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12 matching courses
Courses per page: 10 | 25 | 50 | 100


Analysis of bulk RNA-seq data (IN PERSON) Fri 17 Mar 2023   09:30   [More dates...] [Places]

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

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.

2 other events...

Date Availability
Fri 17 Mar 2023 09:30 [Full]
Fri 23 Jun 2023 09:30 Not bookable
Analysis of single cell RNA-seq data (IN PERSON) Thu 18 May 2023   09:30 Not bookable

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.

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 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 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.

1 other event...

Date Availability
Wed 12 Jul 2023 09:30 Not bookable
High Performance Computing: An Introduction (IN PERSON) Mon 10 Jul 2023   09:30 Not bookable

Have you heard about High Performance Computing, but are not sure what it is or whether it is relevant for your work? Would you like to use a HPC, but are not sure where to start? Are you using your personal computer to run computationally demanding tasks, which take long and slow down your work? Do you need to use software that runs on Linux, but don't have access to a Linux computer? If any of these questions apply to you, then this course might be for you!

Knowing how to work on a High Performance Computing system is an essential skill for applications such as bioinformatics, big-data analysis, image processing, machine learning, parallelising tasks, and other high-throughput applications.

In this course we will cover the basics of High Performance Computing, what it is and how you can use it in practice. This is a hands-on workshop, which should be accessible to researchers from a range of backgrounds and offering several opportunities to practice the skills we learn along the way.

As an optional session for those interested, we will also introduce the (free) HPC facilities available at Cambridge University (the course is not otherwise Cambridge-specific).

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.

Have you heard about High Performance Computing, but are not sure what it is or whether it is relevant for your work? Would you like to use a HPC, but are not sure where to start? Are you using your personal computer to run computationally demanding tasks, which take long and slow down your work? Do you need to use software that runs on Linux, but don't have access to a Linux computer? If any of these questions apply to you, then this course might be for you!

Knowing how to work on a High Performance Computing system is an essential skill for applications such as bioinformatics, big-data analysis, image processing, machine learning, parallelising tasks, and other high-throughput applications.

In this course we will cover the basics of High Performance Computing, what it is and how you can use it in practice. This is a hands-on workshop, which should be accessible to researchers from a range of backgrounds and offering several opportunities to practice the skills we learn along the way.

As an optional session for those interested, we will also introduce the (free) HPC facilities available at Cambridge University (the course is not otherwise Cambridge-specific).

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.

The course will cover ANOVA, linear regression and some extensions. It will be a mixture of lectures and hands-on time using RStudio to analyse data.

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 Interest by linking here.

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.

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.

2 other events...

Date Availability
Tue 4 Jul 2023 09:30 Not bookable
Tue 4 Jul 2023 09:30 Not bookable

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).

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.

1 other event...

Date Availability
Mon 19 Jun 2023 09:30 Not bookable
Reproducible Research with R (ONLINE LIVE TRAINING) Thu 4 May 2023   09:30 Not bookable

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.

Variant Discovery with GATK4 (IN PERSON) Tue 18 Apr 2023   09:30 [Places]

This workshop will focus on the core steps involved in calling variants from Illumina next generation sequencing data using the Genome Analysis Toolkit (GATK). You will learn about best practices in calling somatic variants: single nucleotide variants (SNVs), short insertion/deletions (indels) and copy number variants (CNVs). We will also cover considerations to take when calling variants on the mitochondrial genome, as well as variant calling from bulk and single-cell RNA-seq data. We will also cover how the data structures provided by GATK can help you process large datasets in parallel and at scale. Although this workshop focuses on human data, the majority of the concepts and approaches apply to non-human data, and we will cover some adaptations needed in those situations.

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.

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