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Bioinformatics Training

Bioinformatics course timetable

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Sat 17 Nov – Fri 1 Mar 2019

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November 2018

Wed 21
Ontologies and ontology-based data analysis [Places] 10:00 - 15:00 Bioinformatics Training Room, Craik-Marshall Building, Downing Site

Ontologies have long provided a core foundation in the organization of biomedical entities, their attributes, and their relationships. With over 500 biomedical ontologies currently available there are a number of new and exciting opportunities emerging in using ontologies for large scale data sharing and data analysis.

This tutorial will help you understand what ontologies are and how they are being used in computational biology and bioinformatics. It will include hands-on examples and exercises and an introduction to Onto2Vec and OPA2Vec, two methods that can be used to learn semantic similarity measures in a data- and application-driven way.

The training room is located on the first floor and there is currently no level access.

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

Thu 29
An Introduction to Solving Biological Problems with Python (1 of 2) [Full] 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. Concepts and strategies for working more effectively with Python are now the focus of a new 2-days course, Data Science in Python.

The training room is located on the first floor and there is currently no level access.

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

Fri 30
An Introduction to Solving Biological Problems with Python (2 of 2) [Full] 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. Concepts and strategies for working more effectively with Python are now the focus of a new 2-days course, Data Science in Python.

The training room is located on the first floor and there is currently no level access.

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

December 2018

Mon 3
Bioinformatics for Biologists: An introduction to programming, analysis and reproducibility new (1 of 5) [Full] 09:30 - 17:30 Bioinformatics Training Room, Craik-Marshall Building, Downing Site

This 1-week course aims to provide an introduction to the best practises and tools needed to perform bioinformatics research effectively and reproducibly.

Focusing on solutions around handling biological data, we will cover introductory lessons in programming in R, statistical analyses, data management and reproducibility. The R component of the course will cover from basic steps in R to how to use some of the most popular R packages (dplyr and ggplot2) for data manipulation and visualisation. No prior R experience or previous knowledge of programming/coding is required. The course also includes introductory sessions in statistics and working examples on how to analyse biological data. At the end of the course we will address issues relating to reusability and reproducibility.

More information about the course can be found here.

The training room is located on the first floor and there is currently no level access.

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 4
Bioinformatics for Biologists: An introduction to programming, analysis and reproducibility new (2 of 5) [Full] 09:30 - 17:30 Bioinformatics Training Room, Craik-Marshall Building, Downing Site

This 1-week course aims to provide an introduction to the best practises and tools needed to perform bioinformatics research effectively and reproducibly.

Focusing on solutions around handling biological data, we will cover introductory lessons in programming in R, statistical analyses, data management and reproducibility. The R component of the course will cover from basic steps in R to how to use some of the most popular R packages (dplyr and ggplot2) for data manipulation and visualisation. No prior R experience or previous knowledge of programming/coding is required. The course also includes introductory sessions in statistics and working examples on how to analyse biological data. At the end of the course we will address issues relating to reusability and reproducibility.

More information about the course can be found here.

The training room is located on the first floor and there is currently no level access.

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 5
Bioinformatics for Biologists: An introduction to programming, analysis and reproducibility new (3 of 5) [Full] 09:30 - 17:30 Bioinformatics Training Room, Craik-Marshall Building, Downing Site

This 1-week course aims to provide an introduction to the best practises and tools needed to perform bioinformatics research effectively and reproducibly.

Focusing on solutions around handling biological data, we will cover introductory lessons in programming in R, statistical analyses, data management and reproducibility. The R component of the course will cover from basic steps in R to how to use some of the most popular R packages (dplyr and ggplot2) for data manipulation and visualisation. No prior R experience or previous knowledge of programming/coding is required. The course also includes introductory sessions in statistics and working examples on how to analyse biological data. At the end of the course we will address issues relating to reusability and reproducibility.

More information about the course can be found here.

The training room is located on the first floor and there is currently no level access.

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 6
Bioinformatics for Biologists: An introduction to programming, analysis and reproducibility new (4 of 5) [Full] 09:30 - 17:30 Bioinformatics Training Room, Craik-Marshall Building, Downing Site

This 1-week course aims to provide an introduction to the best practises and tools needed to perform bioinformatics research effectively and reproducibly.

