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Cambridge Academy of Therapeutic Sciences

 

The following Bioinformatics Training events, taking place at the University of Cambridge, are currently open for booking. Although some of them are already fully booked, we encourage registering as you will be added to the waiting list and notified when a place becomes available.

  • Please note that these courses are only free for University of Cambridge studentsAll other participants will be charged a registration fee in some form.
  • It is the participant’s responsibility to acquire approval from their line manager/supervisor to attend any of these courses.
  • Please review full charging policy at the end of this email.

 

  • These courses are aimed primarily at mid-career scientists – especially those whose formal education likely included statistics, but who have not perhaps put this into practice since.
  • Graduate students, Postdocs and Staff members from the University of CambridgeAffiliated Institutions and other external Institutions or individuals are eligible to attend
  • Further details regarding eligibility criteria are available here

 

All scheduled courses can be found at: http://training.csx.cam.ac.uk/bioinformatics/Event-timetable

 

October 2019

Thu 10  

An Introduction to Data Exploration, Experimental Design, and Biomarker Expression Analysis using JMP Software Tools

13:00 - 17:30 Bioinformatics Training Room, Craik-Marshall Building, Downing Site

Through the use of real world examples and the JMP, JMP Pro, and JMP Genomics software, we will cover best practices used in both industry and academia today to visually explore data, plan biological experiments, detect differential expression patterns, find signals in next-generation sequencing data and easily discover statistically appropriate biomarker profiles and patterns.

 

Fri 11    

Introduction to Scientific Figure Design

09:30 - 17:30 Bioinformatics Training Room, Craik-Marshall Building, Downing Site

This course provides a practical guide to producing figures for use in reports and publications.

It is a wide ranging course which looks at how to design figures to clearly and fairly represent your data, the practical aspects of graph creation, the allowable manipulation of bitmap images and compositing and editing of final figures.

The course will use a number of different open source software packages and is illustrated with a number of example figures adapted from common analysis tools.

Further information and access to the course materials is here.

 

 

Thu 17  

Open Targets: Integrating genetics and genomics for disease biology and translational medicine

13:00 - 17:00 Bioinformatics Training Room, Craik-Marshall Building, Downing Site

Open Targets is a public-private partnership to use human genetics, genomic data and drug information for systematic identification and prioritisation of therapeutic targets. This module introduces the Open Targets partnership, its underlying projects and the bioinformatics resources for researchers studying associations of human genes with diseases.

We offer interactive and hands-on experience with Open Targets Platform and Open Targets Genetics, open source tools of integrated biological and chemical data for drug target identification and prioritisation. We cover user cases relevant to the biomedical and pharmaceutical communities and can customise the course according to specific therapeutic areas.

 

 

Wed 23

ChIP-seq and ATAC-seq analysis (1 of 2)

09:30 - 17:30 Bioinformatics Training Room, Craik-Marshall Building, Downing Site

The primary aim of this course is to familiarise participants with the analysis of ChIP-seq and ATAC-seq data and provide hands-on training on the latest analytical approaches.

The course starts with an introduction to ChIP-seq experiments for the detection of genome-wide DNA binding sites of transcription factors and other proteins. We first show data quality control and basic analytical steps such as alignment, peak calling and motif analysis, followed by practical examples on how to work with biological replicates and fundamental quality metrics for ChIP-seq datasets. On the second day, we then focus on the analysis of differential binding, comparing between different samples. We will also give an introduction to ATAC-seq data analysis for the detection of regions of open chromatin.

 

 

Thu 24

ChIP-seq and ATAC-seq analysis (2 of 2)

09:30 - 17:00 Bioinformatics Training Room, Craik-Marshall Building, Downing Site

The primary aim of this course is to familiarise participants with the analysis of ChIP-seq and ATAC-seq data and provide hands-on training on the latest analytical approaches.

The course starts with an introduction to ChIP-seq experiments for the detection of genome-wide DNA binding sites of transcription factors and other proteins. We first show data quality control and basic analytical steps such as alignment, peak calling and motif analysis, followed by practical examples on how to work with biological replicates and fundamental quality metrics for ChIP-seq datasets. On the second day, we then focus on the analysis of differential binding, comparing between different samples. We will also give an introduction to ATAC-seq data analysis for the detection of regions of open chromatin.

