GCC2019

People should be able to discover galaxy via the scientific workflow that they are looking for.  Let's build a good place for these and generate a few test case workflows. (Ideas: Differential Expression, Variant calling, DNA-methylation, Metagenomics).

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• What exactly is variant calling?
• How can I use Galaxy to call variants from my (exome-, whole-genome-)sequenced samples?

Learning objectives

• Perform simple variant calling workflows including sequencing data quality control, read mapping and variant calling
• Learn about different variant callers available for Galaxy and their strengths and weaknesses

Prerequisites

• Introduction to Galaxy or equivalent experience
• Quality Contol of HTS Data or prior exposure to HTS data
• A wi-fi enabled laptop with a modern web browser. Google Chrome, Firefox and Safari will work best

TIaaS URL for this training: https://usegalaxy.eu/join-training/gcc-variant-calling

Tharindu Senapathi, Simon Bray, Christopher Barnett, Björn Grüning and Kevin Naidoo

→ Abstract, Poster (doi: 10.7490/f1000research.1116911.1)

Anne Fouilloux 1, Jean Iaquinta 1 and Kirstin Krüger 1

1. Department of Geosciences, University of Oslo, Norway

• Why is a simple list of variants for a sample not enough?
• How can I explore called variants and compare them across samples?
• How can I link variants to phenotypes, i.e., identify causative variants?

Learning objectives

• Use joint variant calling to facilitate variant comparison across samples
• Filter, annotate and report lists of variants
• Discover variant inheritance and linkage patterns

Prerequisites

• Introduction to Galaxy or equivalent experience
• Quality Contol of HTS Data or prior exposure to HTS data
• Variant calling I - from sequenced reads to variant lists or variant calling
• A wi-fi enabled laptop with a modern web browser. Google Chrome, Firefox and Safari will work best

TIaaS URL for this training: https://usegalaxy.eu/join-training/gcc-variant-calling

Discuss aspects of the EOSC-Life roadmap relevant to the computational biology community. It's for anyone interested in the future of the European Open Science Cloud.

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This workshop will introduce:

• using Galaxy as a training tool
• Determining aim and audience
  • e.g. single topic; string of related topics;
  • e.g. response to specific request for training; or general upskilling people in Galaxy bioinformatics
• setting up appropriate infrastructure
  • usegalaxy.* resources
  • TIaaS
  • Your own
• The available materials
  • GTN tutorials
  • and/or write your own; including how to contribute it to GTN
  • Customising materials for your needs (Slides, language etc.)
• Distributed workshops
  • In practice
  • Local facilitators vs lead trainers
  • Using Zoom / Skype / other video conferencing software
• Practise setting up your own workshop?
  • eg. choose a topic from GTN
  • check that it runs on Galaxy server of choice
  • time it // modify if need be (e.g. cut down data set more?)
  • create schedule, eg google doc → publish → tinyurl
• Getting good feedback!

Prerequisites

• An interest in using Galaxy to teach/train people

TIaaS URL for this training: https://usegalaxy.eu/join-training/gcc-ttt

Glory Basumata and Kusum K Singh

Galaxy workflows are scientific data processing pipelines for performing and
reproducing data analyses. The workflows are complex and difficult to create from a
suite of 2,000+ tools available in Galaxy, especially for new Galaxy users. In order to
make creating workflows easier, faster and less error-prone, a recommendation
system was developed to predict following tools. The predictive system analyses the
complete set of workflows available on Galaxy’s European server using a deep
learning approach to create a tool prediction model.

Workflows are directed acyclic graphs. To create the predictive model, sequences
(paths) of tools are extracted from these graphs and learned by a deep learning
approach ( Gated Recurrent Neural Network ). The hyperparameters of the deep
learning model are optimised using bayesian optimisation. The usage frequency of
tools is integrated in the model so that the tools which have not been used recently do
not appear in the set of possible tools. This is achieved by learning the usage of each
tool over time using a support vector regression model.

An API was developed to predict tools and visualize them using a user interface. It can
be used in the Galaxy workflow editor (It is not yet available publicly. The complete
code is located here ). The API can be also used for multiple user interface
integrations. Using the tool recommendation system, a user does not need to search
for the tools in the tool box to create a workflow. The possible tools are available in
the “recommended tools” modal popup.

This training session has a Gitter channel where preparation instructions are posted, and for class discussion, last minute links, and more.

    https://gitter.im/galaxyproject/open-source-awesome

Many journals require that scientific / research code to be open source in order to be published, but simply sharing source code alone isn’t usually enough to draw in new users and contributors. This session will discuss how researchers and coders can make their open source code repositories inclusive and welcoming to contributors.

This workshop will be led by members of the InterMine and Galaxy teams (and hopefully other equally awesome projects).

Prerequisites

• A laptop with wifi
• Interest in open source code

This Ecology-focused session will introduce using Galaxy to import (from external sources as GBIF, iNaturalist, Atlas of Living Australia or Zenodo repositories), handle (filter, rename fields, search/replace text patterns), visualize (stacked histograms) and analyze (calculate species abundance, phenology and trends) biodiversity data.

Prerequisites

• Introduction to Galaxy or equivalent experience
• A wi-fi enabled laptop with a modern web browser. Google Chrome, Firefox and Safari will work best

TIaaS URL for this training: https://usegalaxy.eu/join-training/gcc-biodiversity

Ray Sajulga, Praveen Kumar, Caleb Easterly, Subina Mehta, Thomas McGowan, James Johnson, Pratik Jagtap and Timothy J. Griffin

Willem de Koning, Milad Miladi, Saskia Hiltemann and Bjoern Gruening

Use of RAD-seq, Genotyping by sequencing and similar data for analysis of populations, effects of selection, phylogeography studies.
Prerequisites

• Introduction to Galaxy or equivalent experience
• Quality Contol of HTS Data or prior exposure to HTS data
• A wi-fi enabled laptop with a modern web browser. Google Chrome, Firefox and Safari will work best

TIaaS URL for this training: https://usegalaxy.eu/join-training/gcc-radseq