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Bioinformatics 2022-23

Programme of events provided by Bioinformatics
(Mon 12 Sep 2022 - Thu 20 Jul 2023)

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Mon 12 Sep 2022 – Mon 7 Nov 2022

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September 2022

Mon 12
Analysis of single cell RNA-seq data (IN PERSON) (1 of 3) Finished 09:30 - 17:30 Bioinformatics Training Room, Craik-Marshall Building

Recent technological advances have made it possible to obtain genome-wide transcriptome data from single cells using high-throughput sequencing (scRNA-seq). Even though scRNA-seq makes it possible to address problems that are intractable with bulk RNA-seq data, analysing scRNA-seq is also more challenging.

In this course we will be surveying the existing problems as well as the available computational and statistical frameworks available for the analysis of scRNA-seq.

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.

Introduction to Python for Biologists (ONLINE LIVE TRAINING) (1 of 2) Finished 09:30 - 17:30 Bioinformatics Training Facility - Online LIVE Training

This course provides a practical introduction to the writing of Python programs for the complete novice. Participants are lead through the core concepts of Python including Python syntax, data structures and reading/writing files. These are illustrated by a series of example programs. Upon completion of the course, participants will be able to write simple Python programs.

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 13
Introduction to R for Biologists (ONLINE) (1 of 2) Finished 09:30 - 17:30 Bioinformatics Training Facility - Online LIVE Training

PLEASE BE AWARE: This event is run online, if you wish to book for the in-person version, please click here.

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.

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.

Introduction to R for Biologists (IN PERSON) (1 of 2) Finished 09:30 - 17:30 Bioinformatics Training Room, Craik-Marshall Building

PLEASE BE AWARE: This event is run in-person, if you wish to book for the online version, please click here.

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.

Wed 14
Introduction to R for Biologists (ONLINE) (2 of 2) Finished 09:30 - 17:30 Bioinformatics Training Facility - Online LIVE Training

PLEASE BE AWARE: This event is run online, if you wish to book for the in-person version, please click here.

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.

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.

Introduction to R for Biologists (IN PERSON) (2 of 2) Finished 09:30 - 17:30 Bioinformatics Training Room, Craik-Marshall Building

PLEASE BE AWARE: This event is run in-person, if you wish to book for the online version, please click here.

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.

Thu 15
Using the Ensembl Genome Browser (CANCELLED) CANCELLED 09:30 - 17:30 Bioinformatics Training Facility - Online LIVE Training

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.

Fri 16
Ensembl REST API workshop (CANCELLED) CANCELLED 09:30 - 16:30 Bioinformatics Training Facility - Online LIVE Training

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

This workshop is aimed at researchers and developers interested in exploring Ensembl beyond the website. The workshop covers how to use the Ensembl REST APIs, including understanding the major endpoints and how to write scripts to call them.

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 20
Analysis of single cell RNA-seq data (IN PERSON) (2 of 3) Finished 09:30 - 17:30 Bioinformatics Training Room, Craik-Marshall Building

Recent technological advances have made it possible to obtain genome-wide transcriptome data from single cells using high-throughput sequencing (scRNA-seq). Even though scRNA-seq makes it possible to address problems that are intractable with bulk RNA-seq data, analysing scRNA-seq is also more challenging.

In this course we will be surveying the existing problems as well as the available computational and statistical frameworks available for the analysis of scRNA-seq.

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.

Introduction to Python for Biologists (ONLINE LIVE TRAINING) (2 of 2) Finished 09:30 - 17:30 Bioinformatics Training Facility - Online LIVE Training

This course provides a practical introduction to the writing of Python programs for the complete novice. Participants are lead through the core concepts of Python including Python syntax, data structures and reading/writing files. These are illustrated by a series of example programs. Upon completion of the course, participants will be able to write simple Python programs.

