Register training material
105 material found

Licence: Creative Commons Attributio... 


WEBINAR: Portable, reproducible and scalable bioinformatics workflows using Nextflow and Pawsey Nimbus Cloud

This record includes training materials associated with the Australian BioCommons webinar ‘Portable, reproducible and scalable bioinformatics workflows using Nextflow and Pawsey Nimbus Cloud’. This webinar took place on 20 September 2022.

Event description 

Bioinformatics workflows can support...

Keywords: Bioinformatics, Workflows, Nextflow, Containerisation

WEBINAR: Portable, reproducible and scalable bioinformatics workflows using Nextflow and Pawsey Nimbus Cloud https://dresa.org.au/materials/webinar-portable-reproducible-and-scalable-bioinformatics-workflows-using-nextflow-and-pawsey-nimbus-cloud This record includes training materials associated with the Australian BioCommons webinar ‘Portable, reproducible and scalable bioinformatics workflows using Nextflow and Pawsey Nimbus Cloud’. This webinar took place on 20 September 2022. Event description  Bioinformatics workflows can support portable, reproducible and scalable analysis of omics datasets but using workflows can be challenging for both beginners and experienced bioinformaticians. Beginners face a steep learning curve to be able to build and deploy their own bioinformatics workflows while those with more experience face challenges productionising and scaling code for custom workflows and big data.  Bioinformaticians across the world are using Nextflow to build and manage workflows. Many of these workflows are shared for others to use and supported by the community via nf-co.re. So far, 39 workflows for omics data are available with another 23 under development. These workflows cover common analyses such as RNAseq, mapping, variant calling, single cell transcriptomics and more and can be easily deployed by anyone, regardless of skill level. In this webinar, Nandan Deshpande from the Sydney Informatics Hub, University of Sydney, will discuss how you can deploy freely available Nextflow (nf.co-re) bioinformatics workflows with a single command. We describe how you can quickly get started deploying these workflows using Pawsey Nimbus Cloud. For advanced users, we introduce you to Nextflow concepts to get you started with building your own workflows that will save you time and support reproducible, portable and scalable analysis. In the latter half of the webinar, Sarah Beecroft from the Pawsey Supercomputing Research Centre will talk about their Nimbus Cloud systems. While Nextflow supports portability and can run on many computing infrastructures, we describe why we specifically love using Nimbus with Nextflow for many bioinformatics projects. We will describe some of the nf.co-re workflows that we have used on Nimbus and the research outcomes. We will also cover when not to use Nimbus and the alternatives we recommend.   Materials are shared under a Creative Commons Attribution 4.0 International agreement unless otherwise specified and were current at the time of the event. Files and materials included in this record: Event metadata (PDF): Information about the event including, description, event URL, learning objectives, prerequisites, technical requirements etc. Index of training materials (PDF): List and description of all materials associated with this event including the name, format, location and a brief description of each file. Nextflow_Nimbus_slides (PDF): A PDF copy of the slides presented during the webinar. Materials shared elsewhere: A recording of this webinar is available on the Australian BioCommons YouTube Channel: https://youtu.be/VnLX63yXbJU Melissa Burke (melissa@biocommons.org.au) Bioinformatics, Workflows, Nextflow, Containerisation
WORKSHOP: Single cell RNAseq analysis in R

This record includes training materials associated with the Australian BioCommons workshop ‘Single cell RNAseq analysis in R’. This workshop took place over two, 3.5 hour sessions on 22 and 3 August 2022.

Event description

Analysis and interpretation of single cell RNAseq (scRNAseq) data...

Keywords: Bioinformatics, Analysis, Transcriptomics, R software, Single cell RNAseq, scRNAseq

WORKSHOP: Single cell RNAseq analysis in R https://dresa.org.au/materials/workshop-single-cell-rnaseq-analysis-in-r This record includes training materials associated with the Australian BioCommons workshop ‘Single cell RNAseq analysis in R’. This workshop took place over two, 3.5 hour sessions on 22 and 3 August 2022. Event description Analysis and interpretation of single cell RNAseq (scRNAseq) data requires dedicated workflows. In this hands-on workshop we will show you how to perform single cell analysis using Seurat - an R package for QC, analysis, and exploration of single-cell RNAseq data.  We will discuss the ‘why’ behind each step and cover reading in the count data, quality control, filtering, normalisation, clustering, UMAP layout and identification of cluster markers. We will also explore various ways of visualising single cell expression data. This workshop is presented by the Australian BioCommons and Queensland Cyber Infrastructure Foundation (QCIF) with the assistance of a network of facilitators from the national Bioinformatics Training Cooperative.   Materials are shared under a Creative Commons Attribution 4.0 International agreement unless otherwise specified and were current at the time of the event. Files and materials included in this record: Event metadata (PDF): Information about the event including, description, event URL, learning objectives, prerequisites, technical requirements etc. Index of training materials (PDF): List and description of all materials associated with this event including the name, format, location and a brief description of each file. scRNAseq_Slides (PDF): Slides used to introduce topics scRNAseq_Schedule (PDF): A breakdown of the topics and timings for the workshop scRNAseq_Resources (PDF): A list of resources recommended by trainers and participants scRNAseq_QandA(PDF): Archive of questions and their answers from the workshop Slack Channel.   Materials shared elsewhere: This workshop follows the tutorial ‘scRNAseq Analysis in R with Seurat’ https://swbioinf.github.io/scRNAseqInR_Doco/index.html This material is based on the introductory Guided Clustering Tutorial tutorial from Seurat. It is also drawing from a similar workshop held by Monash Bioinformatics Platform Single-Cell-Workshop, with material here. Melissa Burke (melissa@biocommons.org.au) Bioinformatics, Analysis, Transcriptomics, R software, Single cell RNAseq, scRNAseq
WEBINAR: Getting started with whole genome mapping and variant calling on the command line

This record includes training materials associated with the Australian BioCommons webinar ‘Getting started with whole genome mapping and variant calling on the command line’. This webinar took place on 24 August 2022.

Event description 

Life scientists are increasingly using whole genome...

