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Showing courses 1-10 of 16
Courses per page: 10 | 25 | 50 | 100

Analysis of DNA Methylation using Sequencing Wed 20 Nov 2019   09:30 [Places]

This course will cover all aspects of the analysis of DNA methylation using sequencing, including primary analysis, mapping and quality control of BS-Seq data, common pitfalls and complications.

It will also include exploratory analysis of methylation, looking at different methods of quantitation, and a variety of ways of looking more widely at the distribution of methylation over the genome. Finally the course will look at statistical methods to predict differential methylation.

The course will be comprised of a mixture of theoretical lectures and practicals covering a range of different software packages.

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 single cell RNA-seq data Mon 16 Dec 2019   09:30 [Full]

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 course website providing links to the course materials can be found here.

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.

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.

An Introduction to Machine Learning Wed 2 Oct 2019   09:30 [Full]

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.

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.

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.

ChIP-seq and ATAC-seq analysis Wed 23 Oct 2019   09:30 [Full]

The primary aim of this course is to familiarise participants with the analysis of ChIP-seq and ATAC-seq data and provide hands-on training on the latest analytical approaches.

The course starts with an introduction to ChIP-seq experiments for the detection of genome-wide DNA binding sites of transcription factors and other proteins. We first show data quality control and basic analytical steps such as alignment, peak calling and motif analysis, followed by practical examples on how to work with biological replicates and fundamental quality metrics for ChIP-seq datasets. On the second day, we then focus on the analysis of differential binding, comparing between different samples. We will also give an introduction to ATAC-seq data analysis for the detection of regions of open chromatin.

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.

Data Science in Python Wed 30 Oct 2019   09:30 [Full]

This course covers concepts and strategies for working more effectively with Python with the aim of writing reusable code, using function and libraries. Participants will acquire a working knowledge of key concepts which are prerequisites for advanced programming in Python e.g. writing modules and classes.

Note: this course is the continuation of the Introduction to Solving Biological Problems with Python; participants are expected to have attended the introductory Python course and/or have acquired some working knowledge of Python. This course is also open to Python beginners who are already fluent in other programming languages as this will help them to quickly get started 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.

Extracting biological information from gene lists Thu 23 Jan 2020   09:30 [Full]

Many experimental designs end up producing lists of hits, usually based around genes or transcripts. Sometimes these lists are small enough that they can be examined individually, but often it is useful to do a more structured functional analysis to try to automatically determine any interesting biological themes which turn up in the lists.

This course looks at the various software packages, databases and statistical methods which may be of use in performing such an analysis. As well as being a practical guide to performing these types of analysis the course will also look at the types of artefacts and bias which can lead to false conclusions about functionality and will look at the appropriate ways to both run the analysis and present the results for publication.

Course materials are available here.

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 R for Biologists Tue 5 Nov 2019   09:30 [Full]

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.