All Bioinformatics courses

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 sets.

InterMine-based data analysis platforms are available for many organisms including mouse, rat, budding yeast, plants (over 87 plant genomes), nematodes, fly, zebrafish, Hymenoptera, 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 programmatic access to InterMine through the API and InterMine searches will be done using Python and R scripts. 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 User Interface. More information on this event are 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 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.

The Open Microscopy Environment (OME) is an open-source software project that develops tools that enable access, analysis, visualization, sharing and publication of biological image data.

OME has three components:

• OME-TIFF, standardised file format and data model;
• Bio-Formats, a software library for reading proprietary image file formats; and
• OMERO, a software platform for image data management and analysis.

In this one day course, we will present the OMERO platform, and show how Facility Managers can use it to manage users, groups, and their microscopy, HCS and digital pathology data.

Help pages on 'Using OMERO for Facility Managers' can be found here.

This course is organized alongside a one day course on Biological Imaging Data Management for Life Scientists. More information on this event are available here.

This course will be delivered by members of the OMERO team. The OME project is supported by BBSRC and Wellcome Trust.

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 Open Microscopy Environment (OME) is an open-source software project that develops tools that enable access, analysis, visualization, sharing and publication of biological image data.

OME has three components:

• OME-TIFF, standardised file format and data model;
• Bio-Formats, a software library for reading proprietary image file formats; and
• OMERO, a software platform for image data management and analysis.

In this one day course, we will present the OMERO platform, and show how to import, organise, view, search, annotate and publish imaging data. Additionally, we will briefly introduce how to use a variety of processing tools with OMERO.

This course is organized alongside a one day course on Biological Imaging Data Processing for Data Scientists. More information on this event are available here.

This course will be delivered by members of the OMERO team. The OME project is supported by BBSRC and Wellcome Trust.

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 Open Microscopy Environment (OME) is an open-source software project that develops tools that enable access, analysis, visualization, sharing and publication of biological image data.

OME has three components:

• OME-TIFF, standardised file format and data model;
• Bio-Formats, a software library for reading proprietary image file formats; and
• OMERO, a software platform for image data management and analysis.

In this one day course, we will present the OMERO platform, and show how to transition from manual data processing to automated processing workflows. We will introduce how to write applications against the OMERO API, how to integrate a variety of processing tools with OMERO and how to automatically generate output ready for publication.

This course is organized alongside a one day course on Biological Imaging Data Management for Life Scientists. More information on this event are available here.

This course will be delivered by members of the OMERO team. The OME project is supported by BBSRC and Wellcome Trust.

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.

High-throughput data analyses usually involve many data processing steps, including the use of a range of command line tools and scripts to transform, filter, aggregate and visualise data. Each tool may require a specific set of inputs and options to be defined and, as we chain multiple tools together, this can become challenging to manage. As analyses pipelines become more complex and with the ever-increasing amounts of data being collected in research, reproducible and scalable automatic workflow management becomes increasingly important.

The Snakemake workflow management system is a tool to create reproducible and scalable data analyses pipelines/workflows. Workflows are described via a human-readable, Python-based language. They can be seamlessly scaled to server, cluster, grid and cloud environments, without the need to modify the workflow definition. Finally, Snakemake workflows can entail a description of the required software, which will be automatically deployed to any execution environment.

With over 500k downloads on Bioconda, and over 2k citations, Snakemake is a widely used and accepted standard for reproducible data science that has powered numerous research goals and publications.

This 1-day workshop will cover the principles for building workflows using Snakemake, as well as more advanced strategies to fully customise, automate and scale your analysis.

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 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.

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.

• ♿ 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.

The Bioinformatics Team are presently teaching this course live online, with tutors available to help you throughout if have any questions. We continue to monitor advice from the UK government and the University of Cambridge on resuming in-person teaching in our training room.

This award winning virtually delivered 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.

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.

COSMIC, the Catalogue of Somatic Mutations in Cancer, is the world’s largest and most comprehensive expert manually curated resource for exploring the impact of somatic mutations in human cancer. Based at the Wellcome Sanger Institute and available publicly at https://cancer.sanger.ac.uk/cosmic, the latest release includes almost 6 million coding mutations across 1.4 million samples from over 26,000 papers. COSMIC captures the full spectrum of genomic data relating to somatic mutations, so in addition to coding mutations, gene fusions, non-coding mutations, copy-number variants, methylation and drug resistance mutations are included.

This course will use the live COSMIC website and tools to show you how to access and explore this information, seeking to identify genetic causes and targets in all human cancers.

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.

