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Bioinformatics Training

Bioinformatics course timetable

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Sun 27 May – Fri 13 Jul

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May 2018

Thu 31
Working with Python: functions and modules POSTPONED 09:30 - 17:30 Bioinformatics Training Room, Craik-Marshall Building, Downing Site

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.

June 2018

Fri 1
Big Data and Cloud Computing new [Full] 09:30 - 17:00 Bioinformatics Training Room, Craik-Marshall Building, Downing Site

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.

Tue 12
Open Targets: Integrating genetics and genomics for disease biology and translational medicine [Places] 13:00 - 16:00 Bioinformatics Training Room, Craik-Marshall Building, Downing Site

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, and later welcomed three new partners, Biogen, Takeda, and Celgene. 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.

Wed 13
Introduction to Scientific Figure Design [Full] 09:30 - 17:30 Bioinformatics Training Room, Craik-Marshall Building, Downing Site

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.

Thu 14
An Introduction to Solving Biological Problems with R (1 of 2) [Full] 09:30 - 17:30 Bioinformatics Training Room, Craik-Marshall Building, Downing Site

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.

Fri 15
An Introduction to Solving Biological Problems with R (2 of 2) [Full] 09:30 - 17:30 Bioinformatics Training Room, Craik-Marshall Building, Downing Site

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.

Mon 18
Introduction to RNA-seq data analysis (1 of 3) [Full] 09:30 - 17:30 Bioinformatics Training Room, Craik-Marshall Building, Downing Site

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.

Tue 19
Introduction to RNA-seq data analysis (2 of 3) [Full] 09:30 - 17:30 Bioinformatics Training Room, Craik-Marshall Building, Downing Site

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.

Wed 20
Introduction to RNA-seq data analysis (3 of 3) [Full] 09:30 - 17:30 Bioinformatics Training Room, Craik-Marshall Building, Downing Site

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.

Thu 21
Statistics for Biologists in R (1 of 2) [Full] 09:30 - 17:00 Bioinformatics Training Room, Craik-Marshall Building, Downing Site

This 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 using the R software package.

In this course we explore classical statistical analysis techniques starting with simple hypothesis testing and building up to generalised linear model analysis. 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.

Fri 22
Statistics for Biologists in R (2 of 2) [Full] 09:30 - 17:00 Bioinformatics Training Room, Craik-Marshall Building, Downing Site

This 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 using the R software package.

In this course we explore classical statistical analysis techniques starting with simple hypothesis testing and building up to generalised linear model analysis. 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.

Mon 25
An Introduction to MATLAB for biologists (1 of 2) [Places] 09:30 - 17:30 Bioinformatics Training Room, Craik-Marshall Building, Downing Site

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.

Tue 26
An Introduction to MATLAB for biologists (2 of 2) [Places] 09:30 - 17:30 Bioinformatics Training Room, Craik-Marshall Building, Downing Site

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.

Wed 27
Analysis of DNA Methylation using Sequencing [Full] 09:30 - 17:30 Bioinformatics Training Room, Craik-Marshall Building, Downing Site

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.

Thu 28
Data Carpentry in R (1 of 2) [Places] 09:30 - 17:30 Bioinformatics Training Room, Craik-Marshall Building, Downing Site

In many domains of research the rapid generation of large amounts of data is fundamentally changing how research is done. The deluge of data presents great opportunities, but also many challenges in managing, analyzing and sharing data.

Data Carpentry workshops are designed to teach basic concepts, skills and tools for working more effectively with data, using a combination of tools with a main focus in R. The workshop is aimed at researchers in the life sciences at all career stages and is designed for learners with little to no prior knowledge of programming, shell scripting, or command line tools.

This course is organized in collaboration with ElixirUK and the Software Sustainability Institute.

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

Fri 29
Data Carpentry in R (2 of 2) [Places] 09:30 - 17:30 Bioinformatics Training Room, Craik-Marshall Building, Downing Site

In many domains of research the rapid generation of large amounts of data is fundamentally changing how research is done. The deluge of data presents great opportunities, but also many challenges in managing, analyzing and sharing data.

