Bioinformatics course timetable

This course provides an introduction to the R programming language and software environment for statistical computing and graphics. A variety of examples with a biological theme will be presented.

The course website providing links 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 Interest by linking here.

This course provides an introduction to the R programming language and software environment for statistical computing and graphics. A variety of examples with a biological theme will be presented.

The course website providing links 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 Interest by linking here.

The aim of this course is to familiarise the participants with advanced data analysis methodologies and provide hands-on training on the latest analytical approaches. Lectures will give insight into how biological knowledge can be generated from High-throughput sequencing 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 sequencing data under the guidance of the lecturers and teaching assistants.

The timetable can be found here.

The aim of this course is to familiarise the participants with advanced data analysis methodologies and provide hands-on training on the latest analytical approaches. Lectures will give insight into how biological knowledge can be generated from High-throughput sequencing 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 sequencing data under the guidance of the lecturers and teaching assistants.

The timetable can be found here.

The aim of this course is to familiarise the participants with advanced data analysis methodologies and provide hands-on training on the latest analytical approaches. Lectures will give insight into how biological knowledge can be generated from High-throughput sequencing 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 sequencing data under the guidance of the lecturers and teaching assistants.

The timetable can be found here.

The aim of this course is to familiarise the participants with advanced data analysis methodologies and provide hands-on training on the latest analytical approaches. Lectures will give insight into how biological knowledge can be generated from High-throughput sequencing 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 sequencing data under the guidance of the lecturers and teaching assistants.

The timetable can be found here.

The aim of this course is to familiarise the participants with advanced data analysis methodologies and provide hands-on training on the latest analytical approaches. Lectures will give insight into how biological knowledge can be generated from High-throughput sequencing 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 sequencing data under the guidance of the lecturers and teaching assistants.

The timetable can be found here.

The aim of this course is to familiarise the participants with advanced data analysis methodologies and provide hands-on training on the latest analytical approaches. Lectures will give insight into how biological knowledge can be generated from High-throughput sequencing 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 sequencing data under the guidance of the lecturers and teaching assistants.

The timetable can be found here.

This course is aimed at those new to programming and provides an introduction to programming using Perl.

During this course you will learn the basics of the Perl programming language, including how to store data in Perl’s standard data structures such as arrays and hashes, and how to process data using loops, functions, and many of Perl’s built in operators. You will learn how to write and run your own Perl scripts and how to pass options and files to them. The course also covers sorting, regular expressions, references and multi-dimensional data structures.

The course will be taught using the online Learning Perl materials created by Sofia Robb of the University of California Riverside.

The course website providing links 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 by linking here.

This course is aimed at those new to programming and provides an introduction to programming using Perl.

During this course you will learn the basics of the Perl programming language, including how to store data in Perl’s standard data structures such as arrays and hashes, and how to process data using loops, functions, and many of Perl’s built in operators. You will learn how to write and run your own Perl scripts and how to pass options and files to them. The course also covers sorting, regular expressions, references and multi-dimensional data structures.

The course will be taught using the online Learning Perl materials created by Sofia Robb of the University of California Riverside.

The course website providing links 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 by linking here.

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 Interest by linking here.

This course is aimed at researchers who want to learn core skills and best practices for scientific computing. It will cover basic concepts and tools, including program design, version control, data management, and task automation. Participants will be encouraged to help one another and to apply what they have learned to their own research problems.

The course covers the core skills needed to be productive in a small research team:

• Unix command line (and how to automate repetitive tasks);
• Python or R (and how to grow a program in a modular, testable way); and
• version control with Git (and how to track and share work efficiently).

Further information is available here.

Applicants for this course are requested to complete a pre-course survey. This will be used to tailor the course content to the audience research interests and background.

This event is organized in collaboration with Software Carpentry.

This course is aimed at researchers who want to learn core skills and best practices for scientific computing. It will cover basic concepts and tools, including program design, version control, data management, and task automation. Participants will be encouraged to help one another and to apply what they have learned to their own research problems.

The course covers the core skills needed to be productive in a small research team:

• Unix command line (and how to automate repetitive tasks);
• Python or R (and how to grow a program in a modular, testable way); and
• version control with Git (and how to track and share work efficiently).

Further information is available here.

Applicants for this course are requested to complete a pre-course survey. This will be used to tailor the course content to the audience research interests and background.

This event is organized in collaboration with Software Carpentry.

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.

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 from scratch and to customize more complex code to fit their needs.

The Course Web Site providing links 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 by linking here.

This course provides a practical introduction to the writing of Python programs for the complete novice. Participants are lead through the core aspects of Python illustrated by a series of example programs. Upon completion of the course, attentive participants will be able to write simple Python programs from scratch and to customize more complex code to fit their needs.

The Course Web Site providing links 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 by linking here.

COSMIC is an expert-curated database of somatic mutations causing human cancer. Broad and comprehensive in scope, it describes over 4 million coding mutations across all human cancer disease types, and encompasses over 20 million somatic variants across other molecular mutation mechanisms in oncogenetics. Mutations are annotated across the entire genome, with deep-resolution expert curation focused on almost 200 key cancer genes.

This course will use the live COSMIC website and genome browser to show you how to access and explore this information, seeking to identify genetic causes and targets in all human cancers.

A timetable for this event 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.

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

Materials for this course can be found here.

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

This 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.

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.

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.

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.