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
Analysis of single cell RNA-seq data (IN PERSON) (3 of 3) Finished 09:30 - 17:30 Bioinformatics Training Room, Craik-Marshall Building

Recent technological advances have made it possible to obtain genome-wide transcriptome data from single cells using high-throughput sequencing (scRNA-seq). Even though scRNA-seq makes it possible to address problems that are intractable with bulk RNA-seq data, analysing scRNA-seq is also more challenging.

In this course we will be surveying the existing problems as well as the available computational and statistical frameworks available for the analysis of scRNA-seq.

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 28
Core Statistics using R (ONLINE) (1 of 3) Finished 09:30 - 17:00 Bioinformatics Training Facility - Online LIVE Training

PLEASE BE AWARE: This event is run online, if you wish to book for the in-person version, please click here.

This award winning virtually delivered 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.

There are three core goals for this course:

  1. Use R confidently for statistics and data analysis
  2. Be able to analyse datasets using standard statistical techniques
  3. Know which tests are and are not appropriate

R is an open source programming language so all of the software we will use in the course is free.

In this course, we explore classical statistical analysis techniques starting with simple hypothesis testing and building up to linear models and power analyses. 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.

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.

Core Statistics using R (IN PERSON) (1 of 3) Finished 09:30 - 17:00 Bioinformatics Training Room, Craik-Marshall Building

PLEASE BE AWARE: This event is run in-person, if you wish to book for the online version, please click here.

This award winning virtually delivered 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.

There are three core goals for this course:

  1. Use R confidently for statistics and data analysis
  2. Be able to analyse datasets using standard statistical techniques
  3. Know which tests are and are not appropriate

R is an open source programming language so all of the software we will use in the course is free.

In this course, we explore classical statistical analysis techniques starting with simple hypothesis testing and building up to linear models and power analyses. 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.

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 29
Core Statistics using R (ONLINE) (2 of 3) Finished 09:30 - 17:00 Bioinformatics Training Facility - Online LIVE Training

PLEASE BE AWARE: This event is run online, if you wish to book for the in-person version, please click here.

This award winning virtually delivered 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.

There are three core goals for this course:

  1. Use R confidently for statistics and data analysis
  2. Be able to analyse datasets using standard statistical techniques
  3. Know which tests are and are not appropriate

R is an open source programming language so all of the software we will use in the course is free.

In this course, we explore classical statistical analysis techniques starting with simple hypothesis testing and building up to linear models and power analyses. 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.

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.

Core Statistics using R (IN PERSON) (2 of 3) Finished 09:30 - 17:00 Bioinformatics Training Room, Craik-Marshall Building

PLEASE BE AWARE: This event is run in-person, if you wish to book for the online version, please click here.

This award winning virtually delivered 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.

There are three core goals for this course:

  1. Use R confidently for statistics and data analysis
  2. Be able to analyse datasets using standard statistical techniques
  3. Know which tests are and are not appropriate

R is an open source programming language so all of the software we will use in the course is free.

In this course, we explore classical statistical analysis techniques starting with simple hypothesis testing and building up to linear models and power analyses. 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.

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 30
Core Statistics using R (ONLINE) (3 of 3) Finished 09:30 - 17:00 Bioinformatics Training Facility - Online LIVE Training

PLEASE BE AWARE: This event is run online, if you wish to book for the in-person version, please click here.

This award winning virtually delivered 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.

There are three core goals for this course:

  1. Use R confidently for statistics and data analysis
  2. Be able to analyse datasets using standard statistical techniques
  3. Know which tests are and are not appropriate

R is an open source programming language so all of the software we will use in the course is free.

In this course, we explore classical statistical analysis techniques starting with simple hypothesis testing and building up to linear models and power analyses. 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.

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.

Core Statistics using R (IN PERSON) (3 of 3) Finished 09:30 - 17:00 Bioinformatics Training Room, Craik-Marshall Building

PLEASE BE AWARE: This event is run in-person, if you wish to book for the online version, please click here.

This award winning virtually delivered 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.

