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22 matching courses
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Analysis of DNA Methylation using Sequencing Wed 27 Jun 2018   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.

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

An Introduction to Machine Learning new Tue 1 May 2018   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.

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

An Introduction to MATLAB for biologists Mon 25 Jun 2018   09:30 [Places]

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 goal of metabolomics is to identify and quantify the complete biochemical composition of a biological sample. With the increase in genomic, transcriptomic and proteomic information there is a growing need to understand the metabolic phenotype that these genes and proteins ultimately control.

The aim of this course is to provide an overview of metabolomics and its applications in life sciences, clinical and environmental settings. Over 2 days we will introduce different techniques used to extract metabolites and analyse samples to collect metabolomic data (such as HPLC or GC-based MS and NMR), present how to analyse such data, how to identify metabolites using online databases and how to map the metabolomic data to metabolic pathways.

The course content will predominantly be based on analysing samples from model plant species such as Arabidopsis thaliana but the procedures are transferable to all other organisms, including clinical and environmental settings.

Please note that if you are not eligible for a University of Cambridge Raven account you will need to book 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. Functions and modules are now the focus of a new 1-day course, Working with Python: functions and modules.

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

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.

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.

Big Data and Cloud Computing new Fri 1 Jun 2018   09:30 [Full]

Recent advances in genomics, proteomics, imaging and other technologies, have resulted in data being generated at a faster rate than they can be meaningfully analysed. In this course we will show you how cloud computing can be used to meet the challenges of storage, management and analysis of big data. The first half of the course will introduce cloud infrastructure technologies. The second half will cover tools for collaborative working, resource management, and creation of workflows. The instructors will demonstrate how they are using cloud computing in their own research.

N.B. If you sign up for this course, you will be automatically registered for an AWS educate account, which will provide you with sufficient AWS credits to complete the course exercises. If you decide to continue using cloud computing after the course, you will need to either purchase more credits or apply for a grant from programs like: AWS Cloud Credits for Research, Microsoft Azure for Research or Google Cloud Platform Education Grants.

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

Data Analysis and Visualisation in R Wed 23 May 2018   09:30 [Full]

This course introduces some relatively new additions to the R programming language: dplyr and ggplot2. In combination these R packages provide a powerful toolkit to make the process of manipulating and visualising data easy and intuitive.

Materials for this course can be found here.

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

This 2-days workshop will bring together bioimage analysts, trainers and developers from NEUBIAS, EuroBioImaging and Global BioImaging, as well as ELIXIR’s Bioschemas and TeSS developers, and anyone willing to contribute, to foster new collaborations between ELIXIR and key initiatives from the image analysis community, to:

  • Build a collection of curated image analysis training materials. Many materials are currently available online for several topics but no consistent curation has been applied to them to make them easily discoverable. During the workshop we will collate materials and ensure that, for each image analysis workflow, a minimum set of training materials is available, including slides, practical exercises, Docker container, etc.
  • Improve materials’ annotations (introducing full BioSchemas compliance) and align them with existing ELIXIR efforts (linking to TeSS). During the workshop, materials will be curated to ensure that they are properly described, according to the existing ELIXIR guidelines, and BioSchemas compliant. Consequently the curation will enable materials, hosted by individual providers, to be discoverable via TeSS.
  • Increase the number of Docker/Virtual Machines (VMs) available for easy installation of image analysis training environments. We will focus on: (i) specific pipelines for which containers currently do not exist, (ii) workflows that are of interest to the NEUBIAS/GBI communities and (iii) for which expertise will be available among the workshop participants. This would be incredibly helpful for running future image analysis courses, including the next GBI course planned for October 2018, as it would increase portability of training environments, reducing the burden of lengthy, and often troublesome, software installations.
High Performance Computing: An Introduction Tue 22 May 2018   09:30 [Places]

The course aims to give an introductory overview of High Performance Computing (HPC) in general, and of the facilities of the High Performance Computing Service (HPCS) available at the University of Cambridge.

Practical examples of using the HPCS clusters will be used throughout, although it is hoped that much of the content will have applicability to systems elsewhere.

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

Image Analysis for Biologists Mon 9 Jul 2018   09:30 [Places]

This course will focus on computational methods for analysing cellular images and extracting quantitative data from them. The aim of this course is to familiarise the participants with computational image analysis methodologies, and to provide hands-on training in running quantitative analysis pipelines.

On day 1 we will introduce principles of image processing and analysis, giving an overview of commonly used algorithms through a series of talks and practicals based on Fiji, an extensible open source software package.

On day 2, we will cover time series processing and cell tracking using TrackMate and advanced image segmentation using Ilastik. Additionally, in the afternoon we will run a study design and data clinic (sign up will be required) for participants that wish to discuss their experiments.

On day 3, we will describe the open Icy platform developed at the Institut Pasteur. Icy is a next-generation, user-friendly software offering powerful acquisition, visualisation, annotation and analysis algorithms for 5D bioimaging data, together with unique automation/scripting capabilities (notably via its graphical programming interface) and tight integration with existing software (e.g. ImageJ, Matlab, Micro-Manager).

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 RNA-seq data analysis Mon 18 Jun 2018   09:30 [Full]

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.

