Bioinformatics course timetable
July 2019
Mon 8 |
Variant Discovery with GATK4
Finished
This workshop will focus on the core steps involved in calling germline short variants, somatic short variants, and copy number alterations with the Broad’s Genome Analysis Toolkit (GATK), using “Best Practices” developed by the GATK methods development team. A team of methods developers and instructors from the Data Sciences Platform at Broad will give talks explaining the rationale, theory, and real-world applications of the GATK Best Practices. You will learn why each step is essential to the variant-calling process, what key operations are 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. If you are an experienced GATK user, you will gain a deeper understanding of how the GATK works under-the-hood and how to improve your results further, especially with respect to the latest innovations.
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 hands-on GATK tutorials in this workshop will be conducted on Terra, a new platform developed at Broad in collaboration with Verily Life Sciences for accessing data, running analysis tools and collaborating securely and seamlessly. The training room is located on the first floor and there is currently no wheelchair or level access available to this level. 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. |
Tue 9 |
Variant Discovery with GATK4
Finished
This workshop will focus on the core steps involved in calling germline short variants, somatic short variants, and copy number alterations with the Broad’s Genome Analysis Toolkit (GATK), using “Best Practices” developed by the GATK methods development team. A team of methods developers and instructors from the Data Sciences Platform at Broad will give talks explaining the rationale, theory, and real-world applications of the GATK Best Practices. You will learn why each step is essential to the variant-calling process, what key operations are 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. If you are an experienced GATK user, you will gain a deeper understanding of how the GATK works under-the-hood and how to improve your results further, especially with respect to the latest innovations.
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 hands-on GATK tutorials in this workshop will be conducted on Terra, a new platform developed at Broad in collaboration with Verily Life Sciences for accessing data, running analysis tools and collaborating securely and seamlessly. The training room is located on the first floor and there is currently no wheelchair or level access available to this level. 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 10 |
Variant Discovery with GATK4
Finished
This workshop will focus on the core steps involved in calling germline short variants, somatic short variants, and copy number alterations with the Broad’s Genome Analysis Toolkit (GATK), using “Best Practices” developed by the GATK methods development team. A team of methods developers and instructors from the Data Sciences Platform at Broad will give talks explaining the rationale, theory, and real-world applications of the GATK Best Practices. You will learn why each step is essential to the variant-calling process, what key operations are 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. If you are an experienced GATK user, you will gain a deeper understanding of how the GATK works under-the-hood and how to improve your results further, especially with respect to the latest innovations.
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 hands-on GATK tutorials in this workshop will be conducted on Terra, a new platform developed at Broad in collaboration with Verily Life Sciences for accessing data, running analysis tools and collaborating securely and seamlessly. The training room is located on the first floor and there is currently no wheelchair or level access available to this level. 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 11 |
Variant Discovery with GATK4
Finished
This workshop will focus on the core steps involved in calling germline short variants, somatic short variants, and copy number alterations with the Broad’s Genome Analysis Toolkit (GATK), using “Best Practices” developed by the GATK methods development team. A team of methods developers and instructors from the Data Sciences Platform at Broad will give talks explaining the rationale, theory, and real-world applications of the GATK Best Practices. You will learn why each step is essential to the variant-calling process, what key operations are 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. If you are an experienced GATK user, you will gain a deeper understanding of how the GATK works under-the-hood and how to improve your results further, especially with respect to the latest innovations.
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 hands-on GATK tutorials in this workshop will be conducted on Terra, a new platform developed at Broad in collaboration with Verily Life Sciences for accessing data, running analysis tools and collaborating securely and seamlessly. The training room is located on the first floor and there is currently no wheelchair or level access available to this level. 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 12 |
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. This event is supported by the BBSRC Strategic Training Awards for Research Skills (STARS) grant (BB/P022766/1). The training room is located on the first floor and there is currently no wheelchair or level access available to this level. 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 26 |
CRUK: Image Analysis with Fiji
Finished
Fiji/ImageJ is a popular open-source image analysis software application. This course will briefly cover introductory aspects of image processing and analysis theory, but will focus on practical sessions where participants will gain hands on experience with Fiji. This course is run by the CRUK CI Light microscopy core facility. 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. |
September 2019
Mon 2 |
Analysis of bulk RNA-seq data
Finished
The aim of this course is to familiarize the participants with the primary analysis of RNA-seq data. This course starts with a brief introduction to RNA-seq and discusses quality control issues. Next, we will present the alignment step, quantification of expression and differential expression analysis. For downstream analysis we will focus on tools available through the Bioconductor project for manipulating and analysing bulk RNA-seq. The training room is located on the first floor and there is currently no wheelchair or level access available to this level. 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 3 |
Analysis of bulk RNA-seq data
Finished
The aim of this course is to familiarize the participants with the primary analysis of RNA-seq data. This course starts with a brief introduction to RNA-seq and discusses quality control issues. Next, we will present the alignment step, quantification of expression and differential expression analysis. For downstream analysis we will focus on tools available through the Bioconductor project for manipulating and analysing bulk RNA-seq. The training room is located on the first floor and there is currently no wheelchair or level access available to this level. 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 4 |
