skip to navigation skip to content

Theme: Specialized Training

Show:
Show only:

41 matching courses


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.

Analysis of DNA Methylation using Sequencing Wed 15 Nov 2017   09:30 Finished

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.

This advanced course will cover high-throughput sequencing data processing, ChIP-seq data analysis (including alignment, peak calling), differences in analyses methods for transcription factors (TF) binding and epigenomic datasets, a range of downstream analysis methods for extracting meaningful biology from ChIP-seq data and will provide an introduction to the analysis of open chromatin with ATAC-seq and long-distance interactions with chromosomal conformation capture based Hi-C datasets.

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 or register your interest by linking here.

This course provides an introduction to the tools available through the Bioconductor project for manipulating and analysing high-throughput sequencing (HTS) data. We will present workflows for the analysis of ChIP-Seq and RNA-seq data starting from aligned reads in bam format. We will also describe the various resources available through Bioconductor to annotate and visualize HTS data, which can be applied to any type of sequencing experiment.

The course timetable is available here.

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

Analysis of mapped NGS data with SeqMonk Wed 3 Feb 2016   09:30 Finished

SeqMonk is a graphical program for the visualisation and analysis of large mapped sequencing datasets such as ChIP-Seq, RNA-Seq, and BS-Seq.

The program allows you to view your reads against an annotated genome and to quantitate and filter your data to let you identify regions of interest. It is a friendly way to explore and analysis very large datasets.

This course provides an introduction to the main features of SeqMonk and will run through the analysis of a couple of different datasets to show what sort of analysis options it provides.

Further information is available here.

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

Analysis of single cell RNA-seq data Tue 31 Oct 2017   09:30 Finished

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.

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

In this course we will introduce web-based, open source tools to analyse and interpret high-throughput biological data.

The main focus will be g:Profiler - a toolset for finding most significant functional groups for a given gene or protein list; MEM - a query engine allowing to mine hundreds of public gene expression datasets to find most co-expressed genes based on a query gene; and ClustVis - a web tool for visualizing clustering of multivariate data using Principal Component Analysis (PCA) plot and heatmap.

MEM and g:Profiler are ELIXIR-Estonia node services.

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

Bioinformatics for Principal Investigators new Tue 20 Sep 2016   09:00 Finished

The aim of this workshop is to introduce principal investigators to the challenges of working with biological data, to provide guidance on how to manage such data and to encourage the development of bioinformatics skills in their team.

A timetable for this workshop 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 Interest by linking here.

The Open Microscopy Environment (OME) is an open-source software project that develops tools that enable access, analysis, visualization, sharing and publication of biological image data.

OME has three components:

  • OME-TIFF, standardised file format and data model;
  • Bio-Formats, a software library for reading proprietary image file formats; and
  • OMERO, a software platform for image data management and analysis.

In this one day course, we will present the OMERO platform, and show how Facility Managers can use it to manage users, groups, and their microscopy, HCS and digital pathology data.

Help pages on 'Using OMERO for Facility Managers' can be found here.

This course is organized alongside a one day course on Biological Imaging Data Management for Life Scientists. More information on this event are available here.

This course will be delivered by members of the OMERO team. The OME project is supported by BBSRC and Wellcome Trust.

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 Open Microscopy Environment (OME) is an open-source software project that develops tools that enable access, analysis, visualization, sharing and publication of biological image data.

OME has three components:

  • OME-TIFF, standardised file format and data model;
  • Bio-Formats, a software library for reading proprietary image file formats; and
  • OMERO, a software platform for image data management and analysis.

In this one day course, we will present the OMERO platform, and show how to import, organise, view, search, annotate and publish imaging data. Additionally, we will briefly introduce how to use a variety of processing tools with OMERO.

This course is organized alongside a one day course on Biological Imaging Data Processing for Data Scientists. More information on this event are available here.

This course will be delivered by members of the OMERO team. The OME project is supported by BBSRC and Wellcome Trust.

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.

CRUK: Analysis of publicly available microarray data Mon 20 Feb 2017   09:30 Finished

Although microarrays have been superseded by high-throughput sequencing technologies for gene expression profiling, years of experience gained from analysing microarray data has led to a variety of analysis techniques and datasets that can be exploited in other contexts. In this course, we will focus on retrieving and exploring microarray data from public repositories such as Gene Expression Omnibus (GEO).

Course materials can be found here.

This event is part of a series of training courses organized in collaboration with Dr. Mark Dunning at CRUK Cambridge Institute.

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

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?

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.

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.

CRUK: Image Analysis with Fiji Fri 24 Mar 2017   12:30 Finished

Fiji/ImageJ is a popular open-source image analysis software application. This course will briefly cover introductory aspects of image processing and analysis theory, but will focus on practical sessions where participants will gain hands on experience with Fiji.