 

 

Wed 30

Data Science in Python (1 of 2)

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.

 

 

Thu 31

Data Science in Python (2 of 2)

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.

 

 

November 2019

Tue 5

Introduction to R for Biologists (1 of 2)

09:30 - 17:30 Bioinformatics Training Room, Craik-Marshall Building, Downing Site

R is one of the leading programming languages in Data Science. It is widely used to perform statistics, machine learning, visualisations and data analyses. It is an open source programming language so all the software we will use in the course is free. This course is an introduction to R designed for participants with no programming experience. We will start from scratch by introducing how to start programming in R and progress our way and learn how to read and write to files, manipulate data and visualise it by creating different plots - all the fundamental tasks you need to get you started analysing your data. During the course we will be working with one of the most popular packages in R; tidyverse that will allow you to manipulate your data effectively and visualise it to a publication level standard.

 

Wed 6

Introduction to R for Biologists (2 of 2)

09:30 - 17:30 Bioinformatics Training Room, Craik-Marshall Building, Downing Site

R is one of the leading programming languages in Data Science. It is widely used to perform statistics, machine learning, visualisations and data analyses. It is an open source programming language so all the software we will use in the course is free. This course is an introduction to R designed for participants with no programming experience. We will start from scratch by introducing how to start programming in R and progress our way and learn how to read and write to files, manipulate data and visualise it by creating different plots - all the fundamental tasks you need to get you started analysing your data. During the course we will be working with one of the most popular packages in R; tidyverse that will allow you to manipulate your data effectively and visualise it to a publication level standard.

 

Wed 20

Analysis of DNA Methylation using Sequencing

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.

 

 

Wed 27

Using the Ensembl Genome Browser

09:30 - 17:30 Bioinformatics Training Room, Craik-Marshall Building, Downing Site

The Ensembl Project provides a comprehensive and integrated source of annotation of, mainly vertebrate, genome sequences. This workshop offers a comprehensive practical introduction to the use of the Ensembl genome browser as well as essential background information.

This course will focus on the vertebrate genomes in Ensembl, however much of what will be covered is also applicable to the non-vertebrates (plants, bacteria, fungi, metazoa and protists) in Ensembl Genomes.

 

December 2019

Thu 5

An Introduction to Solving Biological Problems with Python (1 of 2)

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.

 

 

Fri 6

An Introduction to Solving Biological Problems with Python (2 of 2)

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.

 

 

Mon 9

IAFIG-RMS: Bioimage analysis with Python new charged (1 of 5)

09:30 - 17:00 Bioinformatics Training Room, Craik-Marshall Building, Downing Site

The aim of this 5 days course is to develop motivated participants toward becoming independent BioImage Analysts in an imaging facility or research role. Participants will be taught theory and algorithms relating to bioimage analysis using Python as the primary coding language.

Lectures will focus on image analysis theory and applications. Topics to be covered include: Image Analysis and image processing, Python and Jupyter notebooks, Visualisation, Fiji to Python, Segmentation, Omero and Python, Image Registration, Colocalisation, Time-series analysis, Tracking, Machine Learning, and Applied Machine Learning.

The bulk of the practical work will focus on Python and how to code algorithms and handle data using Python. Fiji will be used as a tool to facilitate image analysis. Omero will be described and used for some interactive coding challenges.

 

 

Tue 10

IAFIG-RMS: Bioimage analysis with Python new charged (2 of 5)

09:30 - 17:00 Bioinformatics Training Room, Craik-Marshall Building, Downing Site

Please see course information above (1 of 5)

 

Wed 11

IAFIG-RMS: Bioimage analysis with Python new charged (3 of 5)

09:30 - 17:00 Bioinformatics Training Room, Craik-Marshall Building, Downing Site

Please see course information above (1 of 5)

 

Thu 12

IAFIG-RMS: Bioimage analysis with Python new charged (4 of 5)

09:30 - 17:00 Bioinformatics Training Room, Craik-Marshall Building, Downing Site

Please see course information above (1 of 5)

 

Fri 13

IAFIG-RMS: Bioimage analysis with Python new charged (5 of 5)

09:30 - 17:00 Bioinformatics Training Room, Craik-Marshall Building, Downing Site

Please see course information above (1 of 5)

 

Mon 16

Analysis of single cell RNA-seq data (1 of 2)

09:30 - 17:30 Bioinformatics Training Room, Craik-Marshall Building, Downing Site

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.

