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Bioinformatics Training

Bioinformatics course timetable

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Mon 29 May – Tue 12 Sep

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June 2017

Thu 8
Bacterial Genome Assembly and Annotation in Galaxy new [Places] 09:30 - 17:30 Bioinformatics Training Room, Craik-Marshall Building, Downing Site

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

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

This session will include an introduction to the Galaxy platform.

This event is co-organized with EMBL-ABR and the Genomics Virtual Lab.

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

Mon 12
An Introduction to Solving Biological Problems with Python (1 of 2) [Places] 09:30 - 17:00 Bioinformatics Training Room, Craik-Marshall Building, Downing Site

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 and customize more complex code to fit their needs.

Course materials are available here.

Please note that the content of this course has recently been updated. This course now mostly focuses on core concepts including Python syntax, data structures and reading/writing files. Functions and modules are now the focus of a new 1-day course, Working with Python: functions and modules.

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

Tue 13
An Introduction to Solving Biological Problems with Python (2 of 2) [Places] 09:30 - 17:00 Bioinformatics Training Room, Craik-Marshall Building, Downing Site

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 and customize more complex code to fit their needs.

Course materials are available here.

Please note that the content of this course has recently been updated. This course now mostly focuses on core concepts including Python syntax, data structures and reading/writing files. Functions and modules are now the focus of a new 1-day course, Working with Python: functions and modules.

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

Wed 14
Analysis of DNA Methylation using Sequencing [Full] 09:30 - 17:30 Bioinformatics Training Room, Craik-Marshall Building, Downing Site

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.

Thu 15
An Introduction to Solving Biological Problems with R (1 of 2) [Full] 09:30 - 17:30 Bioinformatics Training Room, Craik-Marshall Building, Downing Site

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.

The course website providing links to the course materials is 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.

Fri 16
An Introduction to Solving Biological Problems with R (2 of 2) [Full] 09:30 - 17:30 Bioinformatics Training Room, Craik-Marshall Building, Downing Site

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.

The course website providing links to the course materials is 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.

Mon 19
An introduction to metabolomics and its application in life-sciences (1 of 2) [Full] 09:30 - 17:00 Bioinformatics Training Room, Craik-Marshall Building, Downing Site

The goal of metabolomics is to identify and quantify the complete biochemical composition of a biological sample. With the increase in genomic, transcriptomic and proteomic information there is a growing need to understand the metabolic phenotype that these genes and proteins ultimately control.

The aim of this course is to provide an overview of metabolomics and its applications in life sciences, clinical and environmental settings. Over 2 days we will introduce different techniques used to extract metabolites and analyse samples to collect metabolomic data (such as HPLC or GC-based MS and NMR), present how to analyse such data, how to identify metabolites using online databases and how to map the metabolomic data to metabolic pathways.

The course content will predominantly be based on analysing samples from model plant species such as Arabidopsis thaliana but the procedures are transferable to all other organisms, including clinical and environmental settings.

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

Tue 20
An introduction to metabolomics and its application in life-sciences (2 of 2) [Full] 09:30 - 18:00 Bioinformatics Training Room, Craik-Marshall Building, Downing Site

The goal of metabolomics is to identify and quantify the complete biochemical composition of a biological sample. With the increase in genomic, transcriptomic and proteomic information there is a growing need to understand the metabolic phenotype that these genes and proteins ultimately control.

The aim of this course is to provide an overview of metabolomics and its applications in life sciences, clinical and environmental settings. Over 2 days we will introduce different techniques used to extract metabolites and analyse samples to collect metabolomic data (such as HPLC or GC-based MS and NMR), present how to analyse such data, how to identify metabolites using online databases and how to map the metabolomic data to metabolic pathways.

The course content will predominantly be based on analysing samples from model plant species such as Arabidopsis thaliana but the procedures are transferable to all other organisms, including clinical and environmental settings.

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

Wed 21
Working with Python: functions and modules [Places] 09:30 - 17:30 Bioinformatics Training Room, Craik-Marshall Building, Downing Site

This course will cover concepts and strategies for working more effectively with Python with the aim of writing reusable code. In the morning session, we will briefly go over the basic syntax, data structures and control statements. This will be followed by an introduction to writing user-defined functions. We will finish the course by looking into how to incorporate existing python modules and packages into your programs as well as writing you own modules.

Course materials can be found here.

Note: this one-day course is the continuation of the Introduction to Solving Biological Problems with Python; participants are expected to have attended the introductory Python course and/or have acquired some working knowledge of Python. This course is also open to Python beginners who are already fluent in other programming languages as this will help them to quickly get started in Python.

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

Thu 22
Introduction to RNA-seq and ChIP-seq data analysis (1 of 2) [Full] 09:30 - 17:30 Bioinformatics Training Room, Craik-Marshall Building, Downing Site

The aim of this course is to familiarize the participants with the primary analysis of datasets generated through two popular high-throughput 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.

Fri 23
Introduction to RNA-seq and ChIP-seq data analysis (2 of 2) [Full] 09:30 - 17:30 Bioinformatics Training Room, Craik-Marshall Building, Downing Site

The aim of this course is to familiarize the participants with the primary analysis of datasets generated through two popular high-throughput 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.

