short insertions/deletions, struggle to correctly map structural variants (SVs). Long-read sequencing technologies offer improvements in the characterisation of genetic variation and regions that are difficult to assess with short-read sequences.

The aim of this course is to familiarise participants with long read sequencing technologies, their applications and the bioinformatics tools used to assemble this kind of data. Lectures will introduce this technology and provide insight into methods for the analysis of genomic data, while the hands-on sessions will allow participants to run analysis pipelines, focusing on data generated by the Oxford Nanopore Technologies (ONT) platform.

The training room is located on the first floor and there is currently no wheelchair or level access available to this level.

Please note that if you are not eligible for a University of Cambridge Raven account you will need to book or register your interest by linking here.

PLEASE NOTE The Bioinformatics Team are presently teaching as many courses live online, with tutors available to help you work through the course material on a personal copy of the course environment. We aim to simulate the classroom experience as closely as possible, with opportunities for one-to-one discussion with tutors and a focus on interactivity throughout.

This course aims to give you an introduction to the basics of Matlab. During the two day course we will use a practical based approach to give you the confidence to start using Matlab in your own work. In particular we will show you how to write your own scripts and functions and how to use pre-written functions. We will also explore the many ways in which help is available to Matlab users. In addition we will cover basic computer programming in Matlab to enable you to write more efficient scripts.

Please note that if you are not eligible for a University of Cambridge Raven account you will need to Book or register Interest by linking here.

This course is aimed at those new to programming and provides an introduction to programming using Perl.

During this course you will learn the basics of the Perl programming language, including how to store data in Perl’s standard data structures such as arrays and hashes, and how to process data using loops, functions, and many of Perl’s built in operators. You will learn how to write and run your own Perl scripts and how to pass options and files to them. The course also covers sorting, regular expressions, references and multi-dimensional data structures.

The course will be taught using the online Learning Perl materials created by Sofia Robb of the University of California Riverside.

The course website providing links to the course materials is here.

Please note that if you are not eligible for a University of Cambridge Raven account you will need to book by linking here.

The workshop will cover the basics of de novo genome assembly using a small genome example. This includes project planning steps, selecting fragment sizes, initial assembly of reads into fully covered contigs, and then assembling those contigs into larger scaffolds that may include gaps. The end result will be a set of contigs and scaffolds with sufficient average length to perform further analysis on, including genome annotation (link to that nomination). This workshop will use tools and methods targeted at small genomes. The basics of assembly and scaffolding presented here will be useful for building larger genomes, but the specific tools and much of the project planning will be different.

This workshop will also introduce genome annotation in the context of small genomes. We’ll begin with genome annotation concepts, and then introduce resources and tools for automatically annotating small genomes. The workshop will finish with a review of options for further automatic and manual tuning of the annotation, and for maintaining it as new assemblies or information becomes available.

This session will include an introduction to the Galaxy platform.

This event is co-organized with EMBL-ABR and the Genomics Virtual Lab. Course materials can be found here.

Please note that if you are not eligible for a University of Cambridge Raven account you will need to book by linking here.

This three day course is intended to open doors to applying statistics - whether directly increasing skills and personally undertaking analyses, or by expanding knowledge towards identifying collaborators. The end goal is to drive confident engagement with data analysis and further training - increasing the quality and reliability of interpretation, and putting that interpretation and subsequent presentation into the hands of the researcher. Each day of the course will deliver a mixture of lectures, workshops and hands-on practicals – and will focus on the following specific elements.

Day 1 focuses on basic approaches and the computer skills required to do downstream analysis. Covering: Basic skills for data manipulation in R. How to prepare your data effectively. Principles of experimental design and how this influences analysis.

On day 2, participants will explore the core concepts of statistics – so that they can begin to see how they can be applied to their own work, and to also help with better critical evaluation of the work of others. Covering: Basic statistics concepts and practice: power, variability, false discovery, t-test, effect size, simulations to understand what a p-value means.

On day 3 we will continue to explore core concepts of statistics, focusing on linear regression and multiple testing correction.

Course materials are available here.

This event is supported by the BBSRC Strategic Training Awards for Research Skills (STARS) grant (BB/P022766/1).

Please note that if you are not eligible for a University of Cambridge Raven account you will need to book by linking here.

PLEASE NOTE The Bioinformatics Team are presently teaching as many courses live online. We aim to simulate the classroom experience as closely as possible, with opportunities for one-to-one discussion with tutors and a focus on interactivity throughout.