Data Carpentry workshops are designed to teach basic concepts, skills and tools for working more effectively with data, using a combination of tools with a main focus in R. The workshop is aimed at researchers in the life sciences at all career stages and is designed for learners with little to no prior knowledge of programming, shell scripting, or command line tools.

This course is organized in collaboration with ElixirUK and the Software Sustainability Institute.

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

July 2018

Mon 2
An introduction to metabolomics and its application in life-sciences (1 of 2) [Full] 09:30 - 17:00 Bioinformatics Training Room, Craik-Marshall Building, Downing Site

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.

Tue 3
An introduction to metabolomics and its application in life-sciences (2 of 2) [Full] 09:30 - 18:00 Bioinformatics Training Room, Craik-Marshall Building, Downing Site

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.

Wed 4
Working with Python: functions and modules [Places] 09:30 - 17:30 Bioinformatics Training Room, Craik-Marshall Building, Downing Site

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.

Fri 6
R object-oriented programming and package development [Places] 09:30 - 17:00 Bioinformatics Training Room, Craik-Marshall Building, Downing Site

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.

Mon 9
Image Analysis for Biologists (1 of 3) [Full] 09:30 - 17:30 Bioinformatics Training Room, Craik-Marshall Building, Downing Site

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.

Tue 10
Image Analysis for Biologists (2 of 3) [Full] 09:30 - 17:00 Bioinformatics Training Room, Craik-Marshall Building, Downing Site

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.

Wed 11
Image Analysis for Biologists (3 of 3) [Full] 09:30 - 17:00 Bioinformatics Training Room, Craik-Marshall Building, Downing Site

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.

Thu 12
An Introduction to Solving Biological Problems with Python (1 of 2) [Places] 09:30 - 17:30 Bioinformatics Training Room, Craik-Marshall Building, Downing Site

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.

Fri 13
An Introduction to Solving Biological Problems with Python (2 of 2) [Places] 09:30 - 17:30 Bioinformatics Training Room, Craik-Marshall Building, Downing Site

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.



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Training events

June 2018

6 6
Metabolomics data analysis in the Cloud: Live Online Training
European Bioinformatics Institute (EMBL-EBI) - Wellcome Genome Campus, Hinxton, Cambridge,  CB10 1SD, United Kingdom
6th 8th Jun

Between 6-8th June 2018, the PhenoMeNal project will be hosting Live Online Training, via a series of live webinars, in which participants will become familiar with the open-source tools and workflows in the PhenoMeNal infrastructure. PhenoMeNal is a comprehensive and standardised e-infrastructure that supports data processing and analysis workflows for data generated by metabolomics studies.

First come, first served

6th

July 2018

12 12
Ensembl REST API course, July 2018
European Bioinformatics Institute (EMBL-EBI) - Training Room 2 - Wellcome Genome Campus, Hinxton, Cambridge,  CB10 1SD, United Kingdom
12th Jul

Work with Ensembl to master the Ensembl REST APIs and flexibly access genome-wide data, such as genes, variants, regulatory features, homologues and alignments.

First come, first served

September 2018

3 3
Structural Bioinformatics
European Bioinformatics Institute (EMBL-EBI) - Wellcome Genome Campus, Hinxton, Cambridge,  CB10 1SD, United Kingdom
3rd 7th Sep

This course explores bioinformatics data resources and tools for the interpretation and exploitation of bio-macromolecular structures.

Open application with selection

3rd

October 2018

2 2
Introduction to Next Generation Sequencing
European Bioinformatics Institute (EMBL-EBI) - Wellcome Genome Campus, Hinxton, Cambridge,  CB10 1SD, United Kingdom
2nd 5th Oct

This course will provide an introduction to the technology, data analysis, tools and resources for next generation sequencing (NGS) data.

Open application with selection

2nd 10 10
ENA Sequence Retrieval
European Bioinformatics Institute (EMBL-EBI) - Wellcome Genome Campus, Hinxton, Cambridge,  CB10 1SD, United Kingdom
10th Oct

This training will introduce ENA (European Nucleotide Archive) users to powerful search and retrieval methods available for annotated sequences, genomes, raw data and metadata, as well as download options from the ENA browser and an introduction to the various ENA browser tools. There will also be a section on cross references and how to retrieve accessions for other resources linked to the primary data in ENA. There will be time for users to present their own use cases or request specific help with their own queries.