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.

CRUK: Intermediate Image Analysis new Mon 21 Nov 2016   12:30 Finished

This course will cover common image analysis problems including colocalization, segmentation and tracking. We will also cover the handling of large data including registration, fusion and visualization. We will use Fiji and Icy; two leading open source image analysis software applications.

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.

Galaxy is an open, web-based platform for data-intensive life science research that enables non-bioinformaticians to create, run, tune, and share their own bioinformatic analyses.

A Galaxy introduction course covering basic functions, simple data manipulation using use cases and examples and visualisation mostly targeted at first time users.

Further information is available from the course website.

This event is part of a series of training courses organised in collaboration with Dr. Mark Dunning at CRUK Cambridge Institute.

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

EMBL-EBI: Network Analysis with Cytoscape and PSICQUIC Wed 14 Mar 2018   09:30 [Places]

This module provides an introduction to the theory and concepts of network analysis. Attendees will learn how to construct protein-protein interaction networks and subsequently use these to analyse large-scale datasets generated these to by techniques such as RNA-Seq or mass-spec proteomics. The course will focus on giving attendees hands-on experience in the use of Cytoscape and selected network analysis apps.

Also note: This event is part of a series of short introductions focusing on EMBL-EBI resources. If you want to learn more about these separate training events, see the Related Courses section below.

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 an introduction to high-throughput sequencing (HTS) data analysis methodologies. Lectures will give insight into how biological knowledge can be generated from RNA-seq, ChIP-seq and DNA-seq experiments and illustrate different ways of analyzing such data. Practicals will consist of computer exercises that will enable the participants to apply statistical methods to the analysis of RNA-seq, ChIP-seq and DNA-seq data under the guidance of the lecturers and teaching assistants. It is aimed at researchers who are applying or planning to apply HTS technologies and bioinformatics methods in their research.

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.

Ensembl REST API workshop Thu 25 May 2017   09:30 Finished

The Ensembl project provides a comprehensive and integrated source of annotation of mainly vertebrate genome sequences.

This workshop is aimed at researchers and developers interested in exploring Ensembl beyond the website. The workshop covers using the REST API to query the core, variation, compara and functional genomics (regulation) databases.

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

A hands-on interactive course that will introduce you to how to analyse genomic sequences in the command line environment. Examples will focus on metagenomics data but the course is suitable to anyone starting to analyze high-throughput sequencing data.

This course will be taught by Dr. Adina Howe from Iowa State University. Her group focuses on integrating traditional microbiology approaches with metagenomics and computational biology as investigative tools to understand environmental microbial populations

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 11 Dec 2017   09:30 Finished

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. The afternoon of day two will focus on understanding the basics of deconvolution and colocalisation, using tools in Fiji to look at basic examples of how to apply deconvolution and how to carry out colocalisation analysis in fluorescence microscopy.

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.

Image Analysis for Biologists Mon 26 Jun 2017   09:30 Finished

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 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).

On day 3, we will cover time series processing and cell tracking using TrackMate. In the afternoon, we will present the Image Data Resource, an added-value platform that combines data from multiple independent imaging experiments and imaging modalities and integrates them into a single resource for reanalysis in a convenient, scalable form.

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.

Image Processing and Visualisation with LithoGraphX new Thu 4 Aug 2016   10:00 Finished

LithoGraphX is a software to visualize, process and analyse 3D images and meshes.

On the first day of this course, we will demonstrate how to use LithoGraphX to visualize, clean and process 2D and 3D images. We will cover: (i) how to extract cell shape from 2D or 3D images by marking the cell wall or membrane, (ii) how to extract key morphological features and (iii) how to use these features to build a cell classifier. The first day is intended for biologists and computer scientists interested in using LithoGraphX.

On the second day, we will see how to write and distribute extensions to LithoGraphX. To this purpose, we will learn more about the internals of LithoGraphX and its API both in C++ and Python. The second day is intended for computer scientists wanting either to write their own algorithm or automate complex protocols.

Participants can choose to register for both days or for individual days, depending on their interest and background knowledge.

The timetable for this event can be found here.

This course is organized in collaboration with Dr Susana Sauret-Gueto from the OpenPlant Lab of the Department of Plant Sciences of the University of Cambridge.

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.

Galaxy (http://galaxyproject.org/) is an open, web-based platform for data intensive life science research that enables non-bioinformaticians to create, run, tune, and share bioinformatic analyses. The goal of this course is to demonstrate how to use Galaxy to explore RNA-seq data, for expression profiling, and ChIP-seq data, to assess genomic DNA binding sites. You will learn how to perform analysis in Galaxy, and then how to share, repeat, and reproduce your analyses.

