All Bioinformatics courses

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.

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.
• Guidance on visiting Cambridge and finding accommodation is available here.

This course focuses on methods for the analysis of small non-coding RNA data obtained from high-throughput sequencing (HTS) applications (small RNA-seq). During the course, approaches to the investigation of all classes of small non-coding RNAs will be presented, in all organisms.

Day 1 will focus on the analysis of microRNAs and day 2 will cover the analysis of other types of small RNAs, including Piwi-interacting (piRNA), small interfering (siRNA), small nucleolar (snoRNA) and tRNA-derived (tsRNA).

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

This webinar is an Introduction to Biological Networks, their types, and applications. It will include two of the most commonly used open source Network Visualisation Platforms (R-igraph and Cytoscape) with step-wise protocols for creating and visualising your own data as a network. It will present some of the major layout algorithms, visual styles and tips for effective visualisation, with examples from biology revealing how these can improve analysis and provide insights.

The webinar will be presented in the form of a lecture as well as a tutorial with step-wise screenshots that enable listeners to emulate simple Network creation and analysis. Please note that this is a webinar and not a coding exercise. Links to publicly available resources and hands-on tutorials will be shared with you for further reading and practice.

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.

Through the use of real world examples and the JMP, JMP Pro, and JMP Genomics software, we will cover best practices used in both industry and academia today to visually explore data, plan biological experiments, detect differential expression patterns, find signals in next-generation sequencing data and easily discover statistically appropriate biomarker profiles and patterns.

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.

Analysis of whole genome data unearths a multitude of variants of different classes, which need to be filtered, annotated and validated to arrive at a causative variant for a disease. The current short length sequences, whilst being excellent at identifying single nucleotide variants and short insertions/deletions, struggle to correctly map structural variants (SVs). Long-read sequencing technologies offer improvements in the characterisation of genetic variation and regions that are difficult to assess with short-read sequences.

The aim of this course is to familiarise participants with long read sequencing technologies, their applications and the bioinformatics tools used to assemble this kind of data. Lectures will introduce this technology and provide insight into methods for the analysis of genomic data, while the hands-on sessions will allow participants to run analysis pipelines, focusing on data generated by the Oxford Nanopore Technologies (ONT) platform.

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 IS NOT RETURNING IN ITS CURRENT FORM. PLEASE CHECK OUR WEBSITE FOR MORE INFORMATION.

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.

PLEASE NOTE The Bioinformatics Team are presently teaching as many courses live online, with tutors available to help you work through the course material on a personal copy of the course environment. We aim to simulate the classroom experience as closely as possible, with opportunities for one-to-one discussion with tutors and a focus on interactivity throughout.

This course aims to give you an introduction to the basics of Matlab. During the two day course we will use a practical based approach to give you the confidence to start using Matlab in your own work. In particular we will show you how to write your own scripts and functions and how to use pre-written functions. We will also explore the many ways in which help is available to Matlab users. In addition we will cover basic computer programming in Matlab to enable you to write more efficient scripts.

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 aim of this course is to introduce participants to the basics of statistical analysis and the open source statistical software R, a free software environment for statistical computing and graphics.

Participants will actively use R throughout the course, during which they will be introduced to principles of statistical thinking and interpretation by example, exercises and discussion about a range of problems. The examples will be used to present a variety of statistical concepts and techniques, with no focus on any specific discipline.

Important information: We have 12 configured laptops for use at the workshop. After these laptops have been allocated, participants will either need to share, or bring their own. These laptops will be allocated to the first individuals to express an interest in using them. When booking, please indicate under "Special requirements" if you wish to use one of the 12 laptops or bring your own. Participants bringing their own laptop will be given instructions on what software to install.

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 is aimed at those new to programming and provides an introduction to programming using Perl.

During this course you will learn the basics of the Perl programming language, including how to store data in Perl’s standard data structures such as arrays and hashes, and how to process data using loops, functions, and many of Perl’s built in operators. You will learn how to write and run your own Perl scripts and how to pass options and files to them. The course also covers sorting, regular expressions, references and multi-dimensional data structures.

The course will be taught using the online Learning Perl materials created by Sofia Robb of the University of California Riverside.

The course website providing links to the course materials is here.

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

Please note that this course has been discontinued and has been replaced by the Introduction to R for biologists.

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.

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.