First come, first served

23 23
Analysis of High Throughput Sequencing Data
European Bioinformatics Institute (EMBL-EBI) - Wellcome Genome Campus, Hinxton, Cambridge,  CB10 1SD, United Kingdom
23rd 26th Oct

This course will familiarise participants with methodologies for bioinformatics analysis on next generation sequencing (NGS) data.

Open application with selection

23rd

November 2018

6 6
Bioinformatics for Plant Biology
European Bioinformatics Institute (EMBL-EBI) - Wellcome Genome Campus, Hinxton, Cambridge,  CB10 1SD, United Kingdom
6th 9th Nov

A course aimed at introducing those working in plant biology to a range of bioinformatics resources and approaches applicable to their research.

Open application with selection

6th

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CSED 2015 programme

CSED page


COMPUTING FOR RESEARCH
Introduction to NVivo
An Introduction to R  [NEW]
Intermediate Workshop on R [NEW]
An Introduction to PASW (SPSS) [NEW]
Basic Data Analysis PASW (SPSS) [NEW]
Advanced Data Analysis I PASW (SPSS) [NEW]
Advanced Data Analysis II PASW (SPSS) [NEW]
Introduction to Linux [NEW]
Introduction to High Powered Computing [NEW]
Matlab (Online Service) [NEW]

 

Introduction to NVivo

DATE & TIME: Tuesdays 18 & 25 November 2014, 09.30-12.30
REPEATED: Wednesdays 4 & 11 February 2015, 13.30-16.30
REPEATED: Fridays 8 & 15 May 2015, 09.30-12.30
TUTOR: Steve Oldfield, CSED
DURATION: Two half days
VENUE: CSED IT Training Room, 02.01, Library
DETAILS: Nvivo is a software package which makes the task of analysing qualitative data easier. ITCS has arranged a site licence which some Schools at UEA have bought into. It is expected that we will be using version 10 for this course. This course provides a step-by-step introduction to using NVivo for those with little or no experience of it (though some familiarity with analysing qualitative data will be an advantage). Demonstration data will be used, though the techniques and organising principles can be applied to any qualitative data. The course focuses on basic use of the software package; it is not a research methods course.
ADDITIONAL INFORMATION: Participants are expected to attend both parts. A general familiarity with the use of Windows features such as menus, toolbars and dialogue boxes is a prerequisite. Course materials are provided in-session.

[Go to Top of Page]     [Online Course Booking Form]


An Introduction to R [NEW]

DATE & TIME: Wednesday 8 October 2014, 12.00-14.00
VENUE: Room 0.24, Chancellors Drive Annexe
REPEATED: Wednesday 18 February 2015, 12.00-14.00
VENUE: ARTS 1.02
SESSION LEADERS:
Gareth Janacek, CMP
DURATION: 2 hours
RDF Domains: A1, A3
DETAILS: This basic introduction to R aims to get you up and running. We assume some very basic computer skills and a familiarity with data. The topics we expect to cover are;

  • What is R?
  • Basics
  • Preparing and Importing Your Data
  • The Help Files
  • Finding and loading R Packages
  • Graphics
  • Record Keeping
  • Problems/Getting help
  • Examples of analyses: regression and generalised linear models
  • Multivariate techniques (if time permits)

ADDITIONAL INFORMATION: Please feel free to bring your own laptop. The data examples used will be available on Blackboard.

[Go to Top of Page]     [Online Course Booking Form]


Intermediate Workshop on R [NEW]

DATE & TIME: Tuesday 11 November 2014, 12.00-14.00
VENUE: BIO 0.12
REPEATED: Wednesday 13 May 2015, 12.00-14.00
VENUE: ARTS 1.02
SESSION LEADER: Gareth Janacek, CMP
DURATION: 2 hours
RDF Domains: A1, A3
DETAILS: The aim of this session is to show how one can use R to perform statistical analyses. This is a huge subject area and we shall aim to show what is available without delving too far into de   tails. Do feel free to bring your own laptop. The approach is example driven and quite practical.

