Bioinformatics course timetable

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.

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.

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.

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.

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.

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.

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.

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.

High-throughput data analyses usually involve many data processing steps, including the use of a range of command line tools and scripts to transform, filter, aggregate and visualise data. Each tool may require a specific set of inputs and options to be defined and, as we chain multiple tools together, this can become challenging to manage. As analyses pipelines become more complex and with the ever-increasing amounts of data being collected in research, reproducible and scalable automatic workflow management becomes increasingly important.

The Snakemake workflow management system is a tool to create reproducible and scalable data analyses pipelines/workflows. Workflows are described via a human-readable, Python-based language. They can be seamlessly scaled to server, cluster, grid and cloud environments, without the need to modify the workflow definition. Finally, Snakemake workflows can entail a description of the required software, which will be automatically deployed to any execution environment.

With over 500k downloads on Bioconda, and over 2k citations, Snakemake is a widely used and accepted standard for reproducible data science that has powered numerous research goals and publications.

This 1-day workshop will cover the principles for building workflows using Snakemake, as well as more advanced strategies to fully customise, automate and scale your analysis.

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.

The Unix shell (command line) is a powerful and essential tool for modern researchers, in particular those working in computational disciplines such as bioinformatics and large-scale data analysis. In this course we will explore the basic structure of the Unix operating system and how we can interact with it using a basic set of commands. You will learn how to navigate the filesystem, manipulate text-based data and combine multiple commands to quickly extract information from large data files. You will also learn how to write scripts, use programmatic techniques to automate task repetition, and communicate with remote servers (such as High Performance Computing servers).

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.

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

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.

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.

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

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.

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.

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

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.

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.

This one-day course is primarily aimed at life science researchers, but covers many topics that are applicable to other fields. It combines key theoretical knowledge with practical application, which will aid researchers in designing effective experiments. The focus throughout the course is to link experimental design to a clear analysis strategy. This ensures that the collected data will be suitable for statistical analysis. During this course, we cover:

• Practices in experimental design that lead to high quality research
• Common design pitfalls, and how to avoid or mitigate them
• A brief introduction to more advanced analysis techniques for experiments with unusual or complex designs

Topics included in the course include: crafting a good research question, operationalising variables effectively, identifying and dealing with confounding variables and pseudoreplication, and practical tips for power analysis and piloting.

The course is delivered via a mix of lectures, group discussion and worked examples.

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.

This course will teach you how to use molecular data to construct and interpret phylogenies. We will start by introducing basic concepts in phylogenetic analysis, what trees represent and how to interpret them. We will then cover how to produce a multiple sequence alignment from DNA and protein sequences, and the pros and cons of different alignment algorithms. You will then learn about different methods of phylogenetic inference, with a particular focus on maximum likelihood and how to assess confidence in your tree using bootstrap resampling. Finally, we will introduce how Bayesian methods can help to estimate the uncertainty in the inferred tree parameters as well as incorporate information for more advanced/bespoke phylogenetic analysis.

If you do not have a University of Cambridge Raven account please book or register your interest here.

• ♿ The training room is located on the first floor and there is currently no wheelchair or level access.
• Our courses are only free for registered University of Cambridge students. All other participants will be charged according to our charging policy.
• Attendance will be taken on all courses and a charge is applied for non-attendance, including for University of Cambridge students. After you have booked a place, if you are unable to attend any of the live sessions, please email the Bioinfo Team.
• Further details regarding eligibility criteria are available here.

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.