The timetable for this event 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.

Introduction to genome variation analysis using NGS Thu 18 May 2017   09:30 Finished

This course provides an introduction to the analysis of human genome sequence variation with next generation sequencing data (NGS), including:

  • an introduction to genetic variation as well as data formats and analysis workflows commonly used in NGS data analysis;
  • an overview of available analytical tools and discussion of their limitations; and
  • hands-on experience with common computational workflows for analysing genome sequence variation using bioinformatics and computational genomics approaches.

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 and ChIP-seq data analysis Wed 25 Oct 2017   09:30 Finished

The aim of this course is to familiarize the participants with the primary analysis of datasets generated through two popular high-throughput sequencing (HTS) assays: ChIP-seq and RNA-seq.

This course starts with a brief introduction to the transition from capillary to high-throughput sequencing (HTS) and discusses quality control issues, which are common among all HTS datasets. Next, we will present the alignment step and how it differs between the two analysis workflows. Finally, we focus on dataset specific downstream analysis, including peak calling and motif analysis for ChIP-seq and quantification of expression, transcriptome assembly and differential expression analysis for 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 Fri 6 Oct 2017   09:30 Finished

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.

Molecular Phylogenetics Wed 18 Apr 2018   09:00 [Places]

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.

Network Visualisation and Analysis of Biological Data new Thu 14 Apr 2016   09:30 Finished

This two day course will cover network-based approaches to visualise and analyse complex biological ‘big’ data and model pathway systems. The course will be centred on the use of BioLayout Express3D, a tool developed between scientists at the University of Edinburgh and EBI over the last 10 years.

BioLayout provides rapid and versatile means to explore and integrate very large datasets, providing a stunning interface to visualise the relationships between 10’s of thousands of data points. Originally designed for the analysis of microarray data, it is equally effective in analysing data matrices from other analysis platforms.

Day one of the course will introduce principles of network analysis and their use as a generic medium to understand relationships between entities. We will introduce the basics of network visualisation and navigation within BioLayout and principles of correlation analysis of data matrices. We will then explore how data can be explored and clustered within the tool and how you can use the software to rapidly extract meaning from large and complex datasets.

Day two will focus on pathway modelling. We will explain how to collate information about a given system of interest from the literature, and to turn this information into a logic-based pathway model. We will then explore how these models can be parametrised and imported into BioLayout where simulations can be run that model the dynamics of these systems under different conditions. For more information see: http://www.virtuallyimmune.org/

A draft agenda 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 Interest by linking here.

Next Generation Sequencing data analysis Tue 17 Mar 2015   09:00 Finished

This course provides an introduction to next generation sequencing (NGS) data analysis methodologies. Lectures will give insight into how biological knowledge can be generated from RNA-seq, ChIP-seq and DNA-seq experiments and illustrate different ways of analyzing such data. Practicals will consist of computer exercises that will enable the participants to apply statistical methods to the analysis of RNA-seq, ChIP-seq and DNA-seq data under the guidance of the lecturers and teaching assistants. It is aimed at researchers who are applying or planning to apply NGS technologies and bioinformatics methods in their research.

The timetable for this event 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 Interest by linking here.

  • Nowomics - Access to the latest data and papers relevant to your research
  • Nowomics is a new website to help biologists stay up to date with the latest data and papers relevant to their research. Try it here.
  • Nowomics tracks new papers and many types of data in online repositories. You ‘follow’ the genes and processes you work on to see a Twitter-like news feed of new papers, annotation, interactions, curated comments and more.
  • For each gene you can also include information from orthologues and related genes directly in your news feed.
  • Data are currently included for human, mouse, rat, fly and plant.
  • This short workshop will show you how to use the Beta version of Nowomics to find the latest information for genes & keywords, how to set up your personalised news feed and configure email alerts. We’ll also demonstrate new portals to help researchers working on Drosophila or Arabidopsis find the latest and most popular papers.

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

Jalview hands-on training course is for anyone who works with sequence data and multiple sequence alignments from proteins, RNA and DNA.

Jalview is free software for protein and nucleic acid sequence alignment generation, visualisation and analysis. It includes sophisticated editing options and provides a range of analysis tools to investigate the structure and function of macromolecules through a multiple window interface. For example, Jalview supports 8 popular methods for multiple sequence alignment, prediction of protein secondary structure by JPred and disorder prediction by four methods. Jalview also has options to generate phylogenetic trees, and assess consensus and conservation across sequence families. Sequences, alignments and additional annotation can be accessed directly from public databases and journal-quality figures generated for publication.

The course involves of a mixture of talks and hands-on exercises.

Day 1 is an introduction to protein multiple sequence alignment editing and analysis with Jalview.