Fiji/ImageJ is a popular open-source image analysis software application. This course will build on top of the Fiji basic course, to continue explore advanced image processing: segmentation, tracking, and with a specific focus on scripting/programming using Fiji scripting environment. We will use python programming language, and aim to give a tutorial on both image processing and python programming.

This course is run by the CRUK CI Light microscopy core facility.

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.

Although microarrays have been superseded by high-throughput sequencing technologies for gene expression profiling, years of experience gained from analysing microarray data has led to a variety of analysis techniques and datasets that can be exploited in other contexts. In this course, we will focus on retrieving and exploring microarray data from public repositories such as Gene Expression Omnibus (GEO).

Course materials can be found here.

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 by linking here.

Version control is the management of changes to documents, computer programs, and other collections of information. Changes are usually identified by a number named the "revision number". Each revision is associated with a timestamp and the person making the change. Revisions can be compared, restored, and with some types of files, merged.

Version control systems like subversion (svn) and git are frequently used for groups writing software and code, but can be used for any kind of files or projects. Many people share their git repositories on GitHub.

This course will provide an introduction to git and how you can use github to share your projects, or for your own private use if you wish.

Course materials can be found here.

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 course will provide participants with an introduction to EMBL-EBI and its data tools and resources, which cover the whole spectrum of biological / life sciences.

Sessions with trainers from ArrayExpress, Expression Atlas and the GWAS catalog will explore SNP-trait associations and show how further understanding can be gained on the location and level of gene expression across the body.

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.

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.

CellProfiler is a free, open-source image analysis software designed to enable biologists without training in computer vision or programming to quantitatively measure phenotypes from thousands of images automatically.

This course will introduce you the basic usage, and several application examples to help you understand and build up image processing and analysis workflows within CellProfiler. It will also cover a brief introduction to the usage of its companion package CellProfiler Analyst, which allows interactive exploration and analysis of image data. Some related theoretical topics in image processing will also be covered.

This course is run by the CRUK CI Light microscopy core facility.

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.

Fiji/ImageJ is a popular open-source image analysis software application. This course will briefly cover introductory aspects of image processing and analysis theory, but will focus on practical sessions where participants will gain hands on experience with Fiji.

This course is run by the CRUK CI Light microscopy core facility.

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.

Using the Cambridge Institute's High Performance Computing Facilities, this brief (0.5 day) course will give you three things:

• A refresher on Unix and an introduction to cluster computing, i.e. what High Performance Computing facilities re available to you at CI.
• Basic instruction on using our scheduler (The scheduler allots slots of processing time to the jobs submitted by the multiplicity of users on the cluster).
• Some performance hints for efficient use of the HPC

It won't make you an expert on parallel computing and H.P.C, but will let you get to work.

Note that a pre-requisite for this course is either existing familiarity with the Unix/Linux command-line or attendance of our Linux course CRUK: Introduction to Linux Command Line.

This course is run by the CRUK CI Bioinformatics and IT core.

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.

Galaxy is an open, web-based platform for data-intensive life science research that enables non-bioinformaticians to create, run, tune, and share their own bioinformatic analyses.

A Galaxy introduction course covering basic functions, simple data manipulation using use cases and examples and visualisation mostly targeted at first time users.

Further information is available from the course website.

This event is part of a series of training courses organised 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 by linking here.

This course provides a refresher on the foundations of statistical analysis. Practicals are conducted using the R commander package, which provides an accessible interface to the R statistical language.

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

Modern genomics technologies are able to produce large volumes of data that often leave researchers feeling overwhelmed and unsure of how to begin the process of biological interpretation.

In this course, we explain the common file formats generated by sequencing technologies and how they can be manipulated and explored by non-bioinformaticians. The tool that we will use is the Integrative Genomics Viewer (IGV).

If time allows, there will be time at the end of the session for you to explore your own datasets with the assistance of the instructors.

This event is part of a series of training courses organized in collaboration with Dr. Mark Dunning at CRUK Cambridge Institute. The materials for the course were developed in collaboration with Dr. Thomas Carroll from the MRC CSC.

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 has the following objectives:

• To provide an overview on the importance of microscopy image analysis and tools in Arivis Vision4D software for the quantification of various biological problems: cell analysis, time-lapse, colocalization, stitching, handle large images etc
• Practical session with computers during which participants will be introduced to image analysis and visualization using Vision4D
• Demonstration on how virtual reality can help with image visualization and quantification

This course is run by the CRUK CI Light microscopy core facility.

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.

CRUK Summer School

Event posted for Administration purposes only

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.