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Containers and Workflows training materials hackathon

Materials developed at the Containers and Workflows hackathon organised by ELIXIR-BE (VIB) in February and April 2021.

Scientific topics: Computer science

Keywords: Containers, Workflows, eLearning, EeLP

Resource type: Training materials

Containers and Workflows training materials hackathon http://tess.elixir-uk.org/materials/containers-and-workflows-training-materials-hackathon Materials developed at the Containers and Workflows hackathon organised by ELIXIR-BE (VIB) in February and April 2021. Computer science Containers, Workflows, eLearning, EeLP Life Science Researchers Training Designers Training instructors Trainers
Containers & Workflow pipelines workshop

The first day (20 May 2021) is dedicated to Containers (Docker & Singularity) which are great tools for code portability and reproducibility of your analysis. You will learn how to use containers and how to build a container from scratch, share it with others and how to re-use and modify...

Keywords: Containers, Nextflow

Resource type: Training materials

Containers & Workflow pipelines workshop http://tess.elixir-uk.org/materials/containers-workflow-pipelines-workshop The first day (20 May 2021) is dedicated to Containers (Docker & Singularity) which are great tools for code portability and reproducibility of your analysis. You will learn how to use containers and how to build a container from scratch, share it with others and how to re-use and modify existing containers. After an extensive explanation on Docker containers, at the end of the first day, Singularity will be highlighted as well. On the second day (27 May 2021), you will learn how to use Nextflow for building scalable and reproducible bioinformatics pipelines and running them on a personal computer, cluster and cloud. Starting from the basic concepts we will build our own simple pipeline and add new features with every step, all in the new DSL2 language. Containers, Nextflow bioinformaticians
Introduction to Nextflow workshop

workshop materials (mainly) in DSL2 aiming to get familiar with the Nextflow syntax by explaining basic concepts and building a simple RNAseq pipeline. Highlights also reproducibility aspects with adding containers (docker & singularity). Slides available...

Scientific topics: Workflows

Keywords: Nextflow, DSL2

Resource type: Presentation, course materials

Introduction to Nextflow workshop http://tess.elixir-uk.org/materials/introduction-to-nextflow-workshop workshop materials (mainly) in DSL2 aiming to get familiar with the Nextflow syntax by explaining basic concepts and building a simple RNAseq pipeline. Highlights also reproducibility aspects with adding containers (docker & singularity). Slides available [here](https://github.com/vibbits/nextflow-jnj/blob/master/presentation/slidedeck.pdf) Workflows Nextflow, DSL2 bioinformaticians
Introduction to Protein Structure Analysis

This training session will provide the basics of protein structure determination and how this information is stored in databases. We will explore and search in online databases containing protein structure information. With the aid of the Yasara View program we will visualize the structure....

Operations: Visualisation

Keywords: Protein structure visualisation

Resource type: e-learning

Introduction to Protein Structure Analysis http://tess.elixir-uk.org/materials/introduction-to-protein-structure-analysis This training session will provide the basics of protein structure determination and how this information is stored in databases. We will explore and search in online databases containing protein structure information. With the aid of the Yasara View program we will visualize the structure. Different hands-on exercises will allow you to compare the structure of homologues, to predict a structural model of proteins (without any structure information) and to find homologous structures. We will use online tools to quantify various interactions in the structures. ## Objectives * Get to know the data generated from protein structure determination experiments (high-resolution NMR spectroscopy, X-ray crystallography, electron microscopy, ...) and where to get it. * Display protein structure data and compare structures, through the use of Yasara. * Create high-quality graphical representations of the structures. * Calculate the effect of mutations on the stability of your protein. Janick Mathys Protein structure visualisation Life Science Researchers
Reproducible data analysis with RStudio, github and Rmarkdown

Best practices for writing reproducible data-analysis Creating a reproducible and re-usable data-analysis environment with Rstudio Input: https://github.com/vibbits/RDM-LS Output: https://github.com/vibbits/RDM-LS-solution