Keywords: Genome mapping, Variant calling, Bioinformatics, Workflows

WEBINAR: Getting started with whole genome mapping and variant calling on the command line https://dresa.org.au/materials/webinar-getting-started-with-whole-genome-mapping-and-variant-calling-on-the-command-line This record includes training materials associated with the Australian BioCommons webinar ‘Getting started with whole genome mapping and variant calling on the command line’. This webinar took place on 24 August 2022. Event description  Life scientists are increasingly using whole genome sequencing (WGS) to ask and answer research questions across the tree of life. Before any of this work can be done, there is the essential but challenging task of processing raw sequencing data. Processing WGS data is a computationally challenging, multi-step process used to create a map of an individual’s genome and identify genetic variant sites. The tools you use in this process and overall workflow design can look very different for different researchers, it all depends on your dataset and the research questions you’re asking. Luckily, there are lots of existing WGS processing tools and pipelines out there, but knowing where to start and what your specific needs are is hard work, no matter how experienced you are.  In this webinar we will walk through the essential steps and considerations for researchers who are running and building reproducible WGS mapping and variant calling pipelines at the command line interface. We will discuss how to choose and evaluate a pipeline that is right for your dataset and research questions, and how to get access to the compute resources you need Materials are shared under a Creative Commons Attribution 4.0 International agreement unless otherwise specified and were current at the time of the event. Files and materials included in this record: Event metadata (PDF): Information about the event including, description, event URL, learning objectives, prerequisites, technical requirements etc. Index of training materials (PDF): List and description of all materials associated with this event including the name, format, location and a brief description of each file. WGS mapping and variant calling _slides (PDF): A PDF copy of the slides presented during the webinar.   Materials shared elsewhere: A recording of this webinar is available on the Australian BioCommons YouTube Channel: https://youtu.be/Q2EceFyizio Melissa Burke (melissa@biocommons.org.au) Genome mapping, Variant calling, Bioinformatics, Workflows
WEBINAR: bio.tools - making it easier to find, understand and cite biological tools and software

This record includes training materials associated with the Australian BioCommons webinar ‘bio.tools - making it easier to find, understand and cite biological tools and software’. This webinar took place on 21 June 2022.

Event description 

bio.tools provides easy access to essential scientific...

Keywords: Bioinformatics, Research software, EDAM, Workflows, FAIR

WEBINAR: bio.tools - making it easier to find, understand and cite biological tools and software https://dresa.org.au/materials/webinar-bio-tools-making-it-easier-to-find-understand-and-cite-biological-tools-and-software-9180e32a-f4f5-4993-a90a-a9bfcfafd4f3 This record includes training materials associated with the Australian BioCommons webinar ‘bio.tools - making it easier to find, understand and cite biological tools and software’. This webinar took place on 21 June 2022. Event description  bio.tools provides easy access to essential scientific and technical information about software, command-line tools, databases and services. It’s backed by ELIXIR, the European Infrastructure for Biological Information, and is being used in Australia to register software (e.g. Galaxy Australia, prokka). It underpins the information provided in the Australian BioCommons discovery service ToolFinder. Hans Ienasescu and Matúš Kalaš join us to explain how bio.tools uses a community driven, open science model to create this collection of resources and how it makes it easier to find, understand, utilise and cite them. They’ll delve into how bio.tools is using standard semantics (e.g. the EDAM ontology) and syntax (e.g. biotoolsSchema) to enrich the annotation and description of tools and resources. Finally, we’ll see how the community can contribute to bio.tools and take advantage of its key features to share and promote their own research software.   Materials are shared under a Creative Commons Attribution 4.0 International agreement unless otherwise specified and were current at the time of the event. Files and materials included in this record: Event metadata (PDF): Information about the event including, description, event URL, learning objectives, prerequisites, technical requirements etc. Index of training materials (PDF): List and description of all materials associated with this event including the name, format, location and a brief description of each file. biotools_EDAM_slides (PDF): A PDF copy of the slides presented during the webinar.   Materials shared elsewhere: A recording of this webinar is available on the Australian BioCommons YouTube Channel: https://youtu.be/K0J4_bAUG3Y Melissa Burke (melissa@biocommons.org.au) Bioinformatics, Research software, EDAM, Workflows, FAIR
Introduction to Jupyter Notebooks

This workshop will introduce you to Jupyter Notebooks, a digital tool that has exploded in popularity in recent years for those working with data.

You will learn what they are, what they do and why you might like to use them. It is an introductory set of lessons for those who are brand new,...

Keywords: jupyter, Introductory, training material, CloudStor, markdown, Python, R

Resource type: tutorial

Introduction to Jupyter Notebooks https://dresa.org.au/materials/introduction-to-jupyter-notebooks This workshop will introduce you to Jupyter Notebooks, a digital tool that has exploded in popularity in recent years for those working with data. You will learn what they are, what they do and why you might like to use them. It is an introductory set of lessons for those who are brand new, have little or no knowledge of coding and computational methods in research. This workshop is targeted at those who are absolute beginners or ‘tech-curious’. It includes a hands-on component, using basic programming commands, but requires no previous knowledge of programming. sara.king@aarnet.edu.au Mason, Ingrid jupyter, Introductory, training material, CloudStor, markdown, Python, R
WORKSHOP: R: fundamental skills for biologists

This record includes training materials associated with the Australian BioCommons workshop ‘R: fundamental skills for biologists’. This workshop took place over four, three-hour sessions on 1, 8, 15 and 22 June 2022.

Event description

Biologists need data analysis skills to be able to...

Keywords: Bioinformatics, Analysis, Statistics, R software, RStudio, Data visualisation

WORKSHOP: R: fundamental skills for biologists https://dresa.org.au/materials/workshop-r-fundamental-skills-for-biologists This record includes training materials associated with the Australian BioCommons workshop ‘R: fundamental skills for biologists’. This workshop took place over four, three-hour sessions on 1, 8, 15 and 22 June 2022. **Event description** Biologists need data analysis skills to be able to interpret, visualise and communicate their research results. While Excel can cover some data analysis needs, there is a better choice, particularly for large and complex datasets.  R is a free, open-source software and programming language that enables data exploration, statistical analysis, visualisation and more. The large variety of R packages available for analysing biological data make it a robust and flexible option for data of all shapes and sizes.  Getting started can be a little daunting for those without a background in statistics and programming. In this workshop we will equip you with the foundations for getting the most out of R and RStudio, an interactive way of structuring and keeping track of your work in R. Using biological data from a model of influenza infection, you will learn how to efficiently and reproducibly organise, read, wrangle, analyse, visualise and generate reports from your data in R. Topics covered in this workshop include: - Spreadsheets, organising data and first steps with R - Manipulating and analysing data with dplyr - Data visualisation - Summarized experiments and getting started with Bioconductor This workshop is presented by the Australian BioCommons and Saskia Freytag from WEHI  with the assistance of a network of facilitators from the national Bioinformatics Training Cooperative. Materials are shared under a Creative Commons Attribution 4.0 International agreement unless otherwise specified and were current at the time of the event. **Files and materials included in this record:** - Event metadata (PDF): Information about the event including, description, event URL, learning objectives, prerequisites, technical requirements etc. - Index of training materials (PDF): List and description of all materials associated with this event including the name, format, location and a brief description of each file. - Schedule (PDF): A breakdown of the topics and timings for the workshop - Recommended resources (PDF): A list of resources recommended by trainers and participants - Q_and_A(PDF): Archive of questions and their answers from the workshop Slack Channel. **Materials shared elsewhere:** This workshop follows the tutorial ‘Introduction to data analysis with R and Bioconductor’ which is publicly available. https://saskiafreytag.github.io/biocommons-r-intro/ This is derived from material produced as part of The Carpentries Incubator project https://carpentries-incubator.github.io/bioc-intro/ Melissa Burke (melissa@biocommons.org.au) Bioinformatics, Analysis, Statistics, R software, RStudio, Data visualisation
WEBINAR: bio.tools - making it easier to find, understand and cite biological tools and software

This record includes training materials associated with the Australian BioCommons webinar ‘bio.tools - making it easier to find, understand and cite biological tools and software’. This webinar took place on 21 June 2022.

