Bioinformatics course timetable

Open Targets was founded by three global leading institutions in the fields of pharmaceuticals, bioinformatics and genomics, GSK, EMBL-EBI, the Wellcome Trust Sanger Institute, and recently joined by Biogen, the world’s oldest independent biotechnology company.

We combine large-scale genomic experiments with objective statistical and computational techniques to identify and validate the causal links between targets, pathways and diseases. Cross-cutting several therapeutic areas, we generate cellular models of disease through gene editing technologies or single cell analysis. In addition to clinical samples, iPS cells and cellular organoids are resourced to provide cellular phenotyping with high physiological relevance. Open Targets integrates comprehensive datasets from a myriad of renowned public databases, such as UniProt, ChEMBL, Ensembl, NHGRI-EBI GWAS, EuropePMC, COSMIC, GTEx, among others. The data and analytical processes are developed by a set of interlinking projects.

The purpose of this half-day workshop is to acquaint participants with the Open Targets project and its Target Validation interface and introduce the tools for visualisation and interpretation of gene-disease associations and target validation based on a comprehensive platform with data from various publicly available databases. By the end of this half-day workshop, users will be able to carry out effective searches of data, use the web application to visualise genes, variants, ontology, pathways (and more) in the context of human disease and therapeutics.

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.

R is a highly-regarded, free, software environment for statistical analysis, with many useful features that promote and facilitate reproducible research.

In this course, we give an introduction to the R environment and explain how it can be used to import, manipulate and analyse tabular data. After the course you should feel confident to start exploring your own dataset using the materials and references provided.

Course materials are available here.

Please note that although we will demonstrate how to perform statistical analysis in R, we will not cover the theory of statistical analysis in this course. Those seeking an in-depth explanation of how to perform and interpret statistical tests are advised to see the list of Related courses. Moreover, those with some programming experience in other languages (e.g. Python, Perl) might wish to attend the follow-on Data Analysis and Visualisation in R course.

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.

R is a highly-regarded, free, software environment for statistical analysis, with many useful features that promote and facilitate reproducible research.

In this course, we give an introduction to the R environment and explain how it can be used to import, manipulate and analyse tabular data. After the course you should feel confident to start exploring your own dataset using the materials and references provided.

Course materials are available here.

Please note that although we will demonstrate how to perform statistical analysis in R, we will not cover the theory of statistical analysis in this course. Those seeking an in-depth explanation of how to perform and interpret statistical tests are advised to see the list of Related courses. Moreover, those with some programming experience in other languages (e.g. Python, Perl) might wish to attend the follow-on Data Analysis and Visualisation in R course.

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 workshop will give an introduction to the resources provided by UniProt. Participants will be shown, and given hands-on experience in, how to navigate the website, search for data and run analysis tools. The session also covers what the sources of our data are and how they are curated. A basic introduction into accessing UniProt Knowledgebase programmatically will be given as well.

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.

Recent technological advances have made it possible to obtain genome-wide transcriptome data from single cells using high-throughput sequencing (scRNA-seq). Even though scRNA-seq makes it possible to address problems that are intractable with bulk RNA-seq data, analysing scRNA-seq is also more challenging.

In this course we will be surveying the existing problems as well as the available computational and statistical frameworks available for the analysis of scRNA-seq.

Course materials are available here.

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

Recent technological advances have made it possible to obtain genome-wide transcriptome data from single cells using high-throughput sequencing (scRNA-seq). Even though scRNA-seq makes it possible to address problems that are intractable with bulk RNA-seq data, analysing scRNA-seq is also more challenging.

In this course we will be surveying the existing problems as well as the available computational and statistical frameworks available for the analysis of scRNA-seq.

Course materials are available 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 workshop will introduce students to EMBL-EBI, the databases and services it offers, and basic concepts in bioinformatics that will be of use to their disease related research work.

It will explain the role of the EBI in curating and sharing biological data with scientists around the world and introduce basics for locating relevant data and information of interest.

Sessions with trainers from Ensembl, ArrayExpress and the GWAS catalog will introduce practical skills in browsing genes and variation in a genomic context, in exploring SNP-trait associations and will show how further understanding can be gained on the location and level of gene expression across the body.

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 aim of this course is to familiarize the participants with the primary analysis of datasets generated through two popular high-throughout sequencing (HTS) assays: ChIP-seq and RNA-seq.

This course starts with a brief introduction to the transition from capillary to high-throughput sequencing (HTS) and discusses quality control issues, which are common among all HTS datasets.