Analysis of bulk RNA-seq data
Finished
The aim of this course is to familiarize the participants with the primary analysis of RNA-seq data. This course starts with a brief introduction to RNA-seq and discusses quality control issues. Next, we will present the alignment step, quantification of expression and differential expression analysis. For downstream analysis we will focus on tools available through the Bioconductor project for manipulating and analysing bulk RNA-seq. The training room is located on the first floor and there is currently no wheelchair or level access available to this level. 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. |
Thu 5 |
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. Concepts and strategies for working more effectively with Python are now the focus of a new 2-days course, Data Science in Python. The training room is located on the first floor and there is currently no wheelchair or level access available to this level. 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 6 |
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. Concepts and strategies for working more effectively with Python are now the focus of a new 2-days course, Data Science in Python. The training room is located on the first floor and there is currently no wheelchair or level access available to this level. 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 9 |
Introduction to R for Biologists
Finished
R is one of the leading programming languages in Data Science. It is widely used to perform statistics, machine learning, visualisations and data analyses. It is an open source programming language so all the software we will use in the course is free. This course is an introduction to R designed for participants with no programming experience. We will start from scratch by introducing how to start programming in R and progress our way and learn how to read and write to files, manipulate data and visualise it by creating different plots - all the fundamental tasks you need to get you started analysing your data. During the course we will be working with one of the most popular packages in R; tidyverse that will allow you to manipulate your data effectively and visualise it to a publication level standard. The training room is located on the first floor and there is currently no wheelchair or level access available to this level. 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 10 |
Introduction to R for Biologists
Finished
R is one of the leading programming languages in Data Science. It is widely used to perform statistics, machine learning, visualisations and data analyses. It is an open source programming language so all the software we will use in the course is free. This course is an introduction to R designed for participants with no programming experience. We will start from scratch by introducing how to start programming in R and progress our way and learn how to read and write to files, manipulate data and visualise it by creating different plots - all the fundamental tasks you need to get you started analysing your data. During the course we will be working with one of the most popular packages in R; tidyverse that will allow you to manipulate your data effectively and visualise it to a publication level standard. The training room is located on the first floor and there is currently no wheelchair or level access available to this level. 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 16 |
The aim of this workshop is to provide principal investigators with an introduction to the challenges of working with biological data and to the best practices, and tools, needed to perform bioinformatics research effectively and reproducibly. On day 1, we will cover the importance of experimental design, discuss the challenges associated with (i) the analysis of high-throughput sequencing data (utilising RNA-seq as a working example) and (ii) the application of machine learning algorithms, as well as issues relating to reusability and reproducibility. On day 2, we will put into practice concepts from day 1, running a RNA-seq data analysis pipeline, going from raw reads through differential expression analysis and the interpretation of downstream analysis results. Challenges encountered at each step of the analytical pipeline will be discussed. Please note that day 2 is optional. The training room is located on the first floor and there is currently no wheelchair or level access available to this level. 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 17 |
The aim of this workshop is to provide principal investigators with an introduction to the challenges of working with biological data and to the best practices, and tools, needed to perform bioinformatics research effectively and reproducibly. On day 1, we will cover the importance of experimental design, discuss the challenges associated with (i) the analysis of high-throughput sequencing data (utilising RNA-seq as a working example) and (ii) the application of machine learning algorithms, as well as issues relating to reusability and reproducibility. On day 2, we will put into practice concepts from day 1, running a RNA-seq data analysis pipeline, going from raw reads through differential expression analysis and the interpretation of downstream analysis results. Challenges encountered at each step of the analytical pipeline will be discussed. Please note that day 2 is optional. The training room is located on the first floor and there is currently no wheelchair or level access available to this level. 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. |
Thu 19 |
Statistics for Biologists in R
Finished
This course is intended to provide a strong foundation in practical statistics and data analysis using the R software environment. The underlying philosophy of the course is to treat statistics as a practical skill rather than as a theoretical subject and as such the course focuses on methods for addressing real-life issues in the biological sciences using the R software package. In this course we explore classical statistical analysis techniques starting with simple hypothesis testing and building up to multiple linear regression. The focus of the course is on practical implementation of these techniques and developing robust statistical analysis skills rather than on the underlying statistical theory. After the course you should feel confident to be able to select and implement common statistical techniques using R and moreover know when, and when not, to apply these techniques. This event is supported by the BBSRC Strategic Training Awards for Research Skills (STARS) grant (BB/P022766/1). The training room is located on the first floor and there is currently no wheelchair or level access available to this level. 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 20 |
Statistics for Biologists in R
Finished