Event description

bio.tools provides easy access to essential...

Keywords: Bioinformatics, Research software, EDAM, Workflows, FAIR

WEBINAR: bio.tools - making it easier to find, understand and cite biological tools and software https://dresa.org.au/materials/webinar-bio-tools-making-it-easier-to-find-understand-and-cite-biological-tools-and-software This record includes training materials associated with the Australian BioCommons webinar ‘bio.tools - making it easier to find, understand and cite biological tools and software’. This webinar took place on 21 June 2022. **Event description** bio.tools provides easy access to essential scientific and technical information about software, command-line tools, databases and services. It’s backed by ELIXIR, the European Infrastructure for Biological Information, and is being used in Australia to register software (e.g. Galaxy Australia, prokka). It underpins the information provided in the Australian BioCommons discovery service ToolFinder. Hans Ienasescu and Matúš Kalaš join us to explain how bio.tools uses a community driven, open science model to create this collection of resources and how it makes it easier to find, understand, utilise and cite them. They’ll delve into how bio.tools is using standard semantics (e.g. the EDAM ontology) and syntax (e.g. biotoolsSchema) to enrich the annotation and description of tools and resources. Finally, we’ll see how the community can contribute to bio.tools and take advantage of its key features to share and promote their own research software.   Materials are shared under a Creative Commons Attribution 4.0 International agreement unless otherwise specified and were current at the time of the event. **Files and materials included in this record:** - Event metadata (PDF): Information about the event including, description, event URL, learning objectives, prerequisites, technical requirements etc. - Index of training materials (PDF): List and description of all materials associated with this event including the name, format, location and a brief description of each file. - biotools_EDAM_slides (PDF): A PDF copy of the slides presented during the webinar. **Materials shared elsewhere:** A recording of this webinar is available on the Australian BioCommons YouTube Channel: https://youtu.be/K0J4_bAUG3Y Melissa Burke (melissa@biocommons.org.au) Bioinformatics, Research software, EDAM, Workflows, FAIR
Research Data Management Techniques

Are you drowning in research data? Do you want to know where you should be storing your data? Are you required to comply with funding body data management requirements, but don't know how?

This workshop is ideal for researchers who want to know how research data management can support project...

Keywords: Data Management, Data Management

Research Data Management Techniques https://dresa.org.au/materials/research-data-management-techniques Are you drowning in research data? Do you want to know where you should be storing your data? Are you required to comply with funding body data management requirements, but don't know how? This workshop is ideal for researchers who want to know how research data management can support project success and are interested in research data management services and support available at their institution. Combining slide-based background material, discussions, and case studies this workshop will equip participants with best practices for managing their valuable research data. #### You'll learn: - How to manage research data according to legal, statutory, ethical, funding body and university requirements - Approaches to planning, collecting, organising, managing, storing, backing up, preserving, and sharing your data - Services supporting research data at your institution #### Prerequisites: The course has no prerequisites. **For more information, please click [here](https://intersect.org.au/training/course/rdmt001).** training@intersect.org.au Data Management, Data Management
Databases and SQL

A relational database is an extremely efficient, fast and widespread means of storing structured data, and Structured Query Language (SQL) is the standard means for reading from and writing to databases. Databases use multiple tables, linked by well-defined relationships, to store large amounts...

Keywords: Data Management, SQL

Databases and SQL https://dresa.org.au/materials/databases-and-sql A relational database is an extremely efficient, fast and widespread means of storing structured data, and Structured Query Language (SQL) is the standard means for reading from and writing to databases. Databases use multiple tables, linked by well-defined relationships, to store large amounts of data without needless repetition while maintaining the integrity of your data. Moving from spreadsheets and text documents to a structured relational database can be a steep learning curve, but one that will reward you many times over in speed, efficiency and power. Developed using the researcher-focused training modules from the highly regarded Software Carpentry Foundation. #### You'll learn: - Understand and compose a query using SQL - Use the SQL syntax to select, sort and filter data - Calculate new values from existing data - Aggregate data into sums, averages, and other operations - Combine data from multiple tables - Design and build your own relational databases #### Prerequisites: The course has no prerequisites. **For more information, please click [here](https://intersect.org.au/training/course/sql101).** training@intersect.org.au Data Management, SQL
Unix Shell and Command Line Basics

The Unix environment is incredibly powerful but quite daunting to the newcomer. Command line confidence unlocks powerful computing resources beyond the desktop, including virtual machines and High Performance Computing. It enables repetitive tasks to be automated. And it comes with a swag of...

Keywords: Research Computing, Unix

Unix Shell and Command Line Basics https://dresa.org.au/materials/unix-shell-and-command-line-basics The Unix environment is incredibly powerful but quite daunting to the newcomer. Command line confidence unlocks powerful computing resources beyond the desktop, including virtual machines and High Performance Computing. It enables repetitive tasks to be automated. And it comes with a swag of handy tools that can be combined in powerful ways. Getting started is the hardest part, but our helpful instructors are there to demystify Unix as you get to work running programs and writing scripts on the command line. Every attendee is given a dedicated training environment for the duration of the workshop, with all software and data fully loaded and ready to run. We teach this course within a GNU/Linux environment. This is best characterised as a Unix-like environment. We teach how to run commands within the Bash Shell. The skills you'll learn at this course are generally transferable to other Unix environments. #### You'll learn: - Navigate and work with files and directories (folders) - Use a selection of essential tools - Combine data and tools to build a processing workflow - Automate repetitive analysis using the command line #### Prerequisites: The course has no prerequisites. **For more information, please click [here](https://intersect.org.au/training/course/unix101).** training@intersect.org.au Research Computing, Unix
Collecting Web Data

Web scraping is a technique for extracting information from websites. This can be done manually but it is usually faster, more efficient and less error-prone if it can be automated.

Web scraping allows you to convert non-tabular or poorly structured data into a usable, structured format, such as...

Keywords: Data Management, Python

Collecting Web Data https://dresa.org.au/materials/collecting-web-data Web scraping is a technique for extracting information from websites. This can be done manually but it is usually faster, more efficient and less error-prone if it can be automated. Web scraping allows you to convert non-tabular or poorly structured data into a usable, structured format, such as a .csv file or spreadsheet. But scraping is about more than just acquiring data: it can help you track changes to data online, and help you archive data. In short, it's a skill worth learning. So join us for this web scraping workshop to learn web scraping, using the researcher-focused training modules from the highly regarded Software Carpentry Foundation. #### You'll learn: - The concept of structured data - The use of XPath queries on HTML document - How to scrape data using browser extensions - How to scrape using Python and Scrapy - How to automate the scraping of multiple web pages #### Prerequisites: A good knowledge of the basic concepts and techniques in Python. Consider taking our [Learn to Program: Python](https://intersect.org.au/training/course/python101/) and [Python for Research](https://intersect.org.au/training/course/python110/) courses to come up to speed beforehand. **For more information, please click [here](https://intersect.org.au/training/course/webdata201).** training@intersect.org.au Data Management, Python
Version Control with Git

Have you mistakenly overwritten programs or data and want to learn techniques to avoid repeating the loss? Version control systems are one of the most powerful tools available for avoiding data loss and enabling reproducible research. While the learning curve can be steep, our trainers are there...

