Bioinformatics course timetable
March 2017
Tue 7 |
Galaxy is an open, web-based platform for data-intensive life science research that enables non-bioinformaticians to create, run, tune, and share their own bioinformatic analyses. A Galaxy introduction course covering basic functions, simple data manipulation using use cases and examples and visualisation mostly targeted at first time users. Further information is available from the course website. This event is part of a series of training courses organised in collaboration with Dr. Mark Dunning at CRUK Cambridge Institute. Please note that if you are not eligible for a University of Cambridge Raven account you will need to Book by linking here. |
Mon 13 |
Researchers rely on acquiring external data to validate, benchmark and supplement research findings. Funders require researchers to make their datasets accessible for further reuse. The goal of this workshop is to bring to the fore existing challenges with genomic data access and reuse. We will introduce a number of tools and resources to simplify #dataaccess and #datasharing. Please note that if you are not eligible for a University of Cambridge Raven account you will need to book by linking here. |
CRUK: Basic Unix
Finished
The Unix shell has existed since the early days of computers, and yet is still the preferred way to run many popular Bioinformatics tools. This course aims to take the novice and turn them into a beginning Linux user. We will describe the Linux environment so they can start to utilise command-line tools and feel comfortable using a text-based way of interacting with a computer. This event is part of a series of training courses organised in collaboration with Dr. Mark Dunning at CRUK Cambridge Institute. Please note that if you are not eligible for a University of Cambridge Raven account you will need to Book or register Interest by linking here. |
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Tue 14 |
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. |
Wed 15 |
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. |
Thu 16 |
Analysis of single cell RNA-seq data
Finished
Recent technological advances have made it possible to obtain genome-wide transcriptome data from single cells using high-throughput sequencing (scRNA-seq). Even though scRNA-seq makes it possible to address problems that are intractable with bulk RNA-seq data, analysing scRNA-seq is also more challenging. In this course we will be surveying the existing problems as well as the available computational and statistical frameworks available for the analysis of scRNA-seq. The course website providing links to the course materials can be found here. Please note that if you are not eligible for a University of Cambridge Raven account you will need to book by linking here. |
Fri 17 |
Analysis of single cell RNA-seq data
Finished
Recent technological advances have made it possible to obtain genome-wide transcriptome data from single cells using high-throughput sequencing (scRNA-seq). Even though scRNA-seq makes it possible to address problems that are intractable with bulk RNA-seq data, analysing scRNA-seq is also more challenging. In this course we will be surveying the existing problems as well as the available computational and statistical frameworks available for the analysis of scRNA-seq. The course website providing links to the course materials can be found here. Please note that if you are not eligible for a University of Cambridge Raven account you will need to book by linking here. |
Mon 20 |
This module introduces a deeper exploration of bioinformatics analysis of genomic data, providing a greater understanding of the different approaches to mapping and alignment of genome sequence data, programming and scripting, along with approaches for the detection and analysis of genomic changes, gene expression and network analysis. |
Tue 21 |
This module introduces a deeper exploration of bioinformatics analysis of genomic data, providing a greater understanding of the different approaches to mapping and alignment of genome sequence data, programming and scripting, along with approaches for the detection and analysis of genomic changes, gene expression and network analysis. |
Wed 22 |
This module introduces a deeper exploration of bioinformatics analysis of genomic data, providing a greater understanding of the different approaches to mapping and alignment of genome sequence data, programming and scripting, along with approaches for the detection and analysis of genomic changes, gene expression and network analysis. |
Thu 23 |
This module introduces a deeper exploration of bioinformatics analysis of genomic data, providing a greater understanding of the different approaches to mapping and alignment of genome sequence data, programming and scripting, along with approaches for the detection and analysis of genomic changes, gene expression and network analysis. |
Fri 24 |
This module introduces a deeper exploration of bioinformatics analysis of genomic data, providing a greater understanding of the different approaches to mapping and alignment of genome sequence data, programming and scripting, along with approaches for the detection and analysis of genomic changes, gene expression and network analysis. |
