Bioinformatics course timetable

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 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Although microarrays have been superseded by high-throughput sequencing technologies for gene expression profiling, years of experience gained from analysing microarray data has led to a variety of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).

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.

Although microarrays have been superseded by high-throughput sequencing technologies for gene expression profiling, years of experience gained from analysing microarray data has led to a variety of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).

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.

This course provides an introduction to the R programming language and software environment for statistical computing and graphics. A variety of examples with a biological theme will be presented.

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 or register Interest by linking here.

This course provides an introduction to the R programming language and software environment for statistical computing and graphics. A variety of examples with a biological theme will be presented.

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 or register Interest 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.

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 by linking here.

This course provides a practical introduction to the writing of Python programs for the complete novice. Participants are lead through the core aspects of Python illustrated by a series of example programs. Upon completion of the course, attentive participants will be able to write simple Python programs from scratch and to customize more complex code to fit their needs.

The Course Web Site 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.

This course provides a practical introduction to the writing of Python programs for the complete novice. Participants are lead through the core aspects of Python illustrated by a series of example programs. Upon completion of the course, attentive participants will be able to write simple Python programs from scratch and to customize more complex code to fit their needs.

The Course Web Site 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.

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.

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 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.

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.

This introductory course will cover Galaxy's basic functionality, simple data manipulation and visualization. This event is mostly targeted at first time users.

Further information is available from the course website.

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.

This course provides an introduction to high-throughput sequencing (HTS) data analysis methodologies. Lectures will give insight into how biological knowledge can be generated from RNA-seq, ChIP-seq and DNA-seq experiments and illustrate different ways of analyzing such data. Practicals will consist of computer exercises that will enable the participants to apply statistical methods to the analysis of RNA-seq, ChIP-seq and DNA-seq data under the guidance of the lecturers and teaching assistants. It is aimed at researchers who are applying or planning to apply HTS technologies and bioinformatics methods in their research.

The timetable 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 Interest by linking here.

This course provides an introduction to high-throughput sequencing (HTS) data analysis methodologies. Lectures will give insight into how biological knowledge can be generated from RNA-seq, ChIP-seq and DNA-seq experiments and illustrate different ways of analyzing such data. Practicals will consist of computer exercises that will enable the participants to apply statistical methods to the analysis of RNA-seq, ChIP-seq and DNA-seq data under the guidance of the lecturers and teaching assistants. It is aimed at researchers who are applying or planning to apply HTS technologies and bioinformatics methods in their research.

The timetable 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 Interest by linking here.

This course provides an introduction to high-throughput sequencing (HTS) data analysis methodologies. Lectures will give insight into how biological knowledge can be generated from RNA-seq, ChIP-seq and DNA-seq experiments and illustrate different ways of analyzing such data. Practicals will consist of computer exercises that will enable the participants to apply statistical methods to the analysis of RNA-seq, ChIP-seq and DNA-seq data under the guidance of the lecturers and teaching assistants. It is aimed at researchers who are applying or planning to apply HTS technologies and bioinformatics methods in their research.

The timetable 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 Interest by linking here.

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 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 provides an introduction to the R programming language and software environment for statistical computing and graphics. A variety of examples with a biological theme will be presented.

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 or register Interest by linking here.

This course provides an introduction to the R programming language and software environment for statistical computing and graphics. A variety of examples with a biological theme will be presented.

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 or register Interest by linking here.

A hands-on interactive course that will introduce you to how to analyse genomic sequences in the command line environment. Examples will focus on metagenomics data but the course is suitable to anyone starting to analyze high-throughput sequencing data.

This course will be taught by Dr. Adina Howe from Iowa State University. Her group focuses on integrating traditional microbiology approaches with metagenomics and computational biology as investigative tools to understand environmental microbial populations

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 practical introduction to the writing of Python programs for the complete novice. Participants are lead through the core aspects of Python illustrated by a series of example programs. Upon completion of the course, attentive participants will be able to write simple Python programs from scratch and to customize more complex code to fit their needs.

The Course Web Site 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.

This course provides a practical introduction to the writing of Python programs for the complete novice. Participants are lead through the core aspects of Python illustrated by a series of example programs. Upon completion of the course, attentive participants will be able to write simple Python programs from scratch and to customize more complex code to fit their needs.

The Course Web Site 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 course will teach intermediate R object-oriented programming and how to build a fully functional R package.

