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Data Visualisation in Python

Course Materials

You'll learn:

  • Using the Grammar of Graphics to convert data into figures using the seaborn and matplotlib libraries
  • Configuring plot elements within seaborn and matplotlib
  • Exploring different types of plots using seaborn

Prerequisites:

Either [Learn to...

Keywords: Programming, Python

Data Visualisation in Python https://dresa.org.au/materials/data-visualisation-in-python Course Materials #### You'll learn: - Using the Grammar of Graphics to convert data into figures using the seaborn and matplotlib libraries - Configuring plot elements within seaborn and matplotlib - Exploring different types of plots using seaborn #### 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. We also strongly recommend attending the [Data Manipulation in Python](https://intersect.org.au/training/course/python201/). **For more information, please click [here](https://intersect.org.au/training/course/python202).** training@intersect.org.au Programming, Python
Data Manipulation and Visualisation 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 and Visualisation in Python https://dresa.org.au/materials/data-manipulation-and-visualisation-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. You will also explore different types of graphs and learn how to customise them using two of the most popular plotting libraries in Python, matplotlib and seaborn (Data Visualisation). 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 - Using the Grammar of Graphics to convert data into figures using the seaborn and matplotlib libraries - Configuring plot elements within seaborn and matplotlib - Exploring different types of plots using seaborn #### 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/python203).** training@intersect.org.au Programming, Python
Introduction to Machine Learning using Python: Introduction & Linear Regression

Machine Learning (ML) is a new way to program computers to solve real world problems. It has gained popularity over the last few years by achieving tremendous success in tasks that we believed only humans could solve, from recognising images to self-driving cars. In this course, we will explore...

Keywords: Programming, Python

Introduction to Machine Learning using Python: Introduction & Linear Regression https://dresa.org.au/materials/introduction-to-machine-learning-using-python-introduction-linear-regression Machine Learning (ML) is a new way to program computers to solve real world problems. It has gained popularity over the last few years by achieving tremendous success in tasks that we believed only humans could solve, from recognising images to self-driving cars. In this course, we will explore the fundamentals of Machine Learning from a practical perspective with the help of the Python programming language and its scientific computing libraries. #### You'll learn: - Understand the difference between supervised and unsupervised Machine Learning. - Understand the fundamentals of Machine Learning. - Comprehensive introduction to Machine Learning models and techniques such as Linear Regression and Model Training. - Understand the Machine Learning modelling workflows. - Use Python and scikit-learn to process real datasets, train and apply Machine Learning models #### Prerequisites: Either [Learn to Program: Python](https://intersect.org.au/training/course/python101/) and [Data Manipulation in Python](https://intersect.org.au/training/course/python201/) or [Learn to Program: Python](https://intersect.org.au/training/course/python101/) and [Data Manipulation and Visualisation in Python](https://intersect.org.au/training/course/python203/) needed to attend this course. If you already have experience with programming, please check the topics covered in courses above to ensure that you are familiar with the knowledge needed for this course, such as good understanding of Python syntax and basic programming concepts and familiarity with Pandas, Numpy and Seaborn libraries. Maths knowledge is not required. However, there is a few Math formula covered in this course and the references will be provided. Having an understanding of the Mathematics behind each Machine Learning algorithms is going to make you appreciate the behaviour of the model and know its pros/cons when using them. #### Why do this course: - Useful for anyone who wants to learn about Machine Learning but are overwhelmed with the tremendous amount of resources. - It does not go in depth into mathematical concepts and formula, however formal intuitions and references are provided to guide the participants for further learning. - We do have applications on real datasets! - Machine Learning models are introduced in this course together with important feature engineering techniques that are guaranteed to be useful in your own projects. - Give you enough background to kickstart your own Machine Learning journey, or transition yourself into Deep Learning. For a better and more complete understanding of the most popular Machine Learning models and techniques please consider attending all three Introduction to Machine Learning using Python workshops: - Introduction to Machine Learning using Python: Introduction & Linear Regression - Introduction to Machine Learning using Python: Classification - Introduction to Machine Learning using Python: SVM & Unsupervised Learning **For more information, please click [here](https://intersect.org.au/training/course/python205).** training@intersect.org.au Programming, Python
Introduction to Machine Learning using Python: Classification

Machine Learning (ML) is a new way to program computers to solve real world problems. It has gained popularity over the last few years by achieving tremendous success in tasks that we believed only humans could solve, from recognising images to self-driving cars. In this course, we will explore...