Next, we will present the alignment step and how it differs between the two analysis workflows.

Finally, we focus on dataset specific downstream analysis, including peak calling and motif analysis for ChIP-seq and quantification of expression, transcriptome assembly and differential expression analysis for RNA-seq.

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.

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.

InterMine is a freely available data warehouse and analysis software system that has been used to create a suite of databases for the analysis of large and complex biological data sets.

InterMine-based data analysis platforms are available for many organisms including mouse, rat, budding yeast, plants, nematodes, fly, zebrafish and more recently human.

The InterMine web interface offers sophisticated query and visualisation tools, as well as comprehensive web services for bioinformaticians. Genomic and proteomic data within InterMine databases includes pathways, gene expression, interactions, sequence variants, GWAS, regulatory data and protein expression.

We have recently re-designed the InterMine interface to provide a more intuitive user-experience. This workshop will provide an overview of key features of the new interface and how this can be used to interrogate genomic and proteomic data.

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.

Statistics are an important part of most modern studies and being able to effectively use a statistical package will help you to understand your results.

This course provides an introduction to some statistical techniques through the use of the R language. Topics covered include: Chi2 and Fisher tests, descriptive statistics, t-test, analysis of variance and regression.

Students will run analyses using statistical and graphical skills taught during the session.

The 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 course will cover common image analysis problems including colocalization, segmentation and tracking. We will also cover the handling of large data including registration, fusion and visualization. We will use Fiji and Icy; two leading open source image analysis software applications.

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 course will cover common image analysis problems including colocalization, segmentation and tracking. We will also cover the handling of large data including registration, fusion and visualization. We will use Fiji and Icy; two leading open source image analysis software applications.

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 advanced course will cover high-throughput sequencing data processing, ChIP-seq data analysis (including alignment, peak calling), differences in analyses methods for transcription factors (TF) binding and epigenomic datasets, a range of downstream analysis methods for extracting meaningful biology from ChIP-seq data and will provide an introduction to the analysis of open chromatin with ATAC-seq and long-distance interactions with chromosomal conformation capture based Hi-C datasets.

Materials for this course can be found 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.

This course will focus on handling of large image data including image registration, fusion, deconvolution and visualization. We will use Fiji, an open source image analysis software.

This course covers data resources and analytical approaches for the discovery and interpretation of biomacromolecular structures.

Day 1 focuses on public repositories of structural data (Protein Data Bank and Electron Microscopy Data Bank) and resources for protein analysis and classification (Pfam, InterPro and HMMER).

Day 2 covers how to find information about the structure and function of your protein sequence using CATH, principles of modern state-of-the-art protein modelling with Phyre2 and methods for predicting the effects of mutations on protein structure and function using the SAAP family of tools.

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 covers data resources and analytical approaches for the discovery and interpretation of biomacromolecular structures.

Day 1 focuses on public repositories of structural data (Protein Data Bank and Electron Microscopy Data Bank) and resources for protein analysis and classification (Pfam, InterPro and HMMER).

Day 2 covers how to find information about the structure and function of your protein sequence using CATH, principles of modern state-of-the-art protein modelling with Phyre2 and methods for predicting the effects of mutations on protein structure and function using the SAAP family of tools.

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

R is a highly-regarded, free, software environment for statistical analysis, with many useful features that promote and facilitate reproducible research.

In this course, we give an introduction to the R environment and explain how it can be used to import, manipulate and analyse tabular data. After the course you should feel confident to start exploring your own dataset using the materials and references provided.

Course materials are available here.

Please note that although we will demonstrate how to perform statistical analysis in R, we will not cover the theory of statistical analysis in this course. Those seeking an in-depth explanation of how to perform and interpret statistical tests are advised to see the list of Related courses. Moreover, those with some programming experience in other languages (e.g. Python, Perl) might wish to attend the follow-on Data Analysis and Visualisation in R course.

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.

R is a highly-regarded, free, software environment for statistical analysis, with many useful features that promote and facilitate reproducible research.

In this course, we give an introduction to the R environment and explain how it can be used to import, manipulate and analyse tabular data. After the course you should feel confident to start exploring your own dataset using the materials and references provided.

Course materials are available here.

Please note that although we will demonstrate how to perform statistical analysis in R, we will not cover the theory of statistical analysis in this course. Those seeking an in-depth explanation of how to perform and interpret statistical tests are advised to see the list of Related courses. Moreover, those with some programming experience in other languages (e.g. Python, Perl) might wish to attend the follow-on Data Analysis and Visualisation in R course.

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.