The course page includes slides and handouts; other relevant teaching materials are available here) and the sequences example package used as template in the 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 register Interest by linking here.

This two day course will cover network-based approaches to visualise and analyse complex biological ‘big’ data and model pathway systems. The course will be centred on the use of BioLayout Express3D, a tool developed between scientists at the University of Edinburgh and EBI over the last 10 years.

BioLayout provides rapid and versatile means to explore and integrate very large datasets, providing a stunning interface to visualise the relationships between 10’s of thousands of data points. Originally designed for the analysis of microarray data, it is equally effective in analysing data matrices from other analysis platforms.

Day one of the course will introduce principles of network analysis and their use as a generic medium to understand relationships between entities. We will introduce the basics of network visualisation and navigation within BioLayout and principles of correlation analysis of data matrices. We will then explore how data can be explored and clustered within the tool and how you can use the software to rapidly extract meaning from large and complex datasets.

Day two will focus on pathway modelling. We will explain how to collate information about a given system of interest from the literature, and to turn this information into a logic-based pathway model. We will then explore how these models can be parametrised and imported into BioLayout where simulations can be run that model the dynamics of these systems under different conditions. For more information see: http://www.virtuallyimmune.org/

A draft agenda 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 Interest by linking here.

This two day course will cover network-based approaches to visualise and analyse complex biological ‘big’ data and model pathway systems. The course will be centred on the use of BioLayout Express3D, a tool developed between scientists at the University of Edinburgh and EBI over the last 10 years.

BioLayout provides rapid and versatile means to explore and integrate very large datasets, providing a stunning interface to visualise the relationships between 10’s of thousands of data points. Originally designed for the analysis of microarray data, it is equally effective in analysing data matrices from other analysis platforms.

Day one of the course will introduce principles of network analysis and their use as a generic medium to understand relationships between entities. We will introduce the basics of network visualisation and navigation within BioLayout and principles of correlation analysis of data matrices. We will then explore how data can be explored and clustered within the tool and how you can use the software to rapidly extract meaning from large and complex datasets.

Day two will focus on pathway modelling. We will explain how to collate information about a given system of interest from the literature, and to turn this information into a logic-based pathway model. We will then explore how these models can be parametrised and imported into BioLayout where simulations can be run that model the dynamics of these systems under different conditions. For more information see: http://www.virtuallyimmune.org/

A draft agenda 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 Interest 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 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.

The course will provide training for bench-based biologists to use molecular data to construct and interpret phylogenies, and test their hypotheses. Delegates will gain hands-on practice of using a variety of programs freely available online and commonly used in molecular studies, interspersed with some lectures.

Course timetable is 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.

The course will provide training for bench-based biologists to use molecular data to construct and interpret phylogenies, and test their hypotheses. Delegates will gain hands-on practice of using a variety of programs freely available online and commonly used in molecular studies, interspersed with some lectures.

Course timetable is 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.

The course will provide training for bench-based biologists to use molecular data to construct and interpret phylogenies, and test their hypotheses. Delegates will gain hands-on practice of using a variety of programs freely available online and commonly used in molecular studies, interspersed with some lectures.

Course timetable is 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.

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 manual 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 provides an introduction to the tools available through the Bioconductor project for manipulating and analysing high-throughput sequencing (HTS) data. We will present workflows for the analysis of ChIP-Seq and RNA-seq data starting from aligned reads in bam format. We will also describe the various resources available through Bioconductor to annotate and visualize HTS data, which can be applied to any type of sequencing experiment.

The course timetable is 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 course provides an introduction to the tools available through the Bioconductor project for manipulating and analysing high-throughput sequencing (HTS) data. We will present workflows for the analysis of ChIP-Seq and RNA-seq data starting from aligned reads in bam format. We will also describe the various resources available through Bioconductor to annotate and visualize HTS data, which can be applied to any type of sequencing experiment.

The course timetable is 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 course provides an introduction to the tools available through the Bioconductor project for manipulating and analysing high-throughput sequencing (HTS) data. We will present workflows for the analysis of ChIP-Seq and RNA-seq data starting from aligned reads in bam format. We will also describe the various resources available through Bioconductor to annotate and visualize HTS data, which can be applied to any type of sequencing experiment.

The course timetable is 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 course introduces some relatively new additions to the R programming language: dplyr and ggplot2. In combination these R packages provide a powerful toolkit to make the process of manipulating and visualising data easy and intuitive.