Keywords: Programming, Python

Introduction to Machine Learning using Python: Classification https://dresa.org.au/materials/introduction-to-machine-learning-using-python-classification Machine Learning (ML) is a new way to program computers to solve real world problems. It has gained popularity over the last few years by achieving tremendous success in tasks that we believed only humans could solve, from recognising images to self-driving cars. In this course, we will explore the fundamentals of Machine Learning from a practical perspective with the help of the Python programming language and its scientific computing libraries. #### You'll learn: - Comprehensive introduction to Machine Learning models and techniques such as Logistic Regression, Decision Trees and Ensemble Learning. - Know the differences between various core Machine Learning models. - Understand the Machine Learning modelling workflows. - Use Python and scikit-learn to process real datasets, train and apply Machine Learning models #### Prerequisites: Either [Learn to Program: Python](https://intersect.org.au/training/course/python101/), [Data Manipulation in Python](https://intersect.org.au/training/course/python201/) and [Introduction to ML using Python: Introduction & Linear Regression](https://intersect.org.au/training/course/python205/) or [Learn to Program: Python](https://intersect.org.au/training/course/python101/), [Data Manipulation and Visualisation in Python](https://intersect.org.au/training/course/python203/) and [Introduction to ML using Python: Introduction & Linear Regression](https://intersect.org.au/training/course/python205/) needed to attend this course. If you already have experience with programming, please check the topics covered in courses above to ensure that you are familiar with the knowledge needed for this course, such as good understanding of Python syntax, basic programming concepts and familiarity with Pandas, Numpy and Seaborn libraries, and basic understanding of Machine Learning and Model Training. Maths knowledge is not required. However, there is a few Math formula covered in this course and the references will be provided. Having an understanding of the Mathematics behind each Machine Learning algorithms is going to make you appreciate the behaviour of the model and know its pros/cons when using them. #### Why do this course: - Useful for anyone who wants to learn about Machine Learning but are overwhelmed with the tremendous amount of resources. - It does not go in depth into mathematical concepts and formula, however formal intuitions and references are provided to guide the participants for further learning. - We do have applications on real datasets! - Machine Learning models are introduced in this course together with important feature engineering techniques that are guaranteed to be useful in your own projects. - Give you enough background to kickstart your own Machine Learning journey, or transition yourself into Deep Learning. For a better and more complete understanding of the most popular Machine Learning models and techniques please consider attending all three Introduction to Machine Learning using Python workshops: - Introduction to Machine Learning using Python: Introduction & Linear Regression - Introduction to Machine Learning using Python: Classification - Introduction to Machine Learning using Python: SVM & Unsupervised Learning **For more information, please click [here](https://intersect.org.au/training/course/python206).** training@intersect.org.au Programming, Python
Introduction to Machine Learning using Python: SVM & Unsupervised Learning

Machine Learning (ML) is a new way to program computers to solve real world problems. It has gained popularity over the last few years by achieving tremendous success in tasks that we believed only humans could solve, from recognising images to self-driving cars. In this course, we will explore...

