Bioinformatics 2017
(Wed 18 Jan 2017 - Thu 14 Dec 2017)
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March 2017
| 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. |
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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. |
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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. |
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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. |
| Mon 10 |
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, Python functions and modules: best practices. Please note that if you are not eligible for a University of Cambridge Raven account you will need to book by linking here. |
| Tue 11 |
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, Python functions and modules: best practices. Please note that if you are not eligible for a University of Cambridge Raven account you will need to book by linking here. |
| Wed 19 |
Molecular Phylogenetics
Finished
This course will provide training for bench-based biologists to use molecular data to construct and interpret phylogenies, and test their hypotheses. Delegates will gain hands-on practice of using a variety of programs freely-available online and commonly used in molecular studies, interspersed with some lectures. Please note that if you are not eligible for a University of Cambridge Raven account you will need to book by linking here. |
| Thu 20 |
Molecular Phylogenetics
Finished
This course will provide training for bench-based biologists to use molecular data to construct and interpret phylogenies, and test their hypotheses. Delegates will gain hands-on practice of using a variety of programs freely-available online and commonly used in molecular studies, interspersed with some lectures. Please note that if you are not eligible for a University of Cambridge Raven account you will need to book by linking here. |
| Fri 21 |
Molecular Phylogenetics
Finished
This course will provide training for bench-based biologists to use molecular data to construct and interpret phylogenies, and test their hypotheses. Delegates will gain hands-on practice of using a variety of programs freely-available online and commonly used in molecular studies, interspersed with some lectures. Please note that if you are not eligible for a University of Cambridge Raven account you will need to book by linking here. |