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 by linking here.

This course aims to provide trainers with guidance and tips for developing and delivering training in bioinformatics, exploring a range of methods appropriate to different learning styles and examining the requirements for a successful course (both scientific and logistic).

This event is organized as part of the Horizon 2020 ELIXIR-EXCELERATE project.

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 aims to provide trainers with guidance and tips for developing and delivering training in bioinformatics, exploring a range of methods appropriate to different learning styles and examining the requirements for a successful course (both scientific and logistic).

This event is organized as part of the Horizon 2020 ELIXIR-EXCELERATE project.

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 this course we will introduce web-based, open source tools to analyse and interpret high-throughput biological data.

The main focus will be g:Profiler - a toolset for finding most significant functional groups for a given gene or protein list; MEM - a query engine allowing to mine hundreds of public gene expression datasets to find most co-expressed genes based on a query gene; and ClustVis - a web tool for visualizing clustering of multivariate data using Principal Component Analysis (PCA) plot and heatmap.

MEM and g:Profiler are ELIXIR-Estonia node services.

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

During this course you will learn about:

• How to use spreadsheet programs (such as Excel) more effectively, and the limitations of such programs
• Getting data out of spreadsheets and into more powerful tools (R)
• Data management and manipulation
• Data visualization
• Workflows and automating repetitive tasks, in particular using the command line shell

This event is organized in collaboration with Data Carpentry and is sponsored by the HORIZON 2020 TWINNING Project TrainMalta.

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 by linking here.

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 main tools that we will use are the Integrative Genomics Viewer (IGV) and University of Santa Cruz (UCSC) genome browser.

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 will focus on computational methods for analysing cellular images and extracting quantitative data from them. The aim of this course is to familiarise the participants with computational image analysis methodologies, and to provide hands-on training in running quantitative analysis pipelines.

On day 1 we will introduce principles of image processing and analysis, giving an overview of commonly used algorithms through a series of talks and practicals based on Fiji, an extensible open source software package.

On day 2, we will describe the open Icy platform developed at the Institut Pasteur. Icy is a next-generation, user-friendly software offering powerful acquisition, visualization, annotation and analysis algorithms for 5D bioimaging data, together with unique automation/scripting capabilities (notably via its graphical programming interface) and tight integration with existing software (e.g. ImageJ, Matlab, Micro-Manager).

The timetable 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 Interest by linking here.

This course will focus on computational methods for analysing cellular images and extracting quantitative data from them. The aim of this course is to familiarise the participants with computational image analysis methodologies, and to provide hands-on training in running quantitative analysis pipelines.

On day 1 we will introduce principles of image processing and analysis, giving an overview of commonly used algorithms through a series of talks and practicals based on Fiji, an extensible open source software package.

On day 2, we will describe the open Icy platform developed at the Institut Pasteur. Icy is a next-generation, user-friendly software offering powerful acquisition, visualization, annotation and analysis algorithms for 5D bioimaging data, together with unique automation/scripting capabilities (notably via its graphical programming interface) and tight integration with existing software (e.g. ImageJ, Matlab, Micro-Manager).

The timetable 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 Interest by linking here.

This course provides an introduction to the R programming language and software environment for statistical computing and graphics. A variety of examples with a biological theme will be presented.

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 or register Interest by linking here.

This course provides an introduction to the R programming language and software environment for statistical computing and graphics. A variety of examples with a biological theme will be presented.

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 or register Interest by linking here.

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 will be comprised of a mixture of theoretical lectures and practicals covering a range of different software packages.

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 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.

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 Ensembl Project provides a comprehensive and integrated source of annotation of, mainly vertebrate, genome sequences. 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.

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.

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 focus on the core steps involved in calling variants with the Broad’s Genome Analysis Toolkit, using the “Best Practices” developed by the GATK team. You will learn why each step is essential to the variant discovery process, what are the operations performed on the data at each step, and how to use the GATK tools to get the most accurate and reliable results out of your dataset.

In the course of this workshop, we highlight key functionalities such as the GVCF workflow for joint variant discovery in cohorts, RNAseq­ specific processing, and somatic variant discovery using MuTect2. We also preview capabilities of the upcoming GATK version 4, including a new workflow for CNV discovery.