InterMine is a freely available open-source data warehouse built specifically for the integration and analysis of complex biological data.

InterMine-based data analysis platforms are available for many organisms including mouse, rat, budding yeast, plants (over 87 plant genomes), nematodes, fly, zebrafishHymenoptera, Planaria, and more recently human.

Genomic and proteomic data within InterMine databases includes pathways, gene expression, interactions, sequence variants, GWAS, regulatory data and protein expression. InterMine provides sophisticated query and visualisation tools both through a web interface and a powerful web service API, with multiple language bindings including Python and R.

This course will focus on the InterMine web interface and will introduce participants to all aspects of the user interface, starting with some simple exercises and building up to more complex analysis encompassing several analysis tools and comparative analysis across organisms. The exercises will mainly use the fly, human and mouse databases, but the course is applicable to anyone working with data for which an InterMine database is available (a comprehensive list of InterMine databases is available here.)

This event is organised alongside a half day course on Biological data analysis using the InterMine API. More information on this event is available here.

Please note that if you are not eligible for a University of Cambridge Raven account you will need to Book or register Interest by linking here.

PLEASE NOTE The Bioinformatics Team are presently teaching many courses live online, with tutors available to help you work through the course material on a personal copy of the course environment. We continue to monitor advice from the UK government and the University of Cambridge on resuming in-person teaching back in the training room.

Complex natural systems permeate many aspects of everyday life—including human intelligence, social media, biomedicine, agriculture, economics, even our personal and professional relationships. The past decade has seen intensification of research into structural and dynamical properties of complex networks. This course will introduce the basic principles of network theory, and hands-on DIY Network analysis using Cytoscape, one of the most widely used global platforms for construction and analysis of biomolecular networks such as gene regulatory interactions, protein complexes, hydrogen-bonding meshwork in active sites and neuronal networks. The aim is to conceptualize your own textual, tabular or genomic datasets as networks, and to understand how simple topological features can help to decipher complex properties of systems and processes.

Please note that if you are not eligible for a University of Cambridge Raven account you will need to book or register your interest by linking here.

PLEASE NOTE that this course will be taught live online, with demonstrators available to help you throughout if have any questions. All lecture components will be recorded and uploaded to the course Moodle page so that you will be able to access that information even if technical or time zone restrictions means that you aren't able to join us for the live sessions.

This virtually delivered course is intended to provide a strong foundation in practical statistics and data analysis using the R or Python software environments. 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 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

Both R and Python are free software environments that are suitable for statistical and data analysis.

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.

In many domains of research the rapid generation of large amounts of data is fundamentally changing how research is done. The deluge of data presents great opportunities, but also many challenges in managing, analyzing and sharing data.

Data Carpentry workshops are designed to teach basic concepts, skills and tools for working more effectively with data, using a combination of tools with a main focus in R. The workshop is aimed at researchers in the life sciences at all career stages and is designed for learners with little to no prior knowledge of programming, shell scripting, or command line tools.

Please note that if you are not eligible for a University of Cambridge Raven account you will need to book by linking here.

The Ensembl Project provides a comprehensive and integrated source of annotation of, mainly vertebrate, genome sequences. This one-day 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.

There may be some tools and topics that do not apply to non-vertebrates; if you have any questions about this, please email the Ensembl Outreach Project Leader, Emily Perry.

This event is part of a series of training courses organized in collaboration with Dr. Mark Dunning at CRUK Cambridge Institute.

Please note that if you are not eligible for a University of Cambridge Raven account you will need to Book or register Interest by linking here.

This interactive workshop offers participants hands-on experience in the use of the Ensembl VEP to annotate genetic variants with the effects they have on Ensembl genes, and the known information about co-located variants. We will also look at known genes and variants, including the types of data available and where they come from.

Also note: This event is part of a series of short introductions focusing on EMBL-EBI resources. If you want to learn more about these separate training events, see the Related Courses section below.

Please note that if you are not eligible for a University of Cambridge Raven account you will need to book by linking here.

This workshop is an introduction to EMBL-EBI and the life science data resources it provides. Participants will be shown how to navigate the website and search for appropriate database resources and tools, whilst also highlighting resources such as Train online (our e-learning portal) and the literature resources at Europe PMC.

This workshop will not focus on a set of specific resources; for more focused workshops please see the others within this series (see the Related Courses section below)

Please note that if you are not eligible for a University of Cambridge Raven account you will need to book by linking here.