Keywords: Data Management, Git

Version Control with Git https://dresa.org.au/materials/version-control-with-git Have you mistakenly overwritten programs or data and want to learn techniques to avoid repeating the loss? Version control systems are one of the most powerful tools available for avoiding data loss and enabling reproducible research. While the learning curve can be steep, our trainers are there to answer all your questions while you gain hands on experience in using Git, one of the most popular version control systems available. Join us for this workshop where we cover the fundamentals of version control using the researcher-focused training modules from the highly regarded Software Carpentry Foundation. #### You'll learn: - keep versions of data, scripts, and other files - examine commit logs to find which files were changed when - restore earlier versions of files - compare changes between versions of a file - push your versioned files to a remote location, for backup and to facilitate collaboration #### Prerequisites: The course has no prerequisites. **For more information, please click [here](https://intersect.org.au/training/course/git101).** training@intersect.org.au Data Management, Git
Learn to Program: MATLAB

MATLAB is an incredibly powerful programming environment with a rich set of analysis toolkits. But what if you're just getting started - with MATLAB and, more generally, with programming?

Nothing beats a hands-on, face-to-face training session to get you past the inevitable syntax errors!

So...

Keywords: Programming, MATLAB

Learn to Program: MATLAB https://dresa.org.au/materials/learn-to-program-matlab MATLAB is an incredibly powerful programming environment with a rich set of analysis toolkits. But what if you're just getting started - with MATLAB and, more generally, with programming? Nothing beats a hands-on, face-to-face training session to get you past the inevitable syntax errors! So join us for this live coding workshop where we write programs that produce results, using the researcher-focused training modules from the highly regarded Software Carpentry Foundation. #### You'll learn: - Introduction to the MATLAB interface for programming - Basic syntax and data types in MATLAB - How to load external data into MATLAB - Creating functions (FUNCTIONS) - Repeating actions and analysing multiple data sets (LOOPS) - Making choices (IF STATEMENTS – CONDITIONALS) - Ways to visualise data in MATLAB #### Prerequisites: No prior experience with programming needed to attend this course. We strongly recommend attending the Start Coding without Hesitation: Programming Languages Showdown and Thinking like a computer: The Fundamentals of Programming webinars. Recordings of previously delivered webinars can be found [here](https://intersect.org.au/training/webinars/). **For more information, please click [here](https://intersect.org.au/training/course/matlab101).** training@intersect.org.au Programming, MATLAB
Learn to Program: Python

Python has deservedly become a popular language for scientific computing. It has all the friendly features and conveniences you'd expect of a modern programming language, and also a rich set of libraries for working with data.

We teach using Jupyter notebooks, which allow program code, results,...

Keywords: Programming, Python

Learn to Program: Python https://dresa.org.au/materials/learn-to-program-python Python has deservedly become a popular language for scientific computing. It has all the friendly features and conveniences you'd expect of a modern programming language, and also a rich set of libraries for working with data. We teach using Jupyter notebooks, which allow program code, results, visualisations and documentation to be blended seamlessly. Perfect for sharing insights with others while producing reproducible research. Join us for this live coding workshop where we write programs that produce results, using the researcher-focused training modules from the highly regarded Software Carpentry Foundation. #### You'll learn: - Introduction to the JupyterLab interface for programming - Basic syntax and data types in Python - How to load external data into Python - Creating functions (FUNCTIONS) - Repeating actions and anylsing multiple data sets (LOOPS) - Making choices (IF STATEMENTS - CONDITIONALS) - Ways to visualise data in Python #### Prerequisites: No prior experience with programming needed to attend this course. We strongly recommend attending the Start Coding without Hesitation: Programming Languages Showdown and Thinking like a computer: The Fundamentals of Programming webinars. Recordings of previously delivered webinars can be found [here](https://intersect.org.au/training/webinars/). **For more information, please click [here](https://intersect.org.au/training/course/python101).** training@intersect.org.au Programming, Python
Python for Research

Python has deservedly become a popular language for scientific computing. It has all the friendly features and conveniences you'd expect of a modern programming language, and also a rich set of libraries for working with data.

This workshop is an introduction to data structures (DataFrames using...

Keywords: Programming, Python

Python for Research https://dresa.org.au/materials/python-for-research Python has deservedly become a popular language for scientific computing. It has all the friendly features and conveniences you'd expect of a modern programming language, and also a rich set of libraries for working with data. This workshop is an introduction to data structures (DataFrames using the pandas library) and visualisation (using the matplotlib library) in Python. The targeted audience for this workshop is researchers who are already familiar with the basic concepts in programming such as loops, functions, and conditionals. We teach using Jupyter notebooks, which allow program code, results, visualisations and documentation to be blended seamlessly. Perfect for sharing insights with others while producing reproducible research. Join us for this live coding workshop where we write programs that produce results, using the researcher-focused training modules from the highly regarded Software Carpentry Foundation. #### You'll learn: - Introduction to Libraries and Built-in Functions in Python - Introduction to DataFrames using the pandas library - Reading and writing data in DataFrames - Selecting values in DataFrames - Quick introduction to Plotting using the matplotlib library #### Prerequisites: [Learn to Program: Python](https://intersect.org.au/training/course/python101/) or any of the [Learn to Program: R](https://intersect.org.au/training/course/r101/), [Learn to Program: MATLAB](https://intersect.org.au/training/course/matlab101/) or [Learn to Program: Julia](https://intersect.org.au/training/course/julia101/), needed to attend this course. If you already have some experience with programming, please check the topics covered in the [Learn to Program: Python](https://intersect.org.au/training/course/python101/) course to ensure that you are familiar with the knowledge needed for this course. **For more information, please click [here](https://intersect.org.au/training/course/python110).** training@intersect.org.au Programming, Python
Data Manipulation in Python

Python has deservedly become a popular language for scientific computing. It has all the friendly features and conveniences you'd expect of a modern programming language, and also a rich set of libraries for working with data.

In this workshop, you will explore DataFrames in depth (using the...