 

 

Tue 17

Analysis of single cell RNA-seq data (2 of 2)

09:30 - 17:30 Bioinformatics Training Room, Craik-Marshall Building, Downing Site

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.

 

January 2020

Mon 6

Snakemake workshop new (1 of 2)

09:30 - 17:30 Bioinformatics Training Room, Craik-Marshall Building, Downing Site

Data analyses usually entail the application of many command line tools or scripts to transform, filter, aggregate or plot data and results. With ever increasing amounts of data being collected in science, reproducible and scalable automatic workflow management becomes increasingly important.

The Snakemake workflow management system is a tool to create reproducible and scalable data analyses. Workflows are described via a human readable, Python based language. They can be seamlessly scaled to server, cluster, grid and cloud environments, without the need to modify the workflow definition. Finally, Snakemake workflows can entail a description of required software, which will be automatically deployed to any execution environment.

With over 100k downloads on Bioconda, Snakemake is a widely used and accepted standard for reproducible data science that has powered numerous high impact publications.

This 2-day workshop with, at the first day, teach how to use Snakemake for reproducible data analysis. On the second day, we will further discuss advanced topics and everybody is welcome to apply the obtained knowledge for his or her own analysis project while getting help from the organizers.

 

 

Tue 7

Snakemake workshop new (2 of 2)

09:30 - 17:00 Bioinformatics Training Room, Craik-Marshall Building, Downing Site

Data analyses usually entail the application of many command line tools or scripts to transform, filter, aggregate or plot data and results. With ever increasing amounts of data being collected in science, reproducible and scalable automatic workflow management becomes increasingly important.

The Snakemake workflow management system is a tool to create reproducible and scalable data analyses. Workflows are described via a human readable, Python based language. They can be seamlessly scaled to server, cluster, grid and cloud environments, without the need to modify the workflow definition. Finally, Snakemake workflows can entail a description of required software, which will be automatically deployed to any execution environment.

With over 100k downloads on Bioconda, Snakemake is a widely used and accepted standard for reproducible data science that has powered numerous high impact publications.

This 2-day workshop with, at the first day, teach how to use Snakemake for reproducible data analysis. On the second day, we will further discuss advanced topics and everybody is welcome to apply the obtained knowledge for his or her own analysis project while getting help from the organizers.

 

 

Thu 23  

Extracting biological information from gene lists

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.

 

 

 

All scheduled courses can be found at: http://training.csx.cam.ac.uk/bioinformatics/Event-timetable

Full details of our charging policy can be found at: http://training.csx.cam.ac.uk/bioinformatics/info/charging

Please note that it is the participant’s responsibility to acquire approval from their line manager/supervisor to attend any of these courses. All non-attendees (including University of Cambridge students) who fail to cancel more than 24 hours before a course, will be charged irrespectively.

 

Registration charges (Unless otherwise stated):

  • Free for University of Cambridge students.
  • £ 50/day for all University of Cambridge staff, including postdocs, and participants from Affiliated Institutions. Please note that these charges are recovered by us at the Institutional level.
  • It remains the participant's responsibility to acquire prior approval from the relevant group leader, line manager or budget holder to attend the course. It is requested that people booking only do so with the agreement of the relevant party as costs will be charged back to your Lab Head or Group Supervisor.
  • £ 50/day for all other academic participants from External Institutions and Charitable Organizations. These charges must be paid at registration.
  • £ 100/day for all Industry participants. These charges must be paid at registration.

Full details of our charging policy can be found at: http://training.csx.cam.ac.uk/bioinformatics/info/charging