Scientific topics: Data management, Data architecture, analysis and design

Keywords: Data analysis

Resource type: Presentation

Reproducible data analysis with RStudio, github and Rmarkdown http://tess.elixir-uk.org/materials/reproducible-data-analysis-with-rstudio-github-and-rmarkdown Best practices for writing reproducible data-analysis Creating a reproducible and re-usable data-analysis environment with Rstudio Input: https://github.com/vibbits/RDM-LS Output: https://github.com/vibbits/RDM-LS-solution Data management Data architecture, analysis and design Data analysis life scientists
Data security and encryption

1. Data security 2. Encryption 3. Passwords

Scientific topics: Data management, Data security

Keywords: data encryption

Resource type: Presentation

Data security and encryption http://tess.elixir-uk.org/materials/data-security-and-encryption 1. Data security 2. Encryption 3. Passwords Data management Data security data encryption life scientists
Valorisation and intellectual properties in research data management

### Valorisation and IP * Basics of Tech Transfer and IPR from an academic perspective * Insights as to: * Why is it important when handling and managing research data? * How do IP rights fit in FAIR data principles * When to safeguard data for proprietary protection? * Where/how...

Scientific topics: Data management

Keywords: intellectual property protection

Resource type: Presentation

Valorisation and intellectual properties in research data management http://tess.elixir-uk.org/materials/valorisation-and-interlectual-properties-in-research-data-management ### Valorisation and IP * Basics of Tech Transfer and IPR from an academic perspective * Insights as to: * Why is it important when handling and managing research data? * How do IP rights fit in FAIR data principles * When to safeguard data for proprietary protection? * Where/how share and publish data if valorisation is in scope? Data management intellectual property protection life scientists
Preserve, publish and share your data

- why preserve data - what data should be preserved - how share data - where to deposit your data - Fairsharing, re3data - ELIXIR Core Resources - Data Formats - Generic archives

Scientific topics: Data management, Data submission, annotation, and curation

Keywords: data formats, ELIXIR Core resources, FAIR data submission

Resource type: Presentation

Preserve, publish and share your data http://tess.elixir-uk.org/materials/preserve-publish-and-share-your-data - why preserve data - what data should be preserved - how share data - where to deposit your data - Fairsharing, re3data - ELIXIR Core Resources - Data Formats - Generic archives Data management Data submission, annotation, and curation data formats, ELIXIR Core resources, FAIR data submission life scientists
Reusing existing data

- how to find existing data (OmicsDI, pubmed, BioStudies, Google Data search, Data Management Hub) - licenses - datasets as first-class research products - research software as first-class research products - data citations

Scientific topics: Data management

Keywords: data licenses, software licenses, data journal

Resource type: Presentation

Reusing existing data http://tess.elixir-uk.org/materials/reusing-existing-data - how to find existing data (OmicsDI, pubmed, BioStudies, Google Data search, Data Management Hub) - licenses - datasets as first-class research products - research software as first-class research products - data citations Data management data licenses, software licenses, data journal life scientists
Organising your data: structure and versioning

how to store and organize data safe, easy and efficient - practical recommendation for folder structures and file naming schemes

Scientific topics: Data management

Keywords: data stewardship, data collection

Resource type: Presentation

Organising your data: structure and versioning http://tess.elixir-uk.org/materials/organising-your-data-structure-and-versioning how to store and organize data safe, easy and efficient - practical recommendation for folder structures and file naming schemes Nele Pauwels Data management data stewardship, data collection
FAIRify your data: data documentation and metadata

“Documentation is a love letter that you write to your future self.” Damian Conway (2005) Make your data as useful as possible for “your future self” and others Never forget what you did or how or why you did it Always find beck your precious data (easily) Make data understandable,...