There are three core goals for this course:

  1. Use R confidently for statistics and data analysis
  2. Be able to analyse datasets using standard statistical techniques
  3. Know which tests are and are not appropriate

R is an open source programming language so all of the software we will use in the course is free.

In this course, we explore classical statistical analysis techniques starting with simple hypothesis testing and building up to linear models and power analyses. 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.

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.

October 2022

Fri 14
Introduction to R for Biologists (ONLINE LIVE TRAINING) (1 of 2) Finished 09:30 - 17:30 Bioinformatics Training Facility - Online LIVE Training

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.

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 19
Introduction to working with UNIX and bash (ONLINE LIVE TRAINING) (1 of 2) Finished 09:30 - 13:00 Bioinformatics Training Facility - Online LIVE Training

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 the techniques learnt so far, we will then construct bash scripts combining the commands and structures already learnt into more complex, reusable tools. We will look at how we can apply these scripts to common problems faced in UNIX environments such as: communicating with remote servers; managing custom software installations and integrating these tools into our simple pipelines.

This course is targeted at participants with no prior experience working with UNIX-like systems (OSX, Linux) or command line interfaces.

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 20
Introduction to working with UNIX and bash (ONLINE LIVE TRAINING) (2 of 2) Finished 09:30 - 13:00 Bioinformatics Training Facility - Online LIVE Training

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 the techniques learnt so far, we will then construct bash scripts combining the commands and structures already learnt into more complex, reusable tools. We will look at how we can apply these scripts to common problems faced in UNIX environments such as: communicating with remote servers; managing custom software installations and integrating these tools into our simple pipelines.

This course is targeted at participants with no prior experience working with UNIX-like systems (OSX, Linux) or command line interfaces.

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 21
Introduction to R for Biologists (ONLINE LIVE TRAINING) (2 of 2) Finished 09:30 - 17:30 Bioinformatics Training Facility - Online LIVE Training

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.

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 28
Core Statistics using R (ONLINE LIVE TRAINING) (1 of 3) Finished 09:30 - 17:00 Bioinformatics Training Facility - Online LIVE Training

This award winning virtually delivered 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.

There are three core goals for this course:

  1. Use R confidently for statistics and data analysis
  2. Be able to analyse datasets using standard statistical techniques
  3. Know which tests are and are not appropriate

R is an open source programming language so all of the software we will use in the course is free.

In this course, we explore classical statistical analysis techniques starting with simple hypothesis testing and building up to linear models and power analyses. 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.

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 31
Experimental Design (ONLINE LIVE TRAINING) Finished 09:45 - 15:00 Bioinformatics Training Facility - Online LIVE Training

Modern technologies are able to deliver an unprecedented amount of data rapidly. However, without due care and attention early in the experimental process, such data are meaningless if they cannot adequately answer the intended research question. This course is aimed at those planning high-throughput experiments and highlights the kinds of questions they should be asking themselves. The course consists of a lecture and small-group discussions led by a member of the Genomics or Bioinformatics Cores.

This event is part of a series of training courses organized in collaboration with the Bioinformatics Core Facility at CRUK Cambridge Institute.

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

November 2022

Fri 4
Core Statistics using R (ONLINE LIVE TRAINING) (2 of 3) Finished 09:30 - 17:00 Bioinformatics Training Facility - Online LIVE Training

This award winning virtually delivered 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.

There are three core goals for this course:

  1. Use R confidently for statistics and data analysis
  2. Be able to analyse datasets using standard statistical techniques
  3. Know which tests are and are not appropriate

R is an open source programming language so all of the software we will use in the course is free.

In this course, we explore classical statistical analysis techniques starting with simple hypothesis testing and building up to linear models and power analyses. 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.

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 7
Managing your Research Data (ONLINE LIVE TRAINING) Finished 10:00 - 16:00 Bioinformatics Training Facility - Online LIVE Training

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? Would you be able to write a Data Management Plan as part of a grant proposal?

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.

Course materials are available here

This event is part of a series of training courses organized in collaboration with the Bioinformatics Core Facility at CRUK Cambridge Institute.

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