The workshop is composed of one day of lectures (including many opportunities for Q&A) and one day of hands­on training. On the first day, we explain the rationale, theory and application of our Best Practices for Variant Discovery in high­-throughput sequencing data. On the second day, we walk attendees through hands­on exercises that teach how to manipulate the standard data formats involved in variant discovery and how to apply GATK tools appropriately to various use cases and data types. In the course of these exercises, we demonstrate useful tips and tricks for interacting with GATK, dealing with problems, and using third­party tools such as Samtools, IGV and RStudio.

Please note that this workshop is focused on human data analysis. The majority of the materials presented does apply equally to non ­human data, and we will address some questions regarding adaptations that are needed for analysis of non­ human data, but we will not go into much detail on those points.

The timetable 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 Interest by linking here.

This workshop will focus on the core steps involved in calling variants with the Broad’s Genome Analysis Toolkit, using the “Best Practices” developed by the GATK team. You will learn why each step is essential to the variant discovery process, what are the operations performed on the data at each step, and how to use the GATK tools to get the most accurate and reliable results out of your dataset.

In the course of this workshop, we highlight key functionalities such as the GVCF workflow for joint variant discovery in cohorts, RNAseq­ specific processing, and somatic variant discovery using MuTect2. We also preview capabilities of the upcoming GATK version 4, including a new workflow for CNV discovery.

The workshop is composed of one day of lectures (including many opportunities for Q&A) and one day of hands­on training. On the first day, we explain the rationale, theory and application of our Best Practices for Variant Discovery in high­-throughput sequencing data. On the second day, we walk attendees through hands­on exercises that teach how to manipulate the standard data formats involved in variant discovery and how to apply GATK tools appropriately to various use cases and data types. In the course of these exercises, we demonstrate useful tips and tricks for interacting with GATK, dealing with problems, and using third­party tools such as Samtools, IGV and RStudio.

Please note that this workshop is focused on human data analysis. The majority of the materials presented does apply equally to non ­human data, and we will address some questions regarding adaptations that are needed for analysis of non­ human data, but we will not go into much detail on those points.

The timetable 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 Interest by linking here.

This course provides a practical introduction to the writing of Python programs for the complete novice. Participants are lead through the core aspects of Python illustrated by a series of example programs. Upon completion of the course, attentive participants will be able to write simple Python programs from scratch and to customize more complex code to fit their needs.

The Course Web Site 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.

This course provides a practical introduction to the writing of Python programs for the complete novice. Participants are lead through the core aspects of Python illustrated by a series of example programs. Upon completion of the course, attentive participants will be able to write simple Python programs from scratch and to customize more complex code to fit their needs.

The Course Web Site 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 Unix shell has existed since the early days of computers, and yet is still the preferred way to run many popular Bioinformatics tools. This course aims to take the novice and turn them into a beginning Linux user. We will describe the Linux environment so they can start to utilize command-line tools and feel comfortable using a text-based way of interacting with a computer.

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 provides a refresher on the foundations of statistical analysis. The emphasis is on interpreting the results of a statistical test, and being able to determine the correct test to apply.

Practicals are conducted using a series of online apps, and we will not teach a particular statistical analysis package, such as R. For courses that teach R, please see the links under "Related courses" .

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.

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.

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 by linking here.

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 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.

The Ensembl project provides a comprehensive and integrated source of annotation of mainly vertebrate genome sequences.

This workshop is aimed at researchers and developers interested in exploring Ensembl beyond the website. The workshop covers the core, compara, variation and functional genomics (regulation) databases and APIs. The Ensembl Perl API Documentation can be found here.

For each of these, the database schema and the API design as well as the most important objects and their methods will be presented. This will be followed by practical sessions in which the participants can put theoretical learning into practice by writing their own Perl scripts.

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 workshop is aimed at researchers and developers interested in exploring Ensembl beyond the website. The workshop covers the core, compara, variation and functional genomics (regulation) databases and APIs. The Ensembl Perl API Documentation can be found here.

For each of these, the database schema and the API design as well as the most important objects and their methods will be presented. This will be followed by practical sessions in which the participants can put theoretical learning into practice by writing their own Perl scripts.

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 workshop is aimed at researchers and developers interested in exploring Ensembl beyond the website. The workshop covers the core, compara, variation and functional genomics (regulation) databases and APIs. The Ensembl Perl API Documentation can be found here.