Keywords: Programming, Python

Data Manipulation in Python https://dresa.org.au/materials/data-manipulation-in-python Python has deservedly become a popular language for scientific computing. It has all the friendly features and conveniences you'd expect of a modern programming language, and also a rich set of libraries for working with data. In this workshop, you will explore DataFrames in depth (using the pandas library), learn how to manipulate, explore and get insights from your data (Data Manipulation), as well as how to deal with missing values and how to combine multiple datasets. We teach using Jupyter notebooks, which allow program code, results, visualisations and documentation to be blended seamlessly. Perfect for sharing insights with others while producing reproducible research. Join us for this live coding workshop where we write programs that produce results, using the researcher-focused training modules from the highly regarded Software Carpentry Foundation. #### You'll learn: - Working with pandas DataFrames - Indexing, slicing and subsetting in pandas DataFrames - Missing data values - Combine multiple pandas DataFrames #### Prerequisites: Either [Learn to Program: Python](https://intersect.org.au/training/course/python101/) or [Learn to Program: Python](https://intersect.org.au/training/course/python101/) and [Python for Research](https://intersect.org.au/training/course/python110/) needed to attend this course. If you already have experience with programming, please check the topics covered in the [Learn to Program: Python](https://intersect.org.au/training/course/python101/) and [Python for Research](https://intersect.org.au/training/course/python110/) courses to ensure that you are familiar with the knowledge needed for this course. **For more information, please click [here](https://intersect.org.au/training/course/python201).** training@intersect.org.au Programming, Python
Learn to Program: R

R is quickly gaining popularity as a programming language of choice for statisticians, data scientists and researchers. It has an excellent ecosystem including the powerful RStudio development environment and the Shiny web application framework.

But getting started with R can be challenging,...

Keywords: Programming, R

Learn to Program: R https://dresa.org.au/materials/learn-to-program-r R is quickly gaining popularity as a programming language of choice for statisticians, data scientists and researchers. It has an excellent ecosystem including the powerful RStudio development environment and the Shiny web application framework. But getting started with R can be challenging, particularly if you've never programmed before. That's where this introductory course comes in. We teach using RStudio, which allows program code, results, visualisations and documentation to be blended seamlessly. Join us for a live coding workshop where we write programs that produce results, using the researcher-focused training modules from the highly regarded Software Carpentry Foundation. #### You'll learn: - Introduction to the RStudio interface for programming - Basic syntax and data types in R - How to load external data into R - Creating functions (FUNCTIONS) - Repeating actions and analysing multiple data sets (LOOPS) - Making choices (IF STATEMENTS - CONDITIONALS) - Ways to visualise data in R #### Prerequisites: No prior experience with programming needed to attend this course. We strongly recommend attending the Start Coding without Hesitation: Programming Languages Showdown and Thinking like a computer: The Fundamentals of Programming webinars. Recordings of previously delivered webinars can be found [here](https://intersect.org.au/training/webinars/). **For more information, please click [here](https://intersect.org.au/training/course/r101).** training@intersect.org.au Programming, R
R for Social Scientists

R is quickly gaining popularity as a programming language of choice for researchers. It has an excellent ecosystem including the powerful RStudio development environment.

But getting started with R can be challenging, particularly if you've never programmed before. That's where this introductory...

Keywords: Programming, R

R for Social Scientists https://dresa.org.au/materials/r-for-social-scientists R is quickly gaining popularity as a programming language of choice for researchers. It has an excellent ecosystem including the powerful RStudio development environment. But getting started with R can be challenging, particularly if you've never programmed before. That's where this introductory course comes in. Join us for a live coding workshop where we write programs that produce results, using the researcher-focused training modules from the highly regarded Data Carpentry. #### You'll learn: - Basic syntax and data types in R - RStudio interface - How to import CSV files into R - The structure of data frames - A brief introduction to data wrangling and data transformation - How to calculate summary statistics - A brief introduction to visualise data #### Prerequisites: No prior experience with programming needed to attend this course. **For more information, please click [here](https://intersect.org.au/training/course/r103).** training@intersect.org.au Programming, R
R for Research

R is quickly gaining popularity as a programming language of choice for statisticians, data scientists and researchers. It has an excellent ecosystem including the powerful RStudio development environment and the Shiny web application framework.

This workshop is an introduction to data...

Keywords: Programming, R

R for Research https://dresa.org.au/materials/r-for-research R is quickly gaining popularity as a programming language of choice for statisticians, data scientists and researchers. It has an excellent ecosystem including the powerful RStudio development environment and the Shiny web application framework. This workshop is an introduction to data structures (DataFrames) and visualisation (using the ggplot2 package) in R. The targeted audience for this workshop is researchers who are already familiar with the basic concepts in programming such as loops, functions, and conditionals. We teach using RStudio, which allows program code, results, visualisations and documentation to be blended seamlessly. Join us for a live coding workshop where we write programs that produce results, using the researcher-focused training modules from the highly regarded Software Carpentry Foundation. #### You'll learn: - Project Management with RStudio - Introduction to Data Structures in R - Introduction to DataFrames in R - Selecting values in DataFrames - Quick introduction to Plotting using the ggplot2 package #### Prerequisites: [Learn to Program: R](https://intersect.org.au/training/course/r101/) or any of the [Learn to Program: Python](https://intersect.org.au/training/course/python101/), [Learn to Program: MATLAB](https://intersect.org.au/training/course/matlab101/), [Learn to Program: Julia](https://intersect.org.au/training/course/julia101/), needed to attend this course. If you already have some experience with programming, please check the topics covered in the [Learn to Program: R](https://intersect.org.au/training/course/r101/) course to ensure that you are familiar with the knowledge needed for this course. **For more information, please click [here](https://intersect.org.au/training/course/r110).** training@intersect.org.au Programming, R
Data Manipulation in R

R is quickly gaining popularity as a programming language for statisticians, data scientists and researchers. It has an excellent ecosystem including the powerful RStudio and the Shiny web application framework.

In this workshop, you will learn how to manipulate, explore and get insights from...

Keywords: Programming, R

Data Manipulation in R https://dresa.org.au/materials/data-manipulation-in-r R is quickly gaining popularity as a programming language for statisticians, data scientists and researchers. It has an excellent ecosystem including the powerful RStudio and the Shiny web application framework. In this workshop, you will learn how to manipulate, explore and get insights from your data (Data Manipulation using the dplyr package), as well as how to convert your data from one format to another (Data Transformation using the tidyr package). We teach using RStudio, which allows program code, results, visualisations and documentation to be blended seamlessly. Join us for a live coding workshop where we write programs that produce results, using the researcher-focused training modules from Intersect and the highly regarded Software Carpentry Foundation. #### You'll learn: - DataFrame Manipulation using the dplyr package - DataFrame Transformation using the tidyr package #### Prerequisites: Either [Learn to Program: R](https://intersect.org.au/training/course/r101/) or [Learn to Program: R](https://intersect.org.au/training/course/r101/) and [R for Research](https://intersect.org.au/training/course/r110/) needed to attend this course. If you already have experience with programming, please check the topics covered in the [Learn to Program: R](https://intersect.org.au/training/course/r101/) and [R for Research](https://intersect.org.au/training/course/r110/) courses to ensure that you are familiar with the knowledge needed for this course. **For more information, please click [here](https://intersect.org.au/training/course/r201).** training@intersect.org.au Programming, R
ARDC digital research capabilities and skills framework

This informational flyer outlines the value of skills frameworks and describes at a high level the various elements of the ARDC's Capabilities and Skills Framework.

Capabilities and Skills Landscape
Glossary - Framework terminology
Data and Digital Research roles
Skills/Role...

