Bioinformatics course timetable
July 2017
| Mon 10 |
Protein Structure Analysis
Finished
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
Finished
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
Finished
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. |
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How much data would you lose if your laptop was stolen? Have you ever emailed your colleague a file named 'final_final_versionEDITED'? Have you ever struggled to import your spreadsheets into R? As a researcher, you will encounter research data in many forms, ranging from measurements, numbers and images to documents and publications. Whether you create, receive or collect data, you will certainly need to organise it at some stage of your project. This workshop will provide an overview of some basic principles on how we can work with data more effectively. We will discuss the best practices for research data management and organisation so that our research is auditable and reproducible by ourselves, and others, in the future. 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. |
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| Thu 13 |
Variant Analysis with GATK
Finished
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
Finished
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. |
| Wed 19 |
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| Mon 24 |
CRUK Summer School
Finished
CRUK Summer School Event posted for Administration purposes only |
| Tue 25 |
CRUK Summer School
Finished
CRUK Summer School Event posted for Administration purposes only |
| Wed 26 |
CRUK Summer School
Finished
CRUK Summer School Event posted for Administration purposes only |
| Thu 27 |
CRUK Summer School
Finished
CRUK Summer School Event posted for Administration purposes only |
| Fri 28 |
CRUK Summer School
Finished
CRUK Summer School Event posted for Administration purposes only |
August 2017
| Wed 30 |
Basic statistics and data handling
Finished
This three day course is intended to open doors to applying statistics - whether directly increasing skills and personally undertaking analyses, or by expanding knowledge towards identifying collaborators. The end goal is to drive confident engagement with data analysis and further training - increasing the quality and reliability of interpretation, and putting that interpretation and subsequent presentation into the hands of the researcher. Each day of the course will deliver a mixture of lectures, workshops and hands-on practicals – and will focus on the following specific elements. Day 1 focuses on basic approaches and the computer skills required to do downstream analysis. Covering: Basic skills for data manipulation in R. How to prepare your data effectively. Principles of experimental design and how this influences analysis. On day 2, participants will explore the core concepts of statistics – so that they can begin to see how they can be applied to their own work, and to also help with better critical evaluation of the work of others. Covering: Basic statistics concepts and practice: power, variability, false discovery, t-test, effect size, simulations to understand what a p-value means. On day 3 we will continue to explore core concepts of statistics, focusing on linear regression and multiple testing correction. Course materials are available here. This event is supported by the BBSRC Strategic Training Awards for Research Skills (STARS) grant (BB/P022766/1). Please note that if you are not eligible for a University of Cambridge Raven account you will need to book by linking here. |
| Thu 31 |
Basic statistics and data handling
Finished
This three day course is intended to open doors to applying statistics - whether directly increasing skills and personally undertaking analyses, or by expanding knowledge towards identifying collaborators. The end goal is to drive confident engagement with data analysis and further training - increasing the quality and reliability of interpretation, and putting that interpretation and subsequent presentation into the hands of the researcher. Each day of the course will deliver a mixture of lectures, workshops and hands-on practicals – and will focus on the following specific elements. Day 1 focuses on basic approaches and the computer skills required to do downstream analysis. Covering: Basic skills for data manipulation in R. How to prepare your data effectively. Principles of experimental design and how this influences analysis. On day 2, participants will explore the core concepts of statistics – so that they can begin to see how they can be applied to their own work, and to also help with better critical evaluation of the work of others. Covering: Basic statistics concepts and practice: power, variability, false discovery, t-test, effect size, simulations to understand what a p-value means. On day 3 we will continue to explore core concepts of statistics, focusing on linear regression and multiple testing correction. Course materials are available here. This event is supported by the BBSRC Strategic Training Awards for Research Skills (STARS) grant (BB/P022766/1). Please note that if you are not eligible for a University of Cambridge Raven account you will need to book by linking here. |
September 2017
| Fri 1 |
Basic statistics and data handling
Finished
This three day course is intended to open doors to applying statistics - whether directly increasing skills and personally undertaking analyses, or by expanding knowledge towards identifying collaborators. The end goal is to drive confident engagement with data analysis and further training - increasing the quality and reliability of interpretation, and putting that interpretation and subsequent presentation into the hands of the researcher. Each day of the course will deliver a mixture of lectures, workshops and hands-on practicals – and will focus on the following specific elements. Day 1 focuses on basic approaches and the computer skills required to do downstream analysis. Covering: Basic skills for data manipulation in R. How to prepare your data effectively. Principles of experimental design and how this influences analysis. On day 2, participants will explore the core concepts of statistics – so that they can begin to see how they can be applied to their own work, and to also help with better critical evaluation of the work of others. Covering: Basic statistics concepts and practice: power, variability, false discovery, t-test, effect size, simulations to understand what a p-value means. On day 3 we will continue to explore core concepts of statistics, focusing on linear regression and multiple testing correction. Course materials are available here. This event is supported by the BBSRC Strategic Training Awards for Research Skills (STARS) grant (BB/P022766/1). Please note that if you are not eligible for a University of Cambridge Raven account you will need to book by linking here. |
| Mon 4 |
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. |
| Tue 5 |
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. |
| Wed 6 |
Data Analysis and Visualisation in R
Finished
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. |
| Fri 8 |
Using the Ensembl Genome Browser
Finished
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. 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 11 |
Data Carpentry
Finished
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. Course materials can be found here. 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
Finished
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. Course materials can be found here. 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. |
| Wed 13 |
Statistical Analysis using R
Finished
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. |
| Thu 14 |
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. |
| Fri 15 |
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. |
| Thu 28 |
Machine learning gives computers the ability to learn without being explicitly programmed. It encompasses a broad range of approaches to data analysis with applicability across the biological sciences. Lectures will introduce commonly used algorithms and provide insight into their theoretical underpinnings. In the practicals students will apply these algorithms to real biological data-sets using the R language and environment. 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. |