For each of these, the database schema and the API design as well as the most important objects and their methods will be presented. This will be followed by practical sessions in which the participants can put theoretical learning into practice by writing their own Perl scripts.

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 workshop is aimed at researchers and developers interested in exploring Ensembl beyond the website. The workshop covers the core, compara, variation and functional genomics (regulation) databases and APIs. The Ensembl Perl API Documentation can be found here.

For each of these, the database schema and the API design as well as the most important objects and their methods will be presented. This will be followed by practical sessions in which the participants can put theoretical learning into practice by writing their own Perl scripts.

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 practical guide to producing figures for use in reports and publications.

It is a wide ranging course which looks at how to design figures to clearly and fairly represent your data, the practical aspects of graph creation, the allowable manipulation of bitmap images and compositing and editing of final figures.

The course will use a number of different open source software packages and is illustrated with a number of example figures adapted from common analysis tools.

Further information and access 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 or register Interest by linking here.

This course introduces some relatively new additions to the R programming language: dplyr and ggplot2. In combination these R packages provide a powerful toolkit to make the process of manipulating and visualising data easy and intuitive.

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 by linking here.

DECIPHER is a collaborative data sharing and interpretation platform that enables the secure upload, analysis and subsequent sharing of anonymised phenotype-linked patient variant data in rare genetic disorders.

DECIPHER is a worldwide user community of over 250 clinical genetics centres and research groups from over 40 countries that utilise the built-in tools for aiding the interpretation of variants as well as to discover other patients that share similar phenotype and genomic findings.

DECIPHER facilitates collaboration and exchange of information between a global community of clinical centers and researchers leading thereby accelerating discovery and diagnosis. Access to consented anonymised records is free to all users. User accounts are provided to bona-fide clinicians and lab scientists to enable deposition and sharing of anonymised patient data.

The purpose of this half-day workshop is to acquaint participants with the DECIPHER website and database and introduce the various built-in tools for visualisation and interpretation of phenotype-linked genomic variation in anonymised consented patient data. It is hoped that by the end of this workshop, users will be able to carry out effective searches of data, use the built-in genome browser to visualise variation in context of other pathogenic and reference data sources, find other patients with similar variants and shared phenotypes, and identify most likely causes of phenotypic presentation by gene prioritisation.

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 aims to provide new trainers with guidance and tips for developing and delivering training in bioinformatics, exploring a range of methods appropriate to different learning styles and examining the requirements for a successful course (both scientific and logistic).

This course aims to provide new trainers with guidance and tips for developing and delivering training in bioinformatics, exploring a range of methods appropriate to different learning styles and examining the requirements for a successful course (both scientific and logistic).

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 analysis tools with OMERO.

This course is organized alongside a one day course on Biological Imaging Data Management for Facility Managers. 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.

This workshop will guide novice users through the process of analysing interaction networks – that allow biologists to map and characterise signalling pathways and to predict the function of unknown proteins. It will use practical examples in the popular open-source tool Cytoscape and the PSICQUIC client to access several protein interaction repositories at the same time to integrate protein data from different sources. Data from external sources will then be incorporated using different Cytoscape apps to perform clustering and GO enrichment analysis over our newly created networks.

The timetable for this event 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.

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.

The timetable for this event 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 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.

The timetable for this event 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 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.

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.

LithoGraphX is a software to visualize, process and analyse 3D images and meshes.

On the first day of this course, we will demonstrate how to use LithoGraphX to visualize, clean and process 2D and 3D images. We will cover: (i) how to extract cell shape from 2D or 3D images by marking the cell wall or membrane, (ii) how to extract key morphological features and (iii) how to use these features to build a cell classifier. The first day is intended for biologists and computer scientists interested in using LithoGraphX.

On the second day, we will see how to write and distribute extensions to LithoGraphX. To this purpose, we will learn more about the internals of LithoGraphX and its API both in C++ and Python. The second day is intended for computer scientists wanting either to write their own algorithm or automate complex protocols.

Participants can choose to register for both days or for individual days, depending on their interest and background knowledge.

The timetable for this event can be found here.

This course is organized in collaboration with Dr Susana Sauret-Gueto from the OpenPlant Lab of the Department of Plant Sciences of the University of Cambridge.

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.

LithoGraphX is a software to visualize, process and analyse 3D images and meshes.