Day 2 focuses on using Jalview for RNA sequence analysis, and also integrating cDNA and protein analysis and covers more advanced applications after lunch.

Day 3 concentrates on protein secondary structure prediction with JPred version 4 as well as protein sub-family analysis to identify functionally important residues.

There will be opportunities for attendees to get advice on analysis of their own sequence families.

Further information, including some training videos, is also available.

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

Protein Structure Analysis new Mon 10 Jul 2017   09:30 Finished

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.

The course page includes slides and handouts; other 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.

Microscopy experiments have proven to be a powerful means of generating information-rich data for biological applications. From small-scale microscopy experiments to time-lapse movies and high-throughput screens, automatic image analysis is more objective and quantitative and less tedious than visual inspection.

This course will introduce users to the free open-source image analysis program CellProfiler and its companion data exploration program CellProfiler Analyst. We will show how CellProfiler can be used to analyse a variety of types of imaging experiments. We will also briefly discuss the basic principles of supervised machine learning with CellProfiler Analyst in order to score complex and subtle phenotypes.

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 Analysis with GATK Wed 12 Jul 2017   09:30 Finished

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, RNAseq­ specific processing, and somatic variant discovery using MuTect2. We also preview capabilities of the upcoming GATK version 4, including a new workflow for CNV discovery, and we demonstrate the use of pipelining tools to assemble and execute GATK workflows.

The workshop is composed of one day of lectures and two days of hands­on training, structured as follows. Day 1: theory and application of the Best Practices for Variant Discovery in high­throughput sequencing data. Day 2 and the morning of Day 3: hands­on exercises on how to manipulate the standard data formats involved in variant discovery and how to apply GATK tools appropriately to various use cases and data types. Day 3 afternoon: hands-on exercises on how to write workflow scripts using WDL, the Broad's new Workflow Description Language, and to execute these workflows locally as well as through a publicly accessible cloud-based service.

Please note that this workshop is focused on human data analysis. The majority of the materials presented does apply equally to non­human 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 covers state-of-the-art tools and methods for NGS RNA-seq and exome variant data analysis, which are of major relevance in today's genomic and gene expression studies.

It is oriented to experimental researchers, post-doctoral and PhD students who want to learn about the state-of-the-art of genomic variant and transcriptomics data analysis methodologies and carry out their own analysis.

Further information is available here.

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 Wed 17 Jan 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 note that if you are not eligible for a University of Cambridge Raven account you will need to book by linking here.

Analysis of small RNA-seq data new Tue 2 May 2017   09:30 Finished

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.

Analysis of RNA-seq data with Bioconductor Wed 28 Mar 2018   09:30 [Full]

This course provides an introduction to the tools available through the Bioconductor project for manipulating and analysing bulk RNA-seq data. We will present a workflow for the analysis RNA-seq data starting from aligned reads in bam format and producing a list of differentially-expressed genes. We will also describe the various resources available through Bioconductor to annotate, visualise and gain biological insight from the differential expression results.

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

Bacterial Genome Assembly and Annotation in Galaxy new Thu 8 Jun 2017   09:30 Finished

The workshop will cover the basics of de novo genome assembly using a small genome example. This includes project planning steps, selecting fragment sizes, initial assembly of reads into fully covered contigs, and then assembling those contigs into larger scaffolds that may include gaps. The end result will be a set of contigs and scaffolds with sufficient average length to perform further analysis on, including genome annotation (link to that nomination). This workshop will use tools and methods targeted at small genomes. The basics of assembly and scaffolding presented here will be useful for building larger genomes, but the specific tools and much of the project planning will be different.

This workshop will also introduce genome annotation in the context of small genomes. We’ll begin with genome annotation concepts, and then introduce resources and tools for automatically annotating small genomes. The workshop will finish with a review of options for further automatic and manual tuning of the annotation, and for maintaining it as new assemblies or information becomes available.

This session will include an introduction to the Galaxy platform.

This event is co-organized with EMBL-ABR and the Genomics Virtual Lab. Course materials 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.

The Open Microscopy Environment (OME) is an open-source software project that develops tools that enable access, analysis, visualization, sharing and publication of biological image data.

OME has three components:

  • OME-TIFF, standardised file format and data model;
  • Bio-Formats, a software library for reading proprietary image file formats; and
  • OMERO, a software platform for image data management and analysis.

In this one day course, we will present the OMERO platform, and show how to transition from manual data processing to automated processing workflows. We will introduce how to write applications against the OMERO API, how to integrate a variety of processing tools with OMERO and how to automatically generate output ready for publication.

This course is organized alongside a one day course on Biological Imaging Data Management for Life Scientists. More information on this event are available here.

This course will be delivered by members of the OMERO team. The OME project is supported by BBSRC and Wellcome Trust.

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.

[Back to top]