Bioinformatics 2017
(Wed 18 Jan 2017 - Thu 14 Dec 2017)
[ Back to start of the programme ]
June 2017
| Thu 15 |
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 |
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 |
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 |
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 |
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 |
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 |
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
Finished
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. In the afternoon, we will present the Image Data Resource, an added-value platform that combines data from multiple independent imaging experiments and imaging modalities and integrates them into a single resource for reanalysis in a convenient, scalable form. 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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This course provides a practical introduction 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, with the aim of conveying information in an effective manner. It draws on principles of visual design and provides strategies to make informed choices of figure elements and composition, and to facilitate the communication of complex results. The course also covers the practical aspects of compositing and editing of final figures and the allowable manipulation of bitmap images. The course introduces the use of different open source software packages for editing images to achieve professional quality and is illustrated with example figures adapted from common analysis tools. Please note: The material provided in this course is partially based on the course Introduction to Scientific Figure Design, provided by Babraham Bioinformatics. 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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| Tue 27 |
Image Analysis for Biologists
Finished
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. In the afternoon, we will present the Image Data Resource, an added-value platform that combines data from multiple independent imaging experiments and imaging modalities and integrates them into a single resource for reanalysis in a convenient, scalable form. 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
Finished
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. In the afternoon, we will present the Image Data Resource, an added-value platform that combines data from multiple independent imaging experiments and imaging modalities and integrates them into a single resource for reanalysis in a convenient, scalable form. 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 3 |
This event will consist of two parts. The first part of the workshop 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). It will be based on the EXCELERATE Train-the-Trainer (TtT) course materials and content will be tailored to trainers that are involved in teaching bioinformatics to clinical audiences. The second part of the workshop will focus on "Best practices in clinical bioinformatics training", providing an opportunity for people already involved in this kind of training, or in the process of developing it, to come together and exchange best practice/experiences. Participants will include training providers of the Health Education England’s MSc in Genomics Medicine from several UK Universities as well as other providers active in this area, from around Europe and beyond. This event is co-sponsored by ELIXIR-EXCELERATE and Health Education England (HEE). |
| Tue 4 |
This event will consist of two parts. The first part of the workshop 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). It will be based on the EXCELERATE Train-the-Trainer (TtT) course materials and content will be tailored to trainers that are involved in teaching bioinformatics to clinical audiences. The second part of the workshop will focus on "Best practices in clinical bioinformatics training", providing an opportunity for people already involved in this kind of training, or in the process of developing it, to come together and exchange best practice/experiences. Participants will include training providers of the Health Education England’s MSc in Genomics Medicine from several UK Universities as well as other providers active in this area, from around Europe and beyond. This event is co-sponsored by ELIXIR-EXCELERATE and Health Education England (HEE). |
| Wed 5 |
This event will consist of two parts. The first part of the workshop 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). It will be based on the EXCELERATE Train-the-Trainer (TtT) course materials and content will be tailored to trainers that are involved in teaching bioinformatics to clinical audiences. The second part of the workshop will focus on "Best practices in clinical bioinformatics training", providing an opportunity for people already involved in this kind of training, or in the process of developing it, to come together and exchange best practice/experiences. Participants will include training providers of the Health Education England’s MSc in Genomics Medicine from several UK Universities as well as other providers active in this area, from around Europe and beyond. This event is co-sponsored by ELIXIR-EXCELERATE and Health Education England (HEE). |
| 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 |