Scientific topics: Data management

Keywords: data documentation, metadata

Resource type: Presentation

FAIRify your data: data documentation and metadata http://tess.elixir-uk.org/materials/fairify-your-data-data-documentation-and-metadata “Documentation is a love letter that you write to your future self.” Damian Conway (2005) Make your data as useful as possible for “your future self” and others Never forget what you did or how or why you did it Always find beck your precious data (easily) Make data understandable, reproducible and reusable by “your future self” and others Avoid misinterpretation Data management data documentation, metadata life scientists
Data Management Plans

dmponline.be - creating data management plans why, what to cover, examples and self-assessment grids

Keywords: Data management planning

Resource type: Presentation

Data Management Plans http://tess.elixir-uk.org/materials/data-management-plans dmponline.be - creating data management plans why, what to cover, examples and self-assessment grids Data management planning life scientists
Privacy and GDPR in the research life cycle

0. The basics 1. Planning your research from a GDPR point of view 2. From planning to collecting your data 3. Structuring and analyzing your data 4. Sharing, publishing, archiving and destroying your data

Scientific topics: Data management

Keywords: GDPR

Resource type: Presentation

Privacy and GDPR in the research life cycle http://tess.elixir-uk.org/materials/privacy-and-gdpr-in-the-research-life-cycle 0. The basics 1. Planning your research from a GDPR point of view 2. From planning to collecting your data 3. Structuring and analyzing your data 4. Sharing, publishing, archiving and destroying your data Data management GDPR life scientists
Research Data Management: Trends and requirements

Paula Oset - Research funders and journal policies

Scientific topics: Data management

Keywords: journal policies, research funding

Resource type: Presentation

Research Data Management: Trends and requirements http://tess.elixir-uk.org/materials/research-data-management-trends-and-requirements Paula Oset - Research funders and journal policies Data management journal policies, research funding life scientists
Introduction to Research Data Management and the data life cycle

RESEARCH DATA MANAGEMENT IN LIFE SCIENCES Introduction to RDM & data lifecycle Thomas Van de Velde (Data steward team Ghent University)

Keywords: research data, data management

Resource type: Presentation

Introduction to Research Data Management and the data life cycle http://tess.elixir-uk.org/materials/introduction-to-research-data-management-and-the-data-life-cycle RESEARCH DATA MANAGEMENT IN LIFE SCIENCES Introduction to RDM & data lifecycle Thomas Van de Velde (Data steward team Ghent University) research data, data management life scientists
Research Data Management in Life Sciences

The content provided via this link was used in the training on 9 and 10 November 2020 organized by Ghent University and Elixir Belgium and VIB in collaboration with Interreg Vlaanderen-Nederland: https://training.vib.be/all-trainings/research-data-management-life-sciences.

Scientific topics: Data management

Resource type: Presentation, Vignette, Video

Research Data Management in Life Sciences http://tess.elixir-uk.org/materials/research-data-management-in-life-sciences The content provided via this link was used in the training on 9 and 10 November 2020 organized by Ghent University and Elixir Belgium and VIB in collaboration with Interreg Vlaanderen-Nederland: https://training.vib.be/all-trainings/research-data-management-life-sciences. Data management Life Science Researchers
Data Management and Writing a Data Management Plan

Writing a Data Management Plan A good data management plan is crucial for any scientist and researcher. In this course, you will learn how to write one. You will find out how you can prepare, handle and share your research data.

Scientific topics: Data management

Resource type: e-learning

Data Management and Writing a Data Management Plan http://tess.elixir-uk.org/materials/data-management-and-writing-a-data-management-plan Writing a Data Management Plan A good data management plan is crucial for any scientist and researcher. In this course, you will learn how to write one. You will find out how you can prepare, handle and share your research data. Geert Bonamie Data management
Scop3P

Scop3P is available as a web-interface for PTM visualisation and can be accessed at https://iomics.ugent.be/scop3p Search Scop3P with Swiss-Prot accession/ID, protein name, PDB ID, ProteomeXchange ID or by keywords

Scop3P http://tess.elixir-uk.org/materials/scop3p Scop3P is available as a web-interface for PTM visualisation and can be accessed at https://iomics.ugent.be/scop3p Search Scop3P with Swiss-Prot accession/ID, protein name, PDB ID, ProteomeXchange ID or by keywords
galaxy.sciensano.be

This training is meant specifically for the “Galaxy @Sciensano” that is available at https://galaxy.sciensano.be/ and serves two purposes. First, it serves as an introduction in how to handle and employ the Galaxy instance hosted by Sciensano. Secondly, is also serves as a tutorial into both the...