Mon 26
Image Analysis for Biologists (1 of 3) [Full] 09:30 - 17:30 Bioinformatics Training Room, Craik-Marshall Building, Downing Site

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, visualisation, 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.

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.

Tue 27
Image Analysis for Biologists (2 of 3) [Full] 09:30 - 17:30 Bioinformatics Training Room, Craik-Marshall Building, Downing Site

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, visualisation, 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.

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.

Wed 28
Image Analysis for Biologists (3 of 3) [Full] 09:30 - 16:00 Bioinformatics Training Room, Craik-Marshall Building, Downing Site

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, visualisation, 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.

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.

July 2017

Mon 10
Protein Structure Analysis new (1 of 2) [Full] 09:30 - 17:30 University Information Services, Titan Teaching Room 2, New Museums Site

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.

Tue 11
Protein Structure Analysis new (2 of 2) [Full] 09:30 - 17:30 University Information Services, Titan Teaching Room 2, New Museums Site

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.

Wed 12
Variant Analysis with GATK (1 of 3) [Full] 09:30 - 17:30 University Information Services, Titan Teaching Room 2, New Museums Site

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 germline 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, and we demonstrate the use of pipelining tools to assemble and execute GATK workflows.

The workshop is composed of one day of lectures and two days of hands­on training, structured as follows. Day 1: theory and application of the Best Practices for Variant Discovery in high­throughput sequencing data. Day 2 and the morning of Day 3: hands­on exercises on 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. Day 3 afternoon: hands-on exercises on how to write workflow scripts using WDL, the Broad's new Workflow Description Language, and to execute these workflows locally as well as through a publicly accessible cloud-based service.

Please note that this workshop is focused on human data analysis. The majority of the materials presented does apply equally to non­human 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.

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.

Thu 13
Variant Analysis with GATK (2 of 3) [Full] 09:30 - 17:00 University Information Services, Titan Teaching Room 2, New Museums Site

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 germline 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, and we demonstrate the use of pipelining tools to assemble and execute GATK workflows.

The workshop is composed of one day of lectures and two days of hands­on training, structured as follows. Day 1: theory and application of the Best Practices for Variant Discovery in high­throughput sequencing data. Day 2 and the morning of Day 3: hands­on exercises on 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. Day 3 afternoon: hands-on exercises on how to write workflow scripts using WDL, the Broad's new Workflow Description Language, and to execute these workflows locally as well as through a publicly accessible cloud-based service.

Please note that this workshop is focused on human data analysis. The majority of the materials presented does apply equally to non­human 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.

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.

Fri 14
Variant Analysis with GATK (3 of 3) [Full] 09:30 - 17:00 University Information Services, Titan Teaching Room 2, New Museums Site

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 germline 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, and we demonstrate the use of pipelining tools to assemble and execute GATK workflows.

The workshop is composed of one day of lectures and two days of hands­on training, structured as follows. Day 1: theory and application of the Best Practices for Variant Discovery in high­throughput sequencing data. Day 2 and the morning of Day 3: hands­on exercises on 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. Day 3 afternoon: hands-on exercises on how to write workflow scripts using WDL, the Broad's new Workflow Description Language, and to execute these workflows locally as well as through a publicly accessible cloud-based service.

Please note that this workshop is focused on human data analysis. The majority of the materials presented does apply equally to non­human 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.

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.

August 2017

Wed 30
Basic statistics and data handling new (1 of 3) [Places] 09:30 - 17:30 Bioinformatics Training Room, Craik-Marshall Building, Downing Site

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

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

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

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

Course materials are available here.

This event is supported by a BBSRC Strategic Training Awards for Research Skills (STARS) grant.

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

Thu 31
Basic statistics and data handling new (2 of 3) [Places] 09:30 - 17:30 Bioinformatics Training Room, Craik-Marshall Building, Downing Site

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

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

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

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

Course materials are available here.

This event is supported by a BBSRC Strategic Training Awards for Research Skills (STARS) grant.

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

September 2017

Fri 1
Basic statistics and data handling new (3 of 3) [Places] 09:30 - 17:30 Bioinformatics Training Room, Craik-Marshall Building, Downing Site

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

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

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

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

Course materials are available here.

This event is supported by a BBSRC Strategic Training Awards for Research Skills (STARS) grant.

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

Wed 6
Data Analysis and Visualisation in R [Places] 09:30 - 17:30 Bioinformatics Training Room, Craik-Marshall Building, Downing Site

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.

Mon 11
Data Carpentry (1 of 2) [Places] 09:30 - 17:30 Bioinformatics Training Room, Craik-Marshall Building, Downing Site

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.

This course is organized in collaboration with ElixirUK and the Software Sustainability Institute.

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

Tue 12
Data Carpentry (2 of 2) [Places] 09:30 - 17:30 Bioinformatics Training Room, Craik-Marshall Building, Downing Site

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.

This course is organized in collaboration with ElixirUK and the Software Sustainability Institute.

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