April 12-16, 2021, 09:00 - 12:00 (MEZ)
The upcoming training course is divided into five consecutive days, centered on bioinformatic questioning and utilizing Galaxy. Each training course is divided into an interactive lecture followed by a hands-on session. Each day will start with an optional discussion about the previous hands-on. We aim to convey the following topics.
Monday, April 12th - Introduction to Galaxy
Tutor: Steffen C. Lott
In the first lesson, we will dive into the Galaxy platform to master data handling focused on bioinformatics. Here, we get to know the benefits of using Galaxy, the FAIR principles, version control, batch processing, and workflow design. Additionally, sharing data and working with Galaxy histories will also be part of this session.
Tuesday, April 13th - Data formatting
Tutor: David Brauer
Galaxy and its integrated tools offer a flexible way for analyzing complex and diverse data. While autonomously generated data, such as RNA-seq data, are "usually ready-to-go", manually formatted data, like spreadsheets and other text documents, are more challenging to integrate.
This course aims to give you an overview of the data formatting tools in Galaxy. We will showcase simple operations like transposing rows and columns and further introduce more complex data operations using regular expressions and UNIX utilities like "sed" and "awk".
Wednesday, April 14th - Transcriptomics
Tutor: Markus Wolfien
This session will introduce the RNA-Seq data analysis capabilities of the Galaxy framework for scientific data analyses. We will compare current RNA-Seq technologies to meet specific research questions and show initial data exploration as well as quality control of NGS datasets. Further, concepts of genome alignment and data visualization will be introduced.
Thursday, April 15th - Machine learning
Tutor: Maximilian Hillemanns
Machine Learning (ML) has become an indispensable part of today's data processing techniques. Nowadays, researchers are using Support Vector Machines (SVMs), Random Forests (RFs), and Convolutional Neural Networks (CNNs) to analyze their data. This session provides an introduction to different ML technologies and their applications using Galaxy.
Together we will address the following questions: How can I use ML, and is it suitable to analyze my data, and what can ML tell me about my data (or not)?
Friday, April 16th - Workflow Generator
Tutor: Konstantin Riege
This course showcases the setup of the de.STAIR Galaxy flavor, which enables you to set up a customized Galaxy instance on your own system. This Galaxy instance comprises our established workflow generator plugin, which leverages on a new concept of Galaxy Atoms that combines interactive tours and alternative tools.
With this technology, we can build personalized, reusable Galaxy workflows in a guided and self-educated fashion. Here, we do also recap learning goals from previous training sessions.
This workshop is intended for students and researchers with a background in life sciences and a functional web browser.
Galaxy, Machine Learning, Docker, Galaxy Flavors, Interactive Tours, Transcriptomics, Data formatting