We would aim to cover:

  • Multivariate analysis
  • PCA
  • Factor Analysis
  • Discriminant analysis
  • Time Series Analysis
  • Time series class
  • Plots
  • Time domain modelling – Forecasting
  • The frequency domain
  • Graphics
  • The basic graphic system, devices and output
  • Trellis graphics
  • GGplot
  • Bayesian Methods
  • Introduction and the LearnBayes pac  kage
  • MCMC
  • R functions for Bayesian inference using lm, glm, mer and polr objects.
  • Point out packages that link R to other Bayesian sampling engines such as JAGS , OpenBUGS , and WinBUGS
  • Survival Analysis
  • Censoring
  • Kaplan –Meier
  • Cox Models

We aim to have at least one example data set in each case.

ADDITIONAL INFORMATION: Feel free to bring your own laptop

[Go to Top of Page]     [Online Course Booking Form]


Introduction to PASW (SPSS) [NEW]

DATE & TIME: Wednesday 14 January 2015, 09.30-12.30
VENUE: Arts, 1.02
SESSION LEADER: Simon Poulton, BIO
DURATION: A half day
RDF Domains: A1, A3
DETAILS:This session introduces you to the PASW (SPSS) statistical software and will cover ways to create and interpret histograms, bar charts and scatter plots using the interactive “Chart Builder”, as well as two main themes;

  • Getting started, including an introduction to the PASW environment (windows & settings), definition of variables, opening and saving PASW files and importing data from other software packages.
  • Exploring your data, including how to create summary statistics for your variables and the creation of frequency tables and cross-tabulations between variables.

ADDITIONAL INFORMATION: There are no attendance requirements for this session, prior knowledge of PASW (SPSS) is not essential, and you do not have to attend all four sessions.  The emphasis is on practical use of PASW rather than statistical theory.  The session will have a strong graphical emphasis and include ‘hands-on’ exercises as well as opportunities for feedback and Q&As.

[Go to Top of Page]     [Online Course Booking Form]


Basic Data Analysis PASW (SPSS) [NEW]

DATE & TIME: Thursday 15 January 2015, 09.30-12.30
VENUE: BIO, 0.12
SESSION LEADERS: Simon Poulton, BIO
DURATION: A half day
RDF Domains: A1, A3
DETAILS: This session assumes that you have used PASW before and have a basic understanding of statistical analysis and testing methods. It will continue the practical use of PASW and show you how to manage, extract and analyse data as well as generate graphical techniques provided in the “Chart Builder”.
ADDITIONAL INFORMATION: To benefit from this session you should be familiar with using PASW.  If you understand and have successfully completed statistical analyses such as ANOVA and linear regression then this course may not be suitable. The emphasis is on practical use of PASW rather than statistical theory. The session will have a strong graphical emphasis and include ‘hands-on’ exercises as well as opportunities for feedback and Q&As.

[Go to Top of Page]     [Online Course Booking Form]

 


Advanced Data Analysis I PASW (SPSS) [NEW]

DATE & TIME: Wednesday 11 March 2015, 09.30-12.30
VENUE: Arts, 1.02
SESSION LEADER: Simon Poulton, BIO
DURATION: A half day
RDF Domains: A1, A3
DETAILS: This session will introduce the concepts of Analysis-of-Variance, Linear Regression and General Linear Models, how they are run and interpreted in PASW. It will cover advanced PASW data handling methods; transposing data and the comprehensive two-stage process for data validation, including the detection of outliers. It introduces the concepts of ANOVA, then moves forward to two-way and multi-way ANOVA, with particular emphasis on how to arrange your data and explore methods of correlation and multiple regression models.
ADDITIONAL INFORMATION: To benefit from this session you should be well-versed in the use of PASW (SPSS) or other statistical software and confident in manipulating data, although perhaps unsure how to achieve this in PASW. You will require an understanding of concepts such as the sums-of-squares and variances, confidence intervals and how to interpret p-values. If you possess extensive experience in using GLMs for linear modelling, then this course may not be suitable. The emphasis is on practical use of PASW rather than statistical theory. The session will have a strong graphical emphasis and include ‘hands-on’ exercises as well as opportunities for feedback and Q&As.