CRUK: Image Analysis with Fiji
Finished
Fiji/ImageJ is a popular open-source image analysis software application. This course will briefly cover introductory aspects of image processing and analysis theory, but will focus on practical sessions where participants will gain hands on experience with Fiji. Please note that if you are not eligible for a University of Cambridge Raven account you will need to Book or register Interest by linking here. |
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Mon 27 |
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. 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. |
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. This event is part of a series of training courses organised in collaboration with Dr. Mark Dunning at CRUK Cambridge Institute. Please note that if you are not eligible for a University of Cambridge Raven account you will need to book by linking here. |
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Tue 28 |
This course provides an introduction to high-throughput sequencing (HTS) data analysis methodologies. Lectures will give insight into how biological knowledge can be generated from RNA-seq, ChIP-seq and DNA-seq experiments and illustrate different ways of analyzing such data. Practicals will consist of computer exercises that will enable the participants to apply statistical methods to the analysis of RNA-seq, ChIP-seq and DNA-seq data under the guidance of the lecturers and teaching assistants. It is aimed at researchers who are applying or planning to apply HTS technologies and bioinformatics methods in their research. Please note that if you are not eligible for a University of Cambridge Raven account you will need to book or register your interest by linking here. |
Wed 29 |
This course provides an introduction to high-throughput sequencing (HTS) data analysis methodologies. Lectures will give insight into how biological knowledge can be generated from RNA-seq, ChIP-seq and DNA-seq experiments and illustrate different ways of analyzing such data. Practicals will consist of computer exercises that will enable the participants to apply statistical methods to the analysis of RNA-seq, ChIP-seq and DNA-seq data under the guidance of the lecturers and teaching assistants. It is aimed at researchers who are applying or planning to apply HTS technologies and bioinformatics methods in their research. Please note that if you are not eligible for a University of Cambridge Raven account you will need to book or register your interest by linking here. |
Thu 30 |
This course provides an introduction to high-throughput sequencing (HTS) data analysis methodologies. Lectures will give insight into how biological knowledge can be generated from RNA-seq, ChIP-seq and DNA-seq experiments and illustrate different ways of analyzing such data. Practicals will consist of computer exercises that will enable the participants to apply statistical methods to the analysis of RNA-seq, ChIP-seq and DNA-seq data under the guidance of the lecturers and teaching assistants. It is aimed at researchers who are applying or planning to apply HTS technologies and bioinformatics methods in their research. Please note that if you are not eligible for a University of Cambridge Raven account you will need to book or register your interest by linking here. |
Fri 31 |
This course provides an introduction to high-throughput sequencing (HTS) data analysis methodologies. Lectures will give insight into how biological knowledge can be generated from RNA-seq, ChIP-seq and DNA-seq experiments and illustrate different ways of analyzing such data. Practicals will consist of computer exercises that will enable the participants to apply statistical methods to the analysis of RNA-seq, ChIP-seq and DNA-seq data under the guidance of the lecturers and teaching assistants. It is aimed at researchers who are applying or planning to apply HTS technologies and bioinformatics methods in their research. Please note that if you are not eligible for a University of Cambridge Raven account you will need to book or register your interest by linking here. |
April 2017
Mon 3 |
Basic statistics and data handling
Finished
This three day course is intended to open doors to applying statistics - whether directly increasing skills and personally undertaking analyses, or by expanding knowledge towards identifying collaborators. The end goal is to drive confident engagement with data analysis and further training - increasing the quality and reliability of interpretation, and putting that interpretation and subsequent presentation into the hands of the researcher. Each day of the course will deliver a mixture of lectures, workshops and hands-on practicals – and will focus on the following specific elements. Day 1 focuses on basic approaches and the computer skills required to do downstream analysis. Covering: Basic skills for data manipulation in R. How to prepare your data effectively. Principles of experimental design and how this influences analysis. On day 2, participants will explore the core concepts of statistics – so that they can begin to see how they can be applied to their own work, and to also help with better critical evaluation of the work of others. Covering: Basic statistics concepts and practice: power, variability, false discovery, t-test, effect size, simulations to understand what a p-value means. On day 3 we will continue to explore core concepts of statistics, focusing on linear regression and multiple testing correction. Course materials are available here. This event is supported by the BBSRC Strategic Training Awards for Research Skills (STARS) grant (BB/P022766/1). Please note that all participants attending this course will be charged a registration fee of £150. Please note that if you are not eligible for a University of Cambridge Raven account you will need to book by linking here. |