Keywords: training material, skills framework, ARDC skills framework, ARDC capabilities framework, national skills framework

ARDC digital research capabilities and skills framework https://dresa.org.au/materials/ardc-digital-research-capabilities-and-skills-framework-e0acf524-0666-466c-ac93-f13c133b03cf This informational flyer outlines the value of skills frameworks and describes at a high level the various elements of the ARDC's Capabilities and Skills Framework. Capabilities and Skills Landscape Glossary - Framework terminology Data and Digital Research roles Skills/Role profiles Learning paths Skills/Data roles matrix contact@ardc.edu.au Savill, Jo (type: Editor) Duncan, Ian (type: Editor) Unsworth, Kathryn (type: Editor) Murphy, Paul (type: Editor) training material, skills framework, ARDC skills framework, ARDC capabilities framework, national skills framework
ARDC digital research capabilities and skills framework

This informational flyer outlines the value of skills frameworks and describes at a high level the various elements of the ARDC's Capabilities and Skills Framework.

Capabilities and Skills Landscape
Glossary - Framework terminology
Data and Digital Research roles
Skills/Role...

Keywords: training material, skills framework, ARDC skills framework, ARDC capabilities framework, national skills framework

ARDC digital research capabilities and skills framework https://dresa.org.au/materials/ardc-digital-research-capabilities-and-skills-framework This informational flyer outlines the value of skills frameworks and describes at a high level the various elements of the ARDC's Capabilities and Skills Framework. Capabilities and Skills Landscape Glossary - Framework terminology Data and Digital Research roles Skills/Role profiles Learning paths Skills/Data roles matrix Kathryn Unsworth (kathryn.unsworth@ardc.edu.au) Savill, Jo (type: Editor) Duncan, Ian (type: Editor) Unsworth, Kathryn (type: Editor) Murphy, Paul (type: Editor) training material, skills framework, ARDC skills framework, ARDC capabilities framework, national skills framework
WEBINAR: Protection of genomic data and the Australian Privacy Act: when is genomic data 'personal information'?

This record includes training materials associated with the Australian BioCommons webinar ‘Protection of genomic data and the Australian Privacy Act: when is genomic data ‘personal information’?’. This webinar took place on 6 April 2022.

Event description

It is easy to assume that...

Keywords: Bioinformatics, Genomics, Genetic data, Personal information, Health information, Privacy

WEBINAR: Protection of genomic data and the Australian Privacy Act: when is genomic data 'personal information'? https://dresa.org.au/materials/webinar-protection-of-genomic-data-and-the-australian-privacy-act-when-is-genomic-data-personal-information This record includes training materials associated with the Australian BioCommons webinar ‘Protection of genomic data and the Australian Privacy Act: when is genomic data ‘personal information’?’. This webinar took place on 6 April 2022. **Event description** It is easy to assume that genomic data will be captured by legal definitions of ‘health information’ and ‘genetic information’, but the legal meaning of ‘genetic information’ need not align with scientific categories.  There are many different types of genomic data, with varied characteristics, uses and applications.  Clarifying when genomic data is covered by the Privacy Act 1988 (Cth) is an ongoing evaluative exercise but is important for at least 3 reasons:  1. those subject to the Privacy Act need to be able to confidently navigate their responsibilities 2. understanding current controls is a prerequisite for meaningful external critique (and this is particularly important at a time when the Privacy Act is under review), and 3. while legislation that applies to state public sector agencies is generally distinct from the Privacy Act there are similarities that extend the relevance of the question when is genomic data ‘personal information’ under the Privacy Act? In this presentation, Mark will explore the relationship between the legal concept of genetic information and the concept of genomic data relevant to health and medical research, reflect on the characteristics of each, and the possibility Materials are shared under a Creative Commons Attribution 4.0 International agreement unless otherwise specified and were current at the time of the event. **Files and materials included in this record:** - Event metadata (PDF): Information about the event including, description, event URL, learning objectives, prerequisites, technical requirements etc. - Index of training materials (PDF): List and description of all materials associated with this event including the name, format, location and a brief description of each file. - Taylor_Slides (PDF): A PDF copy of the slides presented during the webinar. **Materials shared elsewhere:** A recording of this webinar is available on the Australian BioCommons YouTube Channel: https://youtu.be/Iaei-9Gu-AI Melissa Burke (melissa@biocommons.org.au) Bioinformatics, Genomics, Genetic data, Personal information, Health information, Privacy
Network Know-how and Data Handling Workshop

This workshop is a ‘train-the-trainer’ session that covers topics such as jargon busting, network literacy and data movement solutions. The workshop will also provide a peek at some collaborative research tools such as Jupyter Notebooks and CloudStor. You will learn about networks, integrated...

Keywords: Networks, data handling

Resource type: lesson, presentation

Network Know-how and Data Handling Workshop https://dresa.org.au/materials/network-know-how-and-data-handling-workshop This workshop is a ‘train-the-trainer’ session that covers topics such as jargon busting, network literacy and data movement solutions. The workshop will also provide a peek at some collaborative research tools such as Jupyter Notebooks and CloudStor. You will learn about networks, integrated tools, data and storage and where all these things fit in the researcher’s toolkit. This workshop is targeted at staff who would like to be more confident in giving advice to researchers about the options available to them. It is especially tailored for those with little to no technical knowledge and includes a hands-on component, using basic programming commands, but requires no previous knowledge of programming. Sara King - sara.king@aarnet.edu.au Burke, Melissa (orcid: 0000-0002-5571-8664) Networks, data handling
WORKSHOP: Introduction to Metabarcoding using QIIME2

This record includes training materials associated with the Australian BioCommons workshop ‘Introduction to Metabarcoding using QIIME2’. This workshop took place on 22 February 2022.

Event description

Metabarcoding has revolutionised the study of biodiversity science. By combining DNA...

Keywords: Bioinformatics, Analysis, Workflows, Microbial ecology, Metabarcoding, Microbiome

WORKSHOP: Introduction to Metabarcoding using QIIME2 https://dresa.org.au/materials/workshop-introduction-to-metabarcoding-using-qiime2 This record includes training materials associated with the Australian BioCommons workshop ‘Introduction to Metabarcoding using QIIME2’. This workshop took place on 22 February 2022. **Event description** Metabarcoding has revolutionised the study of biodiversity science. By combining DNA taxonomy with high-throughput DNA sequencing, it offers the potential to observe a larger diversity in the taxa within a single sample, rapidly expanding the scope of microbial analysis and generating high-quality biodiversity data.  This workshop will introduce the topic of metabarcoding and how you can use Qiime2 to analyse 16S data and gain simultaneous identification of all taxa within a sample. Qiime2 is a popular tool used to perform powerful microbiome analysis that can transform your raw data into publication quality visuals and statistics. In this workshop, using example 16S data from the shallow-water marine anemone E. diaphana, you will learn how to use this pipeline to run essential steps in microbial analysis including generating taxonomic assignments and phylogenic trees, and performing both alpha- and beta- diversity analysis.  Materials are shared under a Creative Commons Attribution 4.0 International agreement unless otherwise specified and were current at the time of the event. **Files and materials included in this record:** - Event metadata (PDF): Information about the event including, description, event URL, learning objectives, prerequisites, technical requirements etc. - Index of training materials (PDF): List and description of all materials associated with this event including the name, format, location and a brief description of each file. - Schedule (PDF): A breakdown of the topics and timings for the workshop **Materials shared elsewhere:** This workshop follows the tutorial ‘Introduction to metabarcoding with QIIME2’ which has been made publicly available by Melbourne Bioinformatics. https://www.melbournebioinformatics.org.au/tutorials/tutorials/qiime2/qiime2/ Melissa Burke (melissa@biocommons.org.au) Bioinformatics, Analysis, Workflows, Microbial ecology, Metabarcoding, Microbiome
WEBINAR: Conservation genomics in the age of extinction

This record includes training materials associated with the Australian BioCommons webinar ‘Conservation genomics in the age of extinction’. This webinar took place on 8 March 2022.