Scientific topics: Microbiology, Sequencing, Genomics, Public health and epidemiology, Bioinformatics

Resource type: Video, Tutorial

galaxy.sciensano.be http://tess.elixir-uk.org/materials/galaxy-sciensano-training This training is meant specifically for the “Galaxy @Sciensano” that is available at https://galaxy.sciensano.be/ and serves two purposes. First, it serves as an introduction in how to handle and employ the Galaxy instance hosted by Sciensano. Secondly, is also serves as a tutorial into both the basics of next-generation sequencing data analysis, but also more specialized topics of interest in public health (e.g. AMR detection, cgMLST analysis etc., SNP-based outbreak analysis etc.). The training consists specifically out of a series of training videos that are publicly available on YouTube. Microbiology Sequencing Genomics Public health and epidemiology Bioinformatics Microbiologists Public Health Professionals Life Science Researchers
Bioinformatics Summer School 2019

This one-week intensive summer school in bioinformatics will focus on data analysis and high throughput biology, with a special focus on R/Bioconductor and its application to a wide range of topics across bioinformatics and computational biology. The course is intended for researchers who are...

Scientific topics: Statistics and probability, Omics, RNA-Seq, Proteomics

Operations: Data handling

Bioinformatics Summer School 2019 http://tess.elixir-uk.org/materials/bioinformatics-summer-school-2019 This one-week intensive summer school in bioinformatics will focus on data analysis and high throughput biology, with a special focus on R/Bioconductor and its application to a wide range of topics across bioinformatics and computational biology. The course is intended for researchers who are familiar with omics experimental technologies and their applications in biology, have had some exposure with R, and who want to learn or expand their bioinformatics skills. Martin Morgan Laurent Gatto Janick Mathys Lieven Clement Charlotte Soneson Koen Van den Berge Oliver Crook Statistics and probability Omics RNA-Seq Proteomics PhD students
PLAZA is a plant-oriented online resource for comparative, evolutionary and functional genomics

PLAZA is a plant-oriented online resource for comparative, evolutionary and functional genomics. [Materials](ftp://ftp.psb.ugent.be/pub/plaza/workshop/ELIXIR/)

Scientific topics: Plant biology, Functional genomics, Comparative genomics, Evolutionary biology, Phylogenomics, Genotype and phenotype

Operations: Annotation, Visualisation, Comparison

Keywords: plants, Plants bioinformatics, genomics, Visualisation, Annotation

Resource type: Training materials

PLAZA is a plant-oriented online resource for comparative, evolutionary and functional genomics http://tess.elixir-uk.org/materials/plaza-is-a-plant-oriented-online-resource-for-comparative-evolutionary-and-functional-genomics PLAZA is a plant-oriented online resource for comparative, evolutionary and functional genomics. [Materials](ftp://ftp.psb.ugent.be/pub/plaza/workshop/ELIXIR/) Plant biology Functional genomics Comparative genomics Evolutionary biology Phylogenomics Genotype and phenotype plants, Plants bioinformatics, genomics, Visualisation, Annotation Life Science Researchers plant researchers experimeintal biologist researchers postdoctoral researchers Research Assistants and Research Associates PhD
Probabilistic programming with (R)Stan

Probabilistic models describe how the observed data was generated, and what structure the signal and noise from potentially multiple sources may have. Many classical statistical models are special cases of probabilistic models with special modeling assumptions. Probabilistic models can be...

Scientific topics: Statistics and probability

Probabilistic programming with (R)Stan http://tess.elixir-uk.org/materials/probabilistic-programming-with-r-stan Probabilistic models describe how the observed data was generated, and what structure the signal and noise from potentially multiple sources may have. Many classical statistical models are special cases of probabilistic models with special modeling assumptions. Probabilistic models can be implemented, improved, and critizised in a flexible, explicit and transparent manner, and the analysis can be supported with prior information about the data. This 1-day course provides an introduction to Bayesian/probabilistic models. We will implement standard linear models based on the rstanarm package of the R statistical programming environment and readily available example data sets. The workshop is an ideal opportunity to familiarize yourself with the basic ideas in probabilistic modeling such as prior information, likelihood, model criticism and validation, as well as some of the available tools. At the end, you should be able to implement basic probabilistic models yourself, and understand their relative advantages and pitfalls compared to their classical alternatives. Statistics and probability Life Science Researchers PhD students beginner bioinformaticians post-docs 2016-04-22
Image Ethics and Poster Design

The image ethics part handles on the theoretical aspects of image manipulation, the mistakes people make and how to avoid image fraud. VIB has guidelines for acceptable scientific image manipulations. Not all manipulations are scientifically correct. There are manipulations that fall within the...

