Courses
Course 01: Genome Browser Workshop
Dr. Robert Kuhn
Cost: R$ 50,00
Local: Sala 6 d CEC, Bloco B do IME
Dr. Robert Kuhn
Cost: R$ 50,00
Local: Sala 6 d CEC, Bloco B do IME
This workshop is aimed at the biologist who is interested in exploring genomes using the University of California Santa Cruz (UCSC) Genome Browser. It is geared towards those who have little or no experience using the UCSC Genome Browser and for more advanced users who are not familiar with many of the gene-oriented browser features. Using real examples the user is guided through a step-by-step process for analyzing genes in the context of the human genome and a wide variety of genomic data. The user is shown how to use the UCSC Genome Browser for simple and more complex tasks. Tutorials, exercises and/or other informational material on using the UCSC Genome Browser will be provided.
Course 02: Current methodologies in transcriptome analysis
Dr. Boris Guennewig
Cost: R$ 50,00
Local: Auditório Jacy Monteiro, Bloco B do IME
Dr. Boris Guennewig
Cost: R$ 50,00
Local: Auditório Jacy Monteiro, Bloco B do IME
This workshop is aimed at the biologist or computational biologist who is interested in exploring high throughput transcriptome data. Topics covered will be experimental design, quality control, alignments and quantification (day 1); current annotations, differential expression analysis and batch effect control (day 2); de novo assembly, alternative splicing, editing and circRNAs (day 3).
Course 03: Key Aspects of a Successful NGS Course - a GOBLET initiative
Michelle Brazas (Ontario Institute for Cancer Research, Canada) and Patricia Palagi (SIB Swiss Institute of Bioinformatics, Switzerland)
Cost: R$ 50,00
Local: Auditório, CCSL do IME.
Michelle Brazas (Ontario Institute for Cancer Research, Canada) and Patricia Palagi (SIB Swiss Institute of Bioinformatics, Switzerland)
Cost: R$ 50,00
Local: Auditório, CCSL do IME.
Overview: Next generation sequencing technologies (NGS) are heavily exploited techniques in modern biology. As such, the demand for NGS-related courses is steadily growing. Whether in a formal academic setting, a core facility or a company environment, NGS data analysts are frequently requested to set up training courses for their communities. Providing excellent training is a challenge that requires good planning and careful thinking. In this short course, you will learn how to plan a good NGS course, how to define the learning objectives of a course, how to select students (in other words define the pre-requirements), how to structure an NGS learning environment, and how to best exploit the unified collection of training materials and data-sets available on GOBLET and other repositories. This session will be a mix of group work and short talks on best practices.
Audience: This workshop is aimed at scientists and analysts with little or no experience in setting up a training course in NGS. Experienced individuals are also welcome to share their insight and to network.
Requirements: No previous knowledge of setting up a course or special materials are required. Some understanding or experience in NGS data analysis experience would be an asset.
Schedule and Learning Outcomes
Day 1 - Setting up a NGS classroom: Compute environment and logistics
In this session, you will learn how to apply to Amazon for education funding and how to set up Amazon (or similar cloud service) for use in the classroom. You will also learn how to define the required background and skill level participants should have, structure the learning environment and define learning outcomes.
Day 2 - Setting up a NGS workshop: Data sets, Tools and Exercises
In this session you will find out about test datasets and course material repositories and how to reuse what’s already available. You will learn how to evaluate the elements of a good dataset. You will also learn which NGS tools to focus on for which audience type (I.e. Galaxy or command line) and what makes an exercise useful as a learning tool.
In this session you will find out about test datasets and course material repositories and how to reuse what’s already available. You will learn how to evaluate the elements of a good dataset. You will also learn which NGS tools to focus on for which audience type (I.e. Galaxy or command line) and what makes an exercise useful as a learning tool.
Day 3 - Best practices in NGS training
This session will be devoted to the best practices for setting up any bioinformatics training course with a focus on NGS: how to define pre-work and pre-reading materials, how to set up feedback surveys and measure the quality of your training, how to follow-up with the participants who always want more training help.