Focusing on solutions around handling biological data, we will cover introductory lessons in programming in R, statistical analyses, data management and reproducibility. The R component of the course will cover from basic steps in R to how to use some of the most popular R packages (dplyr and ggplot2) for data manipulation and visualisation. No prior R experience or previous knowledge of programming/coding is required. The course also includes introductory sessions in statistics and working examples on how to analyse biological data. At the end of the course we will address issues relating to reusability and reproducibility.

More information about the course can be found here.

The training room is located on the first floor and there is currently no level access.

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 7
Bioinformatics for Biologists: An introduction to programming, analysis and reproducibility new (5 of 5) [Full] 09:30 - 17:30 Bioinformatics Training Room, Craik-Marshall Building, Downing Site

This 1-week course aims to provide an introduction to the best practises and tools needed to perform bioinformatics research effectively and reproducibly.

Focusing on solutions around handling biological data, we will cover introductory lessons in programming in R, statistical analyses, data management and reproducibility. The R component of the course will cover from basic steps in R to how to use some of the most popular R packages (dplyr and ggplot2) for data manipulation and visualisation. No prior R experience or previous knowledge of programming/coding is required. The course also includes introductory sessions in statistics and working examples on how to analyse biological data. At the end of the course we will address issues relating to reusability and reproducibility.

More information about the course can be found here.

The training room is located on the first floor and there is currently no level access.

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 10
Using CellProfiler and CellProfiler Analyst to analyse biological images (1 of 2) [Full] 09:30 - 17:30 Bioinformatics Training Room, Craik-Marshall Building, Downing Site

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.

The training room is located on the first floor and there is currently no level access.

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 11
Using CellProfiler and CellProfiler Analyst to analyse biological images (2 of 2) [Full] 09:30 - 17:30 Bioinformatics Training Room, Craik-Marshall Building, Downing Site

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.

The training room is located on the first floor and there is currently no level access.

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 12
Data Science in Python (1 of 2) [Places] 09:30 - 16:30 Bioinformatics Training Room, Craik-Marshall Building, Downing Site

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

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

The training room is located on the first floor and there is currently no level access.

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

Thu 13
Data Science in Python (2 of 2) [Places] 09:30 - 16:30 Bioinformatics Training Room, Craik-Marshall Building, Downing Site

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

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

The training room is located on the first floor and there is currently no level access.

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

Fri 14
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.

The training room is located on the first floor and there is currently no level access.

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

Mon 17
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.

This event is supported by the BBSRC Strategic Training Awards for Research Skills (STARS) grant (BB/P022766/1).

The training room is located on the first floor and there is currently no level access.

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 18
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.

This event is supported by the BBSRC Strategic Training Awards for Research Skills (STARS) grant (BB/P022766/1).

The training room is located on the first floor and there is currently no level access.

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.

January 2019

Wed 9
Statistics for Biologists in R (1 of 4) [Full] 13:30 - 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 multiple linear regression. 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.

This event is supported by the BBSRC Strategic Training Awards for Research Skills (STARS) grant (BB/P022766/1).

The training room is located on the first floor and there is currently no level access.

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 10
Statistics for Biologists in R (2 of 4) [Full] 13:30 - 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 multiple linear regression. 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.

This event is supported by the BBSRC Strategic Training Awards for Research Skills (STARS) grant (BB/P022766/1).

The training room is located on the first floor and there is currently no level access.

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 16
Statistics for Biologists in R (3 of 4) [Full] 13:30 - 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 multiple linear regression. 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.

This event is supported by the BBSRC Strategic Training Awards for Research Skills (STARS) grant (BB/P022766/1).

The training room is located on the first floor and there is currently no level access.

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 17
Statistics for Biologists in R (4 of 4) [Full] 13:30 - 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 multiple linear regression. 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.

This event is supported by the BBSRC Strategic Training Awards for Research Skills (STARS) grant (BB/P022766/1).

The training room is located on the first floor and there is currently no level access.