This course is intended to provide a strong foundation in practical statistics and data analysis using the R software environment. The underlying philosophy of the course is to treat statistics as a practical skill rather than as a theoretical subject and as such the course focuses on methods for addressing real-life issues in the biological sciences using the R software package. In this course we explore classical statistical analysis techniques starting with simple hypothesis testing and building up to multiple linear regression. The focus of the course is on practical implementation of these techniques and developing robust statistical analysis skills rather than on the underlying statistical theory. After the course you should feel confident to be able to select and implement common statistical techniques using R and moreover know when, and when not, to apply these techniques. This event is supported by the BBSRC Strategic Training Awards for Research Skills (STARS) grant (BB/P022766/1). The training room is located on the first floor and there is currently no wheelchair or level access available to this level. 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 23 |
THIS EVENT IS NOW FULLY BOOKED! This Autumn School aims to familiarise biomedical students and researchers with principles of Data Science. Focusing on utilising machine learning algorithms to handle biomedical data, it will cover: effects of experimental design, data readiness, pipeline implementations, machine learning in Python, and related statistics, as well as Gaussian Process models. Providing practical experience in the implementation of machine learning methods relevant to biomedical applications, including Gaussian processes, we will illustrate best practices that should be adopted in order to enable reproducibility in any data science application. This event is sponsored by Cambridge Big Data. The training room is located on the first floor and there is currently no wheelchair or level access available to this level. 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 24 |
THIS EVENT IS NOW FULLY BOOKED! This Autumn School aims to familiarise biomedical students and researchers with principles of Data Science. Focusing on utilising machine learning algorithms to handle biomedical data, it will cover: effects of experimental design, data readiness, pipeline implementations, machine learning in Python, and related statistics, as well as Gaussian Process models. Providing practical experience in the implementation of machine learning methods relevant to biomedical applications, including Gaussian processes, we will illustrate best practices that should be adopted in order to enable reproducibility in any data science application. This event is sponsored by Cambridge Big Data. The training room is located on the first floor and there is currently no wheelchair or level access available to this level. 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 25 |
THIS EVENT IS NOW FULLY BOOKED! This Autumn School aims to familiarise biomedical students and researchers with principles of Data Science. Focusing on utilising machine learning algorithms to handle biomedical data, it will cover: effects of experimental design, data readiness, pipeline implementations, machine learning in Python, and related statistics, as well as Gaussian Process models. Providing practical experience in the implementation of machine learning methods relevant to biomedical applications, including Gaussian processes, we will illustrate best practices that should be adopted in order to enable reproducibility in any data science application. This event is sponsored by Cambridge Big Data. The training room is located on the first floor and there is currently no wheelchair or level access available to this level. 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. |
Thu 26 |
THIS EVENT IS NOW FULLY BOOKED! This Autumn School aims to familiarise biomedical students and researchers with principles of Data Science. Focusing on utilising machine learning algorithms to handle biomedical data, it will cover: effects of experimental design, data readiness, pipeline implementations, machine learning in Python, and related statistics, as well as Gaussian Process models. Providing practical experience in the implementation of machine learning methods relevant to biomedical applications, including Gaussian processes, we will illustrate best practices that should be adopted in order to enable reproducibility in any data science application. This event is sponsored by Cambridge Big Data. The training room is located on the first floor and there is currently no wheelchair or level access available to this level. 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 30 |
Using the Linux operating system and the bash command line interface, we will demonstrate the basic structure of the UNIX operating system and how we can interact with it using a basic set of commands. Applying this, we will learn how to navigate the filesystem, manipulate text-based data and structure simple pipelines out of these commands. Building on this foundation, the course will use a bioinformatics example to demonstrate how the skills learnt can be applied to connecting to external resources/servers, installing specialist tools and ultimately combining commands into scripts for automation and reproducibility. This course is targeted at participants with no prior experience working with UNIX-like systems (OSX, Linux) or command line interfaces. The training room is located on the first floor and there is currently no wheelchair or level access available to this level. 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. |
October 2019
Tue 1 |
Reproducible Research with R
Finished
This course introduces concepts about reproducibility that can be used when you are programming in R. We will explore how to create notebooks - a way to integrate your R analyses into reports using Rmarkdown. The course also introduces the concept of version control. We will learn how to create a repository on GitHub and how to work together on the same project collaboratively without creating conflicting versions of files. The training room is located on the first floor and there is currently no wheelchair or level access available to this level. 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 2 |
An Introduction to Machine Learning
Finished
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. Please be aware that the course syllabus is currently being updated following feedback from the last event; therefore the agenda below will be subjected to changes. The training room is located on the first floor and there is currently no wheelchair or level access available to this level. 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. |
Thu 3 |
An Introduction to Machine Learning
Finished
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. Please be aware that the course syllabus is currently being updated following feedback from the last event; therefore the agenda below will be subjected to changes. The training room is located on the first floor and there is currently no wheelchair or level access available to this level. 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. |