Keywords: Programming, Python

Introduction to Machine Learning using Python: SVM & Unsupervised Learning https://dresa.org.au/materials/introduction-to-machine-learning-using-python-svm-unsupervised-learning Machine Learning (ML) is a new way to program computers to solve real world problems. It has gained popularity over the last few years by achieving tremendous success in tasks that we believed only humans could solve, from recognising images to self-driving cars. In this course, we will explore the fundamentals of Machine Learning from a practical perspective with the help of the Python programming language and its scientific computing libraries. #### You'll learn: - Comprehensive introduction to Machine Learning models and techniques such as Support Vector Machine, K-Nearest Neighbor and Dimensionality Reduction. - Know the differences between various core Machine Learning models. - Understand the Machine Learning modelling workflows. - Use Python and scikit-learn to process real datasets, train and apply Machine Learning models #### Prerequisites: Either [Learn to Program: Python](https://intersect.org.au/training/course/python101/), [Data Manipulation in Python](https://intersect.org.au/training/course/python201/) and [Introduction to ML using Python: Introduction & Linear Regression](https://intersect.org.au/training/course/python205/) or [Learn to Program: Python](https://intersect.org.au/training/course/python101/), [Data Manipulation and Visualisation in Python](https://intersect.org.au/training/course/python203/) and [Introduction to ML using Python: Introduction & Linear Regression](https://intersect.org.au/training/course/python205/) needed to attend this course. If you already have experience with programming, please check the topics covered in courses above to ensure that you are familiar with the knowledge needed for this course, such as good understanding of Python syntax, basic programming concepts and familiarity with Pandas, Numpy and Seaborn libraries, and basic understanding of Machine Learning and Model Training. Maths knowledge is not required. However, there is a few Math formula covered in this course and the references will be provided. Having an understanding of the Mathematics behind each Machine Learning algorithms is going to make you appreciate the behaviour of the model and know its pros/cons when using them. #### Why do this course: - Useful for anyone who wants to learn about Machine Learning but are overwhelmed with the tremendous amount of resources. - It does not go in depth into mathematical concepts and formula, however formal intuitions and references are provided to guide the participants for further learning. - We do have applications on real datasets! - Machine Learning models are introduced in this course together with important feature engineering techniques that are guaranteed to be useful in your own projects. - Give you enough background to kickstart your own Machine Learning journey, or transition yourself into Deep Learning. For a better and more complete understanding of the most popular Machine Learning models and techniques please consider attending all three Introduction to Machine Learning using Python workshops: - Introduction to Machine Learning using Python: Introduction & Linear Regression - Introduction to Machine Learning using Python: Classification - Introduction to Machine Learning using Python: SVM & Unsupervised Learning **For more information, please click [here](https://intersect.org.au/training/course/python207).** training@intersect.org.au Programming, Python
Surveying with Qualtrics

Needing to collect data from people in a structured and intuitive way? Have you thought about using Qualtrics?

Qualtrics in a powerful cloud-based survey tool, ideal for social scientists from all disciplines. This course will introduce the technical components of the whole research workflow...

Keywords: Data Management, Qualtrics

Surveying with Qualtrics https://dresa.org.au/materials/surveying-with-qualtrics Needing to collect data from people in a structured and intuitive way? Have you thought about using Qualtrics? Qualtrics in a powerful cloud-based survey tool, ideal for social scientists from all disciplines. This course will introduce the technical components of the whole research workflow from building a survey to analysing the results using Qualtrics. We will discover the numerous design elements available in order to get the most useful results and make life as easy as can be for your respondents. If your institution has a licence to Qualtrics, then this course is right for you. #### You'll learn: - Format a sample survey using the Qualtrics online platform - Configure the survey using a range of design features to improve user experience - Decide which distribution channel is right for your needs - Understand the available data analysis and export options in Qualtrics #### Prerequisites: You must have access to a Qualtrics instance, such as through your university license. Speak to your local university IT or Research Office for assistance in accessing the Qualtrics instance. **For more information, please click [here](https://intersect.org.au/training/course/qltrics101).** training@intersect.org.au Data Management, Qualtrics
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
Heurist Tutorials

A set of video tutorials with accompanying walkthroughs for building your first Heurist database and website. The first three tutorials show you how to get started in Heurist. The five subsequent tutorials introduce you to the five main menus in the Heurist interface.