On the first day of this course, we will demonstrate how to use LithoGraphX to visualize, clean and process 2D and 3D images. We will cover: (i) how to extract cell shape from 2D or 3D images by marking the cell wall or membrane, (ii) how to extract key morphological features and (iii) how to use these features to build a cell classifier. The first day is intended for biologists and computer scientists interested in using LithoGraphX.

On the second day, we will see how to write and distribute extensions to LithoGraphX. To this purpose, we will learn more about the internals of LithoGraphX and its API both in C++ and Python. The second day is intended for computer scientists wanting either to write their own algorithm or automate complex protocols.

Participants can choose to register for both days or for individual days, depending on their interest and background knowledge.

The timetable for this event can be found here.

This course is organized in collaboration with Dr Susana Sauret-Gueto from the OpenPlant Lab of the Department of Plant Sciences of the University of Cambridge.

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 provides an introduction to the R programming language and software environment for statistical computing and graphics. A variety of examples with a biological theme will be presented.

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 or register Interest by linking here.

This course provides an introduction to the R programming language and software environment for statistical computing and graphics. A variety of examples with a biological theme will be presented.

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 or register Interest by linking here.

The aim of this course is to familiarise the participants with advanced data analysis methodologies and provide hands-on training on the latest analytical approaches. Lectures will give insight into how biological knowledge can be generated from High-throughput sequencing experiments and illustrate different ways of analyzing such data. Practicals will consist of computer exercises that will enable the participants to apply statistical methods to the analysis of sequencing data under the guidance of the lecturers and teaching assistants.

The timetable can be found here.

The aim of this course is to familiarise the participants with advanced data analysis methodologies and provide hands-on training on the latest analytical approaches. Lectures will give insight into how biological knowledge can be generated from High-throughput sequencing experiments and illustrate different ways of analyzing such data. Practicals will consist of computer exercises that will enable the participants to apply statistical methods to the analysis of sequencing data under the guidance of the lecturers and teaching assistants.

The timetable can be found here.

The aim of this course is to familiarise the participants with advanced data analysis methodologies and provide hands-on training on the latest analytical approaches. Lectures will give insight into how biological knowledge can be generated from High-throughput sequencing experiments and illustrate different ways of analyzing such data. Practicals will consist of computer exercises that will enable the participants to apply statistical methods to the analysis of sequencing data under the guidance of the lecturers and teaching assistants.

The timetable can be found here.

The aim of this course is to familiarise the participants with advanced data analysis methodologies and provide hands-on training on the latest analytical approaches. Lectures will give insight into how biological knowledge can be generated from High-throughput sequencing experiments and illustrate different ways of analyzing such data. Practicals will consist of computer exercises that will enable the participants to apply statistical methods to the analysis of sequencing data under the guidance of the lecturers and teaching assistants.

The timetable can be found here.

The aim of this course is to familiarise the participants with advanced data analysis methodologies and provide hands-on training on the latest analytical approaches. Lectures will give insight into how biological knowledge can be generated from High-throughput sequencing experiments and illustrate different ways of analyzing such data. Practicals will consist of computer exercises that will enable the participants to apply statistical methods to the analysis of sequencing data under the guidance of the lecturers and teaching assistants.

The timetable can be found here.

The aim of this course is to familiarise the participants with advanced data analysis methodologies and provide hands-on training on the latest analytical approaches. Lectures will give insight into how biological knowledge can be generated from High-throughput sequencing experiments and illustrate different ways of analyzing such data. Practicals will consist of computer exercises that will enable the participants to apply statistical methods to the analysis of sequencing data under the guidance of the lecturers and teaching assistants.

The timetable can be found 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.

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.

This course provides a practical guide to producing figures for use in reports and publications.

It is a wide ranging course which looks at how to design figures to clearly and fairly represent your data, the practical aspects of graph creation, the allowable manipulation of bitmap images and compositing and editing of final figures.

The course will use a number of different open source software packages and is illustrated with a number of example figures adapted from common analysis tools.

Further information and access 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 or register Interest by linking here.

This course is aimed at researchers who want to learn core skills and best practices for scientific computing. It will cover basic concepts and tools, including program design, version control, data management, and task automation. Participants will be encouraged to help one another and to apply what they have learned to their own research problems.

The course covers the core skills needed to be productive in a small research team:

• Unix command line (and how to automate repetitive tasks);
• Python or R (and how to grow a program in a modular, testable way); and
• version control with Git (and how to track and share work efficiently).

Further information is available here.