 

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Advanced Data Analysis II PASW (SPSS) [NEW]

DATE & TIME: Wednesday 27 May 2015, 09.30-12.30
VENUE: Arts, 1.02
SESSION LEADER: Simon Poulton
DURATION: A half day
RDF Domains: A1, A3
DETAILS: This session continues the theme of practical use of the software. It explores the importance of residuals and diagnostic tests in ANOVA and regression models and will also cover a brief introduction to Analysis-of-Covariance (ANCOVA). Emphasis will be on how to organise your data and specify models using the GLM dialogue boxes. It will explore the use of mixed models and repeated-measures models and outline how they are implemented and defined in PASW. If you are curious about residuals plots, post-hoc testing or more complex types of linear models then this session may be for you. There will be a strong emphasis on the interpretation of PASW outputs.
ADDITIONAL INFORMATION: You should possess considerable experience of manipulating data and an understanding of basic linear modelling techniques. Familiarity with interpreting the outputs from simple ANOVA and regression models is also required. The emphasis is on practical use of PASW rather than statistical theory. The session will have a strong graphical emphasis and include ‘hands-on’ exercises as well as opportunities for feedback and Q&As.

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Introduction to Linux [NEW]

RDF Domains: A1, A3
DETAILS: Linux is a powerful and versatile open source operating system frequently found powering desktop computers and servers, including the UEA High Performance Computing Cluster. In one-to-one or small group sessions we will work through the fundamental skills needed to begin working with Linux tailored to the individual: from familiarising participants with the working environment, using common commands and file management to more advanced usage and scripting.
ADDITIONAL INFORMATION: This course is held on a one-to-one basis. For further information and to register your interest, please contact hpc.admin@uea.ac.uk

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Introduction to High Powered Computing [NEW]

RDF Domains: A1, A3
DETAILS: Do you have a computational element to your research? In a one-to-one session we will introduce UEA’s HPC cluster and discuss how it can benefit your research looking at your own specific computational requirements. We will go through the initial steps on using the HPC cluster and help you get started with your own task.
ADDITIONAL INFORMATION: This course is held on a one-to-one basis. For further information and to register your interest, please contact hpc.admin@uea.ac.uk

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Matlab (Online Service) [NEW]

RDF Domains: A1, A3
DETAILS:

Matlab Fundamentals

This online course provides a comprehensive introduction to the MATLAB technical computing environment and is intended for beginners and those looking for a review. No prior programming experience or knowledge of MATLAB is necessary. The course is structured to allow thorough assimilation of ideas through hands-on examples and exercises. MATLAB competency is developed in a natural way, with an emphasis on practical application. Themes of data analysis, visualization, modelling, and programming are explored throughout the course.

Topics include:

  • Working with the MATLAB user interface
  • Entering commands and creating variables
  • Performing analysis on vectors and matrices
  • Visualizing vector and matrix data
  • Working with data files
  • Working with data types
  • Automating commands with scripts
  • Writing programs with logic and flow control
  • Writing functions

Matlab for Data Processing and Visualisation

This course focuses on the details of data management and visualization techniques, from reading arbitrarily formatted text data files to producing customized publication-quality graphics. The course emphasizes creating scripts that extend the basic features provided by MATLAB. Topics include:

  • Importing data
  • Organizing data
  • Visualizing data

Matlab Programming Techniques

This course provides hands-on experience using the features in the MATLAB® language to write efficient, robust, and well-organized code. These concepts form the foundation for writing full applications, developing algorithms, and extending built-in MATLAB capabilities. Details of performance optimization, as well as tools for writing, debugging, and profiling code, are covered. Topics include:

  • Creating robust applications
  • Utilizing development tools
  • Structuring code
  • Structuring data
  • Efficient data management
  • Classes and objects

ADDITIONAL INFORMATION: The Matlab sessions are available to take as an online service. For further information please contact hpc.admin@uea.ac.uk

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