Event description

Biodiversity is crashing and millions of plant and animal species are at the edge of...

Keywords: Conservation genomics, Genomics, Bioinformatics, Sequencing, Threatened Species Initiative, Galaxy Australia

WEBINAR: Conservation genomics in the age of extinction https://dresa.org.au/materials/webinar-conservation-genomics-in-the-age-of-extinction This record includes training materials associated with the Australian BioCommons webinar ‘Conservation genomics in the age of extinction’. This webinar took place on 8 March 2022. **Event description** Biodiversity is crashing and millions of plant and animal species are at the edge of extinction. Understanding the genetic diversity of these species is an important tool for conservation biology but obtaining high quality genomes for threatened species is not always straightforward. In this webinar Dr Carolyn Hogg speaks about the work she has been doing with the Threatened Species Initiative to build genomic resources to understand and protect Australia’s threatened species. Using examples such as the Kroombit Tinker Frog and the Greater Bilby, Carolyn describes some of the complexities and challenges of generating genomes from short reads and HiFi reads for critically endangered species. She outlines the technologies and resources being used and how these are bridging the gap between genomicists, bioinformaticians and conservation experts to help save Australian species. Materials are shared under a Creative Commons Attribution 4.0 International agreement unless otherwise specified and were current at the time of the event. **Files and materials included in this record:** - Event metadata (PDF): Information about the event including, description, event URL, learning objectives, prerequisites, technical requirements etc. - Index of training materials (PDF): List and description of all materials associated with this event including the name, format, location and a brief description of each file. **Materials shared elsewhere:** A recording of this webinar is available on the Australian BioCommons YouTube Channel: https://youtu.be/Bl7CaiGQ91s   Melissa Burke (melissa@biocommons.org.au) Conservation genomics, Genomics, Bioinformatics, Sequencing, Threatened Species Initiative, Galaxy Australia
WEBINAR: Establishing Gen3 to enable better human genome data sharing in Australia

This record includes training materials associated with the Australian BioCommons webinar ‘Establishing Gen3 to enable better human genome data sharing in Australia’. This webinar took place on 16 February 2022.

Event description

Australian human genome initiatives are generating vast...

Keywords: Bioinformatics, Genomics, Human genomics, Digital infrastructure, Gen3, Data sharing, Data management

WEBINAR: Establishing Gen3 to enable better human genome data sharing in Australia https://dresa.org.au/materials/webinar-establishing-gen3-to-enable-better-human-genome-data-sharing-in-australia This record includes training materials associated with the Australian BioCommons webinar ‘Establishing Gen3 to enable better human genome data sharing in Australia’. This webinar took place on 16 February 2022. **Event description** Australian human genome initiatives are generating vast amounts of human genome data. There is a desire and need to share data with collaborators but researchers face significant infrastructural, technical and administrative barriers in achieving this. To efficiently share and distribute their genome data they need scalable services and infrastructure that: is easily administered; allows for the efficient data management; enables sharing and interoperability; and is aligned with global standards for human genome data sharing. Australian BioCommons has brought together a team from Zero Childhood Cancer (Zero), the University of Melbourne Centre for Cancer Research (UMCCR) and Australian Access Federation to explore the use of Gen3 technology. Establishing systems for easier management and sharing of their human genome data holdings is no simple task, and the group wants to ensure that other Australian providers and Institutions can benefit from their experience and easily deploy the same solution in the future. Gen3 is an open source software suite that makes use of private and public clouds to tackle the challenges of data management, interoperability, data sharing and analysis. It has been used in several very large NIH-funded projects that collectively house and describe data derived from hundreds of thousands of human samples (e.g. NCI Genomic Data Commons, BioData Catalyst, BloodPAC, BrainCommons, Kids First Data Commons). In this webinar you’ll hear from UMCCR and Zero about their experiences and progress towards establishing Gen3 instances to better enable better human genome data sharing in Australia. They will outline the challenges and opportunities that have arisen through this Australian BioCommons project and demonstrate the capabilities of Gen3 for human genome research. Materials are shared under a Creative Commons Attribution 4.0 International agreement unless otherwise specified and were current at the time of the event. Files and materials included in this record: - Event metadata (PDF): Information about the event including, description, event URL, learning objectives, prerequisites, technical requirements etc. - Index of training materials (PDF): List and description of all materials associated with this event including the name, format, location and a brief description of each file. - Gen3_Webinar_Slides (PDF): Slides presented during the webinar **Materials shared elsewhere:** A recording of this webinar is available on the Australian BioCommons YouTube Channel: https://youtu.be/1F6B03Byigk Melissa Burke (melissa@biocommons.org.au) Bioinformatics, Genomics, Human genomics, Digital infrastructure, Gen3, Data sharing, Data management
WORKSHOP: Refining genome annotations with Apollo

This record includes training materials associated with the Australian BioCommons  workshop ‘Refining genome annotations with Apollo’. This workshop took place on 17 November 2021.

Workshop description

Genome annotation is crucial to defining the function of genomic sequences. This...

Keywords: Apollo Software, Bioinformatics, Analysis, Workflows, Genomics, Genome annotation