Applicants for this course are requested to complete a pre-course survey. This will be used to tailor the course content to the audience research interests and background.

This event is organized in collaboration with Software Carpentry.

This course is aimed at researchers who want to learn core skills and best practices for scientific computing. It will cover basic concepts and tools, including program design, version control, data management, and task automation. Participants will be encouraged to help one another and to apply what they have learned to their own research problems.

The course covers the core skills needed to be productive in a small research team:

• Unix command line (and how to automate repetitive tasks);
• Python or R (and how to grow a program in a modular, testable way); and
• version control with Git (and how to track and share work efficiently).

Further information is available here.

Applicants for this course are requested to complete a pre-course survey. This will be used to tailor the course content to the audience research interests and background.

This event is organized in collaboration with Software Carpentry.

The aim of this workshop is to introduce principal investigators to the challenges of working with biological data, to provide guidance on how to manage such data and to encourage the development of bioinformatics skills in their team.

A timetable for this workshop 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 Interest by linking here.

This course provides a practical introduction to the writing of Python programs for the complete novice. Participants are lead through the core aspects of Python illustrated by a series of example programs. Upon completion of the course, attentive participants will be able to write simple Python programs from scratch and to customize more complex code to fit their needs.

The Course Web Site 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.

This course provides a practical introduction to the writing of Python programs for the complete novice. Participants are lead through the core aspects of Python illustrated by a series of example programs. Upon completion of the course, attentive participants will be able to write simple Python programs from scratch and to customize more complex code to fit their needs.

The Course Web Site 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.

COSMIC is an expert-curated database of somatic mutations causing human cancer. Broad and comprehensive in scope, it describes over 4 million coding mutations across all human cancer disease types, and encompasses over 20 million somatic variants across other molecular mutation mechanisms in oncogenetics. Mutations are annotated across the entire genome, with deep-resolution expert curation focused on almost 200 key cancer genes.

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

A timetable for 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 by linking here.

This course introduces some relatively new additions to the R programming language: dplyr and ggplot2. In combination these R packages provide a powerful toolkit to make the process of manipulating and visualising data easy and intuitive.

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 by linking here.

This course provides an introduction to the analysis of human genome sequence variation with next generation sequencing data (NGS), including:

• an introduction to genetic variation as well as data formats and analysis workflows commonly used in NGS data analysis;
• an overview of available analytical tools and discussion of their limitations; and
• hands-on experience with common computational workflows for analysing genome sequence variation using bioinformatics and computational genomics approaches.

A draft agenda 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 Interest by linking here.

This course provides an introduction to the analysis of human genome sequence variation with next generation sequencing data (NGS), including:

• an introduction to genetic variation as well as data formats and analysis workflows commonly used in NGS data analysis;
• an overview of available analytical tools and discussion of their limitations; and
• hands-on experience with common computational workflows for analysing genome sequence variation using bioinformatics and computational genomics approaches.

A draft agenda 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 Interest by linking here.

The course will teach intermediate R object-oriented programming and how to build a fully functional R package.

The course page includes slides and handouts; other relevant teaching materials are available here) and the sequences example package used as template in the 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 register Interest by linking here.

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.

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 will be comprised of a mixture of theoretical lectures and practicals covering a range of different software packages.

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 course provides a practical introduction to the writing of Python programs for the complete novice. Participants are lead through the core aspects of Python illustrated by a series of example programs. Upon completion of the course, attentive participants will be able to write simple Python programs from scratch and to customize more complex code to fit their needs.

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 course provides a practical introduction to the writing of Python programs for the complete novice. Participants are lead through the core aspects of Python illustrated by a series of example programs. Upon completion of the course, attentive participants will be able to write simple Python programs from scratch and to customize more complex code to fit their needs.

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 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 lecture, workshop and hands-on practice – 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 will use some practical statistics examples in R to introduce concepts in data presentation for publication. Covering: Some practical examples of statistics in R. Visualising and publishing your data.

Course materials are available here.

This event is sponsored by CRUK.

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 lecture, workshop and hands-on practice – 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 will use some practical statistics examples in R to introduce concepts in data presentation for publication. Covering: Some practical examples of statistics in R. Visualising and publishing your data.

Course materials are available here.

This event is sponsored by CRUK.

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 lecture, workshop and hands-on practice – 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 will use some practical statistics examples in R to introduce concepts in data presentation for publication. Covering: Some practical examples of statistics in R. Visualising and publishing your data.