Employ InterPro to help you answer your research questions!

This workshop will help you find out why there is a need to automatically annotate proteins, how protein family databases can help meet this challenge, and how InterPro pulls together a number of such databases, allowing you to classify unknown protein sequences and identify their function. The module is a combination of presentations and hands-on practical exercises. You will explore the various features of an InterPro entry, and design a workflow to utilise InterPro in the analysis of real world data.

Also note: This event is part of a series of short introductions focusing on EMBL-EBI resources. If you want to learn more about these separate training events, see the Related Courses section below.

The training room is located on the first floor and there is currently no wheelchair or level access available to this level.

Please note that if you are not eligible for a University of Cambridge Raven account you will need to book or register your interest by linking here.

The European Nucleotide Sequence Archive (ENA) is a global database for storing experimental nucleotide data and also interpreted data (alignment files, variant calling, analysis results). ENA is the database where all raw and consensus viral sequence data should be deposited, including SARS-Cov-2 data. The data is submitted by scientists conducting sequencing experiments and publishing research in the area. Data is fully searchable and available for download. Sequence data includes raw NGS files (FastQ, BAM…), assembled genomes and transcriptomes, and annotated sequences (protein coding genes, non coding RNA, barcode genes, HLA genes).

This training is aimed at a wide range of users that need to retrieve data from ENA, either occasionally or on a regular basis, or those users who will have retrieval needs closer to the course time.

Please note that if you are not eligible for a University of Cambridge Raven account you will need to book by linking here.

This course will give an introduction to the basic concepts of ontologies and how they are useful in biological applications. We will explain what a biomedical ontology is and present the two primary types of ontology: (i) domain ontology and (ii) application ontology, using examples as Gene Ontology (GO) and Experimental Factor Ontology (EFO). The module will also go into details of why big data need ontologies and the ontology capabilities in advanced computational biology.

Also note: This event is part of a series of short introductions focusing on EMBL-EBI resources. If you want to learn more about these separate training events, see the Related Courses section below.

The training room is located on the first floor and there is currently no wheelchair or level access available to this level.

Please note that if you are not eligible for a University of Cambridge Raven account you will need to book or register your interest by linking here.

This workshop aims to give the scientific community hands on experience on how to access and effectively use protein data in UniProt. UniProt is a high-quality, comprehensively and thoroughly annotated protein resource. Participants will be able to access detailed information on protein function and millions of protein sequences in the UniProt knowledgebase, including isoforms and disease variants.

Also note: This event is part of a series of short introductions focusing on EMBL-EBI resources. If you want to learn more about these separate training events, see the Related Courses section below.

The training room is located on the first floor and there is currently no wheelchair or level access available to this level.

Please note that if you are not eligible for a University of Cambridge Raven account you will need to book or register your interest by linking here.

PLEASE NOTE The Bioinformatics Team are presently teaching as many courses live online. We aim to simulate the classroom experience as closely as possible, with opportunities for one-to-one discussion with tutors and a focus on interactivity throughout.

This workshop is designed for researchers interested in learning about functional genomics data, how to access, retrieve and use the data from ArrayExpress and hands-on experience in using Expression Atlas, a resource to find information about gene and protein expression across species and biological conditions such as different tissues, cell types, developmental stages and diseases among others. This will include an overview on how gene expression data is curated and analysed in Expression Atlas and a practical activity to demonstrate how to access and visualise gene expression analysis results. These activities should help you answer questions such as "where is my favourite gene expressed?" or "how does its expression change in a disease?".

This workshop is not going to be a session on how to run your own bioinformatics analysis but to use the tools that have been developed in order to be able to take advantage of others’ work and prepare your work to be reproducible.

Please note that if you are not eligible for a University of Cambridge Raven account you will need to book or register your interest by linking here.

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

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

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

• 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.

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.

• ♿ 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.

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.

• 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.

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.

• ♿ 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.

This course offers an introduction to working with Linux. We will describe the Linux environment so that participants can start to utilize command-line tools and feel comfortable using a text-based way of interacting with a computer. We will take a problem-solving approach, drawing on types of tasks commonly encountered by Linux users when processing text files.

The training room is located on the first floor and there is currently no wheelchair or level access available to this level.

Please note that if you are not eligible for a University of Cambridge Raven account you will need to book or register your interest by linking 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, 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.

• ♿ 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.