Keywords: Heurist, Data management, Data visualisation, Digital Humanities, Databasing, website

Resource type: tutorial

Heurist Tutorials https://dresa.org.au/materials/heurist-tutorials A set of video tutorials with accompanying walkthroughs for building your first Heurist database and website. The first three tutorials show you how to get started in Heurist. The five subsequent tutorials introduce you to the five main menus in the Heurist interface. michael.falk@sydney.edu.au Johnson, Ian Osmakov, Artem Heurist, Data management, Data visualisation, Digital Humanities, Databasing, website mbr phd ecr researcher support
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
WORKSHOP: Online data analysis for biologists

This record includes training materials associated with the Australian BioCommons workshop ‘Online data analysis for biologists’. This workshop took place on 9 September 2021.

Workshop description

Galaxy is an online platform for biological research that allows people to use...

Keywords: Bioinformatics, Analysis, Workflows, Galaxy Australia

WORKSHOP: Online data analysis for biologists https://dresa.org.au/materials/workshop-online-data-analysis-for-biologists This record includes training materials associated with the Australian BioCommons workshop ‘Online data analysis for biologists’. This workshop took place on 9 September 2021. **Workshop description** Galaxy is an online platform for biological research that allows people to use computational data analysis tools and workflows without the need for programming experience. It is an open source, web-based platform for accessible, reproducible, and transparent computational biomedical research. It also captures run information so that workflows can be saved, repeated and shared efficiently via the web. This interactive beginners workshop will provide an introduction to the Galaxy interface, histories and available tools. The material covered in this workshop is freely available through the Galaxy Training Network. The workshop will be held via Zoom and involves a combination of presentations by the lead trainer and smaller breakout groups supported by experienced facilitators. The materials are shared under a Creative Commons 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 - Online_data_analysis_for_biologists_extraslides (PPTX and PDF): Slides used to introduce the data set and emphasise the importance of workflows. These slides were developed by Ms Grace Hall. **Materials shared elsewhere:** The tutorial used in this workshop is available via the Galaxy Training Network. Anne Fouilloux, Nadia Goué, Christopher Barnett, Michele Maroni, Olha Nahorna, Dave Clements, Saskia Hiltemann, 2021 Galaxy 101 for everyone (Galaxy Training Materials). https://training.galaxyproject.org/training-material/topics/introduction/tutorials/galaxy-intro-101-everyone/tutorial.html Online; accessed Fri Dec 10 2021 Melissa Burke (melissa@biocommons.org.au) Bioinformatics, Analysis, Workflows, Galaxy Australia
WEBINAR: Launching the new Apollo Service: collaborative genome annotation for Australian researchers

This record includes training materials associated with the Australian BioCommons webinar ‘Launching the new Apollo Service: collaborative genome annotation for Australian researchers’. This webinar/workshop took place on 29 September 2021.

Event description

Genome annotation is crucial...

Keywords: Genome Annotation, Genomics, Genome curation, Bioinformatics, Apollo software

WEBINAR: Launching the new Apollo Service: collaborative genome annotation for Australian researchers https://dresa.org.au/materials/webinar-launching-the-new-apollo-service-collaborative-genome-annotation-for-australian-researchers This record includes training materials associated with the Australian BioCommons webinar ‘Launching the new Apollo Service: collaborative genome annotation for Australian researchers’. This webinar/workshop took place on 29 September 2021. **Event description** Genome annotation is crucial to defining the function of genomic sequences. Apollo is a popular tool for facilitating real-time collaborative curation and genome annotation editing. The technical obstacles faced by Australian researchers wanting to access and maintain this software have now been solved.  The new Australian Apollo Service can host your genome assembly and supporting evidence files, taking care of all the system administration so you and your team can focus on the annotation curation itself. The Australian BioCommons and partners at QCIF and Pawsey are now offering the Apollo Service free to use for Australian