Course materials are available here.

This event is sponsored by CRUK.

This course will focus on computational methods for analysing cellular images and extracting quantitative data from them. The aim of this course is to familiarise the participants with computational image analysis methodologies, and to provide hands-on training in running quantitative analysis pipelines.

On day 1 we will introduce principles of image processing and analysis, giving an overview of commonly used algorithms through a series of talks and practicals based on Fiji, an extensible open source software package.

On day 2, we will describe the open Icy platform developed at the Institut Pasteur. Icy is a next-generation, user-friendly software offering powerful acquisition, visualization, annotation and analysis algorithms for 5D bioimaging data, together with unique automation/scripting capabilities (notably via its graphical programming interface) and tight integration with existing software (e.g. ImageJ, Matlab, Micro-Manager).

On day 3, we will cover time series processing and cell tracking using TrackMate. Additionally, in the afternoon we will run a study design and data clinic (sign up will be required) for participants that wish to discuss their experiments.

A timetable 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.

This course will focus on computational methods for analysing cellular images and extracting quantitative data from them. The aim of this course is to familiarise the participants with computational image analysis methodologies, and to provide hands-on training in running quantitative analysis pipelines.

On day 1 we will introduce principles of image processing and analysis, giving an overview of commonly used algorithms through a series of talks and practicals based on Fiji, an extensible open source software package.

On day 2, we will describe the open Icy platform developed at the Institut Pasteur. Icy is a next-generation, user-friendly software offering powerful acquisition, visualization, annotation and analysis algorithms for 5D bioimaging data, together with unique automation/scripting capabilities (notably via its graphical programming interface) and tight integration with existing software (e.g. ImageJ, Matlab, Micro-Manager).

On day 3, we will cover time series processing and cell tracking using TrackMate. Additionally, in the afternoon we will run a study design and data clinic (sign up will be required) for participants that wish to discuss their experiments.

A timetable 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.

This course will focus on computational methods for analysing cellular images and extracting quantitative data from them. The aim of this course is to familiarise the participants with computational image analysis methodologies, and to provide hands-on training in running quantitative analysis pipelines.

On day 1 we will introduce principles of image processing and analysis, giving an overview of commonly used algorithms through a series of talks and practicals based on Fiji, an extensible open source software package.

On day 2, we will describe the open Icy platform developed at the Institut Pasteur. Icy is a next-generation, user-friendly software offering powerful acquisition, visualization, annotation and analysis algorithms for 5D bioimaging data, together with unique automation/scripting capabilities (notably via its graphical programming interface) and tight integration with existing software (e.g. ImageJ, Matlab, Micro-Manager).

On day 3, we will cover time series processing and cell tracking using TrackMate. Additionally, in the afternoon we will run a study design and data clinic (sign up will be required) for participants that wish to discuss their experiments.

A timetable 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.

Microscopy experiments have proven to be a powerful means of generating information-rich data for biological applications. From small-scale microscopy experiments to time-lapse movies and high-throughput screens, automatic image analysis is more objective and quantitative and less tedious than visual inspection.

This course will introduce users to the free open-source image analysis program CellProfiler and its companion data exploration program CellProfiler Analyst. We will show how CellProfiler can be used to analyse a variety of types of imaging experiments. We will also briefly discuss the basic principles of supervised machine learning with CellProfiler Analyst in order to score complex and subtle phenotypes.

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.

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 develop two major areas of work, which are further subdivided into projects. The major areas are the Core Bioinformatics and Computational Pipelines, which created and developed the Target Validation Platform, and Experimental projects, which combine large-scale genomics with statistical and computational techniques to identify and validate the causal links between targets, pathways and diseases. The Target Validation Platform integrates comprehensive datasets from a myriad of renowned public databases, such as UniProt, ChEMBL, Ensembl, NHGRI-EBI GWAS, EuropePMC, COSMIC, amongst others, and will incorporate the newly generated data by our Experimental projects in Oncology, Immunity, Inflammation and other areas for free and open access.

The purpose of this half-day workshop is to acquaint participants with the Open Targets consortium. We will highlight the experimental projects in the Consortium but focus on the Target Validation Platform to introduce the tools for visualisation and interpretation of gene-disease associations and target validation. By the end of this half-day workshop, users will be able to carry out effective searches of data, and 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 your interest by linking here.