Scientific topics: Image

Image Ethics and Poster Design http://tess.elixir-uk.org/materials/image-ethics-and-poster-design The image ethics part handles on the theoretical aspects of image manipulation, the mistakes people make and how to avoid image fraud. VIB has guidelines for acceptable scientific image manipulations. Not all manipulations are scientifically correct. There are manipulations that fall within the scope of scientific misconduct, because they result in misrepresentation of the data. Such misrepresentation makes it impossible for others to interpret the data correctly, or worse, leads to conclusions that are not correct. The second part of this course deals with poster design. Scientific posters are a resume of a piece or timespan of research on one square meter of paper. They are best compared to slides for oral presentations, not a written document. Posters can’t convey detailed evidence like scientific articles, it must visualize a message on its own. When standing a meter away from a poster you hardly feel like reading much text, especially when the author/designer stands next to it. A poster must bring that message without requiring oral explanation, but with as little text as possible. Prerequisites Participants must have experience with GIMP and Inkscape. Schedule See the TRAINING AT VIB website for a detailed schedule of this training. Training material Not available Links Not available Scientific topics Image data Target audience Life Science Researchers, PhD students, post-docs, beginner bioinformaticians   Image Life Science Researchers PhD students beginner bioinformaticians post-docs 2016-04-22
Analysis of metabolome data

This training will focus on the processing of raw data obtained via either Gas Chromatography- (GC) or Liquid Chromatography- (LC) mass spectrometry (MS). In addition, based on the comparative analysis between two sample sets (e.g. control vs treatment), the subsequent identification of...

Scientific topics: Metabolomics

Analysis of metabolome data http://tess.elixir-uk.org/materials/analysis-of-metabolome-data This training will focus on the processing of raw data obtained via either Gas Chromatography- (GC) or Liquid Chromatography- (LC) mass spectrometry (MS). In addition, based on the comparative analysis between two sample sets (e.g. control vs treatment), the subsequent identification of differential metabolites will be introduced. Afterwards, the trainee should be able to perform independently a comparative analysis of raw metabolome data and to pinpoint the well-known metabolites in the chromatogram. Metabolomics Life Science Researchers PhD students beginner bioinformaticians post-docs 2016-04-22
Advanced FlowJo training

The training will start with an introduction to FlowJo v10 but there will be enough details and features to make it worth even for advanced users. In the afternoon, advanced tools in FlowJo and new plugins (tSNE, SPADE) will be presented showing you how to work in high...

Advanced FlowJo training http://tess.elixir-uk.org/materials/advanced-flowjo-training The training will start with an introduction to FlowJo v10 but there will be enough details and features to make it worth even for advanced users. In the afternoon, advanced tools in FlowJo and new plugins (tSNE, SPADE) will be presented showing you how to work in high dimensionality. Prerequisites Participants must have experience with FlowJo. Schedule See the TRAINING AT VIB website for a detailed schedule of this training. Training material Not available Links Not available Scientific topics FlowJo Target audience Life Science Researchers, PhD students, post-docs, beginner bioinformaticians Life Science Researchers PhD students beginner bioinformaticians post-docs 2016-04-22
A tour of machine learning - classification

Machine learning has become ubiquitous in biotechnology (as in many other fields), fueled largely by the increasing availability and amount of data. Learning algorithms can figure out how to perform important tasks by generalizing examples. Typical applications are diagnoses/prognoses,...