WORKSHOP: Refining genome annotations with Apollo https://dresa.org.au/materials/workshop-refining-genome-annotations-with-apollo This record includes training materials associated with the Australian BioCommons  workshop ‘Refining genome annotations with Apollo’. This workshop took place on 17 November 2021. **Workshop description** Genome annotation is crucial to defining the function of genomic sequences. This process typically involves a round of automated annotation followed by manual curation. Manual curation allows you to visualise your annotations so you can understand what your organism looks like, and then to manually refine these annotations along with any additional data you might have. This process is typically performed collaboratively as part of a team effort. Apollo is a popular tool for facilitating real-time collaborative, manual curation and genome annotation editing. In this workshop we will learn how to use Apollo to refine genome annotations using example data from an E. coli strain. We’ll focus on the basics like getting data into Apollo, viewing evidence tracks, editing and adding structural and functional annotation, visualising the results and collaborating on genome annotations. This workshop made use of a training instance of  the new Australian Apollo Service. This service enables Australian-based research groups and consortia to access Apollo and host genome assembly and supporting evidence files for free. This service has been made possible by The Australian BioCommons and partners at QCIF and Pawsey. To learn more about the Australian Apollo Service you can watch the Australian Apollo Launch Webinar. This workshop was presented by the Australian BioCommons and Queensland Cyber Infrastructure Foundation (QCIF) . The Australian Apollo Service is operated by QCIF and underpinned by computational resources provided by the Pawsey Supercomputing Research Centre and receives NCRIS funding through Bioplatforms Australia and the Australian Research Data Commons as well as Queensland Government RICF funding. The training materials presented in this workshop were developed by Anthony Bretaudeau, Helena Rasche, Nathan Dunn, Mateo Boudet for the Galaxy Training Network. Helena and Anthony are part of the Gallantries project which is supported by Erasmus Programme of the European Union. Materials are shared under a Creative Commons Attribution 4.0 International agreement unless otherwise specified and were current at the time of the event. **Files and materials included in this record:** - Event metadata (PDF): Information about the event including, description, event URL, learning objectives, prerequisites, technical requirements etc. - Index of training materials (PDF): List and description of all materials associated with this event including the name, format, location and a brief description of each file. - Schedule (PDF): A breakdown of the topics and timings for the workshop - 2021 Apollo Training Intro (PPTX and PDF): Slides used to introduce the Australian Apollo Service - Augustus.gff3 (gff3): E.coli derived data file used in the tutorial. Data was obtained from the Galaxy Training Network and pre-processed using Galaxy Australia. - Blastp_vs_swissprot.gff3: E.coli derived data file used in the tutorial. Data was obtained from the Galaxy Training Network and pre-processed using Galaxy Australia. **Materials shared elsewhere:** This workshop is based on the tutorial ‘Refining genome annotations with Apollo’ which was developed for the Galaxy Training Network. Anthony Bretaudeau, Helena Rasche, Nathan Dunn, Mateo Boudet, Erasmus Programme, 2021 Refining Genome Annotations with Apollo (Galaxy Training Materials). https://training.galaxyproject.org/training-material/topics/genome-annotation/tutorials/apollo/tutorial.html Online; accessed Wed Dec 15 2021 See also: Batut et al., 2018 Community-Driven Data Analysis Training for Biology Cell Systems 10.1016/j.cels.2018.05.012 Melissa Burke (melissa@biocommons.org.au) Apollo Software, Bioinformatics, Analysis, Workflows, Genomics, Genome annotation
WORKSHOP: Hybrid de novo genome assembly

This record includes training materials associated with the Australian BioCommons workshop ‘Hybrid de novo genome assembly’. This workshop took place on 7 October 2021.

Workshop description

It’s now easier than ever to assemble new reference genomes thanks to hybrid genome assembly...

Keywords: Galaxy Australia, Bioinformatics, Analysis, Workflows, Genomics, Genome assembly, De novo assembly

WORKSHOP: Hybrid de novo genome assembly https://dresa.org.au/materials/workshop-hybrid-de-novo-genome-assembly This record includes training materials associated with the Australian BioCommons workshop ‘Hybrid de novo genome assembly’. This workshop took place on 7 October 2021. **Workshop description** It’s now easier than ever to assemble new reference genomes thanks to hybrid genome assembly approaches which enable research on organisms for which reference genomes were not previously available. These approaches combine the strengths of short (Illumina) and long (PacBio or Nanopore) read technologies, resulting in improved assembly quality. In this workshop we will learn how to create and assess genome assemblies from Illumina and Nanopore reads using data from a Bacillus Subtilis strain. We will demonstrate two hybrid-assembly methods using the tools Flye, Pilon, and Unicycler to perform assembly and subsequent error correction. You will learn how to visualise input read sets and the assemblies produced at each stage and assess the quality of the final assembly. All analyses will be performed using Galaxy Australia, an online platform for biological research that allows people to use computational data analysis tools and workflows without the need for programming experience. This workshop is presented by the Australian BioCommons and Melbourne Bioinformatics with the assistance of a network of facilitators from the national Bioinformatics Training Cooperative. Materials are shared under a Creative Commons Attribution 4.0 International agreement unless otherwise specified and were current at the time of the event. **Files and materials included in this record:** - Event metadata (PDF): Information about the event including, description, event URL, learning objectives, prerequisites, technical requirements etc. - Index of training materials (PDF): List and description of all materials associated with this event including the name, format, location and a brief description of each file. - Schedule (PDF): A breakdown of the topics and timings for the workshop **Materials shared elsewhere:** This workshop follows the tutorial ‘Hybrid genome assembly - Nanopore and Illumina’ developed by Melbourne Bioinformatics. https://www.melbournebioinformatics.org.au/tutorials/tutorials/hybrid_assembly/nanopore_assembly/ Melissa Burke (melissa@biocommons.org.au) Galaxy Australia, Bioinformatics, Analysis, Workflows, Genomics, Genome assembly, De novo assembly
WORKSHOP: Working with genomics sequences and features in R with Bioconductor

This record includes training materials associated with the Australian BioCommons workshop ‘Working with genomics sequences and features in R with Bioconductor’. This workshop took place on 23 September 2021.

Workshop description

Explore the many useful functions that the Bioconductor...

Keywords: R software, Bioconductor, Bioinformatics, Analysis, Genomics, Sequence analysis

WORKSHOP: Working with genomics sequences and features in R with Bioconductor https://dresa.org.au/materials/workshop-working-with-genomics-sequences-and-features-in-r-with-bioconductor This record includes training materials associated with the Australian BioCommons workshop ‘Working with genomics sequences and features in R with Bioconductor’. This workshop took place on 23 September 2021. **Workshop description** Explore the many useful functions that the Bioconductor environment offers for working with genomic data and other biological sequences.  DNA and proteins are often represented as files containing strings of nucleic acids or amino acids. They are associated with text files that provide additional contextual information such as genome annotations. This workshop provides hands-on experience with tools, software and packages available in R via Bioconductor for manipulating, exploring and extracting information from biological sequences and annotation files. We will look at tools for working with some commonly used file formats including FASTA, GFF3, GTF, methods for identifying regions of interest, and easy methods for obtaining data packages such as genome assemblies.  This workshop is presented by the Australian BioCommons and Monash Bioinformatics Platform with the assistance of a network of facilitators from the national Bioinformatics Training Cooperative. Materials are shared under a Creative Commons Attribution 4.0 International agreement unless otherwise specified and were current at the time of the event. **Files and materials included in this record:** - Event metadata (PDF): Information about the event including, description, event URL, learning objectives, prerequisites, technical requirements etc. - Index of training materials (PDF): List and description of all materials associated with this event including the name, format, location and a brief description of each file. - Schedule (PDF): schedule for the workshop providing a breakdown of topics and timings **Materials shared elsewhere:** This workshop follows the tutorial ‘Working with DNA sequences and features in R with Bioconductor - version 2’ developed for Monash Bioinformatics Platform and Monash Data Fluency by Paul Harrison. https://monashdatafluency.github.io/r-bioc-2/ Melissa Burke (melissa@biocommons.org.au) R software, Bioconductor, Bioinformatics, Analysis, Genomics, Sequence analysis