Introduction to Scientific Figure Design Wed 13 Jun 2018   09:30 [Full]

This course provides a practical guide to producing figures for use in reports and publications.

It is a wide ranging course which looks at how to design figures to clearly and fairly represent your data, the practical aspects of graph creation, the allowable manipulation of bitmap images and compositing and editing of final figures.

The course will use a number of different open source software packages and is illustrated with a number of example figures adapted from common analysis tools.

Further information and access 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 or register your interest by linking here.

Introduction to Unix shell new Mon 21 May 2018   09:30 [Places]

This course offers an introduction to working with Linux. We will describe the Linux environment so that participants can start to utilize command-line tools and feel comfortable using a text-based way of interacting with a computer. We will take a problem-solving approach, drawing on types of tasks commonly encountered by Linux users when processing text files.

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.

Molecular Phylogenetics Wed 18 Apr 2018   09:00 In progress

This course will provide training for bench-based biologists to use molecular data to construct and interpret phylogenies, and test their hypotheses. Delegates will gain hands-on practice of using a variety of programs freely-available online and commonly used in molecular studies, interspersed with some lectures.

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

Open Targets is a public-private partnership to use human genetics, genomic data and drug information for systematic identification and prioritisation of therapeutic targets. The consortium was founded in 2014 by GSK, EMBL-EBI and the Wellcome Sanger Institute. Two additional partners joined Open Targets in 2016 and 2017, Biogen and Takeda, respectively. Underpinning this partnership is the Open Targets Platform, an open source, user-friendly web interface to investigate causal links between genes, pathways and diseases. These links are computed, scored and ranked using biological evidence integrated from many public data sources, including the NHGRI-EBI GWAS Catalog, Genomics England, PheWAS, ClinVar, Expression Atlas, UniProt, and ChEMBL to name a few.

In addition to data integration, Open Targets also generates new data using human cellular models (e.g. organoids, iPSCs) and genome editing (CRISPR/Cas9) to identify drug targets in oncology, immunology and neurodegenerative diseases. This will be publicly available in the public domain and integrated into the Open Targets Platform.

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.

Protein Structure Analysis new Thu 24 May 2018   09:30 [Full]

This course covers data resources and analytical approaches for the discovery and interpretation of biomacromolecular structures.

Day 1 focuses on public repositories of structural data (Protein Data Bank and Electron Microscopy Data Bank) and resources for protein analysis and classification (Pfam, InterPro and HMMER).

Day 2 covers how to find information about the structure and function of your protein sequence using CATH, principles of modern state-of-the-art protein modelling with Phyre2 and methods for predicting the effects of mutations on protein structure and function using the SAAP family of tools.

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

The course will teach intermediate R object-oriented programming and how to build a fully functional R package.

Relevant teaching materials are available here and the sequences example package used as template in the course can be found here.

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.

Statistical Analysis using R Wed 16 May 2018   09:30 [Full]

Statistics are an important part of most modern studies and being able to effectively use a statistical package will help you to understand your results.

This course provides an introduction to some statistical techniques through the use of the R language. Topics covered include: Chi2 and Fisher tests, descriptive statistics, t-test, analysis of variance and regression.

Students will run analyses using statistical and graphical skills taught during the session.

The course manual can be found here.

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

Using the Ensembl Genome Browser Fri 20 Jul 2018   09:30 [Places]

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.

Variant Discovery with GATK4 Mon 16 Jul 2018   09:30 [Full]

This workshop will focus on the core steps involved in calling variants with the Broad’s Genome Analysis Toolkit, using the “Best Practices” developed by the GATK team. You will learn why each step is essential to the variant discovery process, what are the operations performed on the data at each step, and how to use the GATK tools to get the most accurate and reliable results out of your dataset.

In the course of this workshop, we highlight key functionalities such as the germline GVCF workflow for joint variant discovery in cohorts, somatic variant discovery using MuTect2, and copy number variation discovery using GATK-CNV. All analyses are demonstrated using GATK version 4. Finally, we demonstrate the use of pipelining tools to assemble and execute GATK workflows.

The workshop covers basic genomics, all currently supported Best Practices pipelines as well as pipelining with WDL/Cromwell/FireCloud. This includes the logic of the major pipelines, file formats and data transformations involved, and hands-on operation of the tools using goal-oriented exercises.

  • Day 1: Introduction to Genomics, GATK Best Practices and Pipelining
  • Day 2: Germline short variant discovery (SNPs + Indels)
  • Day 3: Somatic variant discovery (SNVs + Indels + CNVs)
  • Day 4: Writing pipelines with WDL and running them in FireCloud

Please note that this workshop is focused on human data analysis. The majority of the materials presented does apply equally to non-human data, and we will address some questions regarding adaptations that are needed for analysis of non-human data, but we will not go into much detail on those points.

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 will cover concepts and strategies for working more effectively with Python with the aim of writing reusable code. In the morning session, we will briefly go over the basic syntax, data structures and control statements. This will be followed by an introduction to writing user-defined functions. We will finish the course by looking into how to incorporate existing python modules and packages into your programs as well as writing you own modules.

Course materials can be found here.

Note: this one-day 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.

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

1 other event...

Date Availability
Thu 31 May 2018 09:30 POSTPONED
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