Tue 4 |
Basic statistics and data handling
Finished
This three day course is intended to open doors to applying statistics - whether directly increasing skills and personally undertaking analyses, or by expanding knowledge towards identifying collaborators. The end goal is to drive confident engagement with data analysis and further training - increasing the quality and reliability of interpretation, and putting that interpretation and subsequent presentation into the hands of the researcher. Each day of the course will deliver a mixture of lectures, workshops and hands-on practicals – and will focus on the following specific elements. Day 1 focuses on basic approaches and the computer skills required to do downstream analysis. Covering: Basic skills for data manipulation in R. How to prepare your data effectively. Principles of experimental design and how this influences analysis. On day 2, participants will explore the core concepts of statistics – so that they can begin to see how they can be applied to their own work, and to also help with better critical evaluation of the work of others. Covering: Basic statistics concepts and practice: power, variability, false discovery, t-test, effect size, simulations to understand what a p-value means. On day 3 we will continue to explore core concepts of statistics, focusing on linear regression and multiple testing correction. Course materials are available here. This event is supported by the BBSRC Strategic Training Awards for Research Skills (STARS) grant (BB/P022766/1). Please note that all participants attending this course will be charged a registration fee of £150. Please note that if you are not eligible for a University of Cambridge Raven account you will need to book by linking here. |
Modern genomics technologies are able to produce large volumes of data that often leave researchers feeling overwhelmed and unsure of how to begin the process of biological interpretation. In this course, we explain the common file formats generated by sequencing technologies and how they can be manipulated and explored by non-bioinformaticians. The tool that we will use is the Integrative Genomics Viewer (IGV). If time allows, there will be time at the end of the session for you to explore your own datasets with the assistance of the instructors. This event is part of a series of training courses organized in collaboration with Dr. Mark Dunning at CRUK Cambridge Institute. The materials for the course were developed in collaboration with Dr. Thomas Carroll from the MRC CSC. 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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Wed 5 |
Basic statistics and data handling
Finished
This three day course is intended to open doors to applying statistics - whether directly increasing skills and personally undertaking analyses, or by expanding knowledge towards identifying collaborators. The end goal is to drive confident engagement with data analysis and further training - increasing the quality and reliability of interpretation, and putting that interpretation and subsequent presentation into the hands of the researcher. Each day of the course will deliver a mixture of lectures, workshops and hands-on practicals – and will focus on the following specific elements. Day 1 focuses on basic approaches and the computer skills required to do downstream analysis. Covering: Basic skills for data manipulation in R. How to prepare your data effectively. Principles of experimental design and how this influences analysis. On day 2, participants will explore the core concepts of statistics – so that they can begin to see how they can be applied to their own work, and to also help with better critical evaluation of the work of others. Covering: Basic statistics concepts and practice: power, variability, false discovery, t-test, effect size, simulations to understand what a p-value means. On day 3 we will continue to explore core concepts of statistics, focusing on linear regression and multiple testing correction. Course materials are available here. This event is supported by the BBSRC Strategic Training Awards for Research Skills (STARS) grant (BB/P022766/1). Please note that all participants attending this course will be charged a registration fee of £150. Please note that if you are not eligible for a University of Cambridge Raven account you will need to book by linking here. |
Thu 6 |
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 7 |
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. |