Scientific topics: Machine learning

A tour of machine learning - classification http://tess.elixir-uk.org/materials/a-tour-of-machine-learning-classification Machine learning has become ubiquitous in biotechnology (as in many other fields), fueled largely by the increasing availability and amount of data. Learning algorithms can figure out how to perform important tasks by generalizing examples. Typical applications are diagnoses/prognoses, gene/protein annotation, drug design, image recognition, text mining and many others. However, building successful machine learning models requires a substantial amount of “black art” that is hard to find in textbooks. This course is an interactive Jupyter Notebook (Python) that will teach you how to build successful machine learning models. No background in machine learning is assumed, just a keen interest. Machine learning Life Science Researchers PhD students beginner bioinformaticians post-docs 2016-04-22
Deep Learning using a Convolutional Neural Network

This course part focuses on a recent machine learning method known as deep learning that emerged as a promising disruptive approach, allowing knowledge discovery from large datasets in an unprecedented effectiveness and efficiency. It is particularly relevant in research areas, which are not...

Scientific topics: Machine learning

Resource type: Video

Deep Learning using a Convolutional Neural Network http://tess.elixir-uk.org/materials/deep-learning-using-a-convolutional-neural-network This course part focuses on a recent machine learning method known as deep learning that emerged as a promising disruptive approach, allowing knowledge discovery from large datasets in an unprecedented effectiveness and efficiency. It is particularly relevant in research areas, which are not accessible through modelling and simulation often performed in HPC. Traditional learning, which was introduced in the 1950s and became a data-driven paradigm in the 90s, is usually based on an iterative process of feature engineering, learning, and modelling. Although successful on many tasks, the resulting models are often hard to transfer to other datasets and research areas. Machine learning PhD students Post Docs
Introduction to Machine Learning Algorithms

This course offers basics of analysing datasets with machine learning algorithms and data mining techniques in order to understand foundations of learning from large quantities of data.

Scientific topics: Machine learning

Resource type: Video

Introduction to Machine Learning Algorithms http://tess.elixir-uk.org/materials/introduction-to-machine-learning-algorithms-b1434ce7-b934-4b48-af7c-0274e2c37815 This course offers basics of analysing datasets with machine learning algorithms and data mining techniques in order to understand foundations of learning from large quantities of data. Machine learning PhD students Post Docs
Introduction to Machine Learning Algorithms

This course offers basics of analysing datasets with machine learning algorithms and data mining techniques in order to understand foundations of learning from large quantities of data.

Scientific topics: Machine learning

Resource type: PDF

Introduction to Machine Learning Algorithms http://tess.elixir-uk.org/materials/introduction-to-machine-learning-algorithms This course offers basics of analysing datasets with machine learning algorithms and data mining techniques in order to understand foundations of learning from large quantities of data. Machine learning PhD students Post Docs
Introduction to Biopython

Biopython is the best-known Python library to process biological data. This training is aimed to empower you to use Biopython to make your research more efficient. The first day of the training is to give an overview of Biopython. You are going to start with your first steps in Biopython on the...

Scientific topics: Software engineering

Introduction to Biopython http://tess.elixir-uk.org/materials/introduction-to-biopython-8ccf2441-bd7d-46f2-84f8-c2b123844a23 Biopython is the best-known Python library to process biological data. This training is aimed to empower you to use Biopython to make your research more efficient. The first day of the training is to give an overview of Biopython. You are going to start with your first steps in Biopython on the command line. Afterwards you will take a tour of the most important components: sequences, NCBI queries, BLAST, trees, and 3D structures. You will try each of these modules on practical examples. Please don't hesitate to ask questions about Python basics or particular data formats (e.g. XML or NGS data). The second day of the training is to broaden your perspective: What other features does the library have? How can you use the documentation effectively? What is Biopython not capable of? What can I do to visualize my data? Are there alternatives? If you have your own data that you would like to work on with Biopython in more detail, there is room for that. For us, the most important thing is to identify concrete Python modules and functions that help you to get your research done. Participants are encouraged to submit a description of their research topic and/or the questions they would like to answer with Biopython. Additionally, participants can bring their own data that they would like to process in Python to the training. Software engineering Life Science Researchers PhD students beginner bioinformaticians post-docs 2016-04-22 2017-10-09