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 24
Exploring, visualising and analysing proteomics data in R new [Full] 09:30 - 17:00 Bioinformatics Training Room, Craik-Marshall Building, Downing Site

This course will present a set of R/Bioconductor packages to access, manipulate, visualise and analyse mass spectrometry (MS) and quantitative proteomics data.

The training room is located on the first floor and there is currently no level access.

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

February 2019

Tue 19
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.

The training room is located on the first floor and there is currently no level access.

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

Wed 20
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.

The training room is located on the first floor and there is currently no level access.

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

March 2019

Fri 1
Extracting biological information from gene lists new [Full] 09:30 - 17:30 Bioinformatics Training Room, Craik-Marshall Building, Downing Site

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

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

Course materials are available here.

The training room is located on the first floor and there is currently no level access.

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.



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Training events

February 2019

5 5
Introduction to Metabolomics Analysis
European Bioinformatics Institute (EMBL-EBI) - Wellcome Genome Campus, Hinxton, Cambridge,  CB10 1SD, United Kingdom
5th 8th Feb

This course will provide an introduction to metabolomics data analysis using publically available software and tools.

Open application with selection

5th 12 12
Introduction to Multiomics Data Integration
European Bioinformatics Institute (EMBL-EBI) - Training Room 2 - Wellcome Genome Campus, Hinxton, Cambridge,  CB10 1SD, United Kingdom
12th 15th Feb

This course will provide participants with biological examples of data integration, and the challenges that researchers face. The course will focus on the use of public data resources and open access tools for enabling integrated working, with an emphasis on data visualisation.

Open application with selection

12th 26 26
Bioinformatics Resources for Protein Biology
European Bioinformatics Institute (EMBL-EBI) - Training Room 1 - Wellcome Genome Campus, Hinxton, Cambridge,  CB10 1SD, United Kingdom
26th 28th Feb

This three day workshop will introduce you to data resources and tools developed by EMBL-EBI that can help you in your protein studies.

First come, first served

26th

March 2019

19 19
Exploring Human Genetic Variation
European Bioinformatics Institute (EMBL-EBI) - Training Room 2 - Wellcome Genome Campus, Hinxton, Cambridge,  CB10 1SD, United Kingdom
19th 20th Mar

A short workshop to introduce you to data resources and tools developed by EMBL-EBI and the Sanger Institute, that can help you better understand human genetic variation.

First come, first served

19th 26 26
Introduction to RNA-Seq and Functional Interpretation
European Bioinformatics Institute (EMBL-EBI) - Training Room 1 - Wellcome Genome Campus, Hinxton, Cambridge,  CB10 1SD, United Kingdom
26th 29th Mar

This course will provide an introduction to the technology, data analysis, tools and resources used in RNA sequencing and transcriptomics.

Open application with selection

26th

April 2019

1 1
Livestock Genomics
European Bioinformatics Institute (EMBL-EBI) - Training Room 2 - Wellcome Genome Campus, Hinxton, Cambridge,  CB10 1SD, United Kingdom
1st 5th Apr

This course will introduce participants to methods and approaches for analysing genomic data from common livestock species.

Open application with selection

1st 8 8
RNA-Sequence Analysis
European Bioinformatics Institute (EMBL-EBI) - Training Room 2 - Wellcome Genome Campus, Hinxton, Cambridge,  CB10 1SD, United Kingdom
8th 12th Apr

This course will familiarise participants with advanced data analysis methodologies in the field of transcriptomics and to provide practical training in the latest analytical approaches.

First come, first served

8th

May 2019

13 13
Functional Insights Into Biological Data Through Network Analysis
European Bioinformatics Institute (EMBL-EBI) - Training Room 2 - Wellcome Genome Campus, Hinxton, Cambridge,  CB10 1SD, United Kingdom
13th 17th May

This course will provide life scientists with training on using network and pathway tools to enrich biological data. The content examines the data repositories, resources and tools available to explore and analyse large datasets. The principles of biological network and pathway analysis will be introduced and explained using relevant case studies. Participants will also have the opportunity to either learn how to access public repositories via programmatic methods or spend time analysing data using the approaches covered in the course.

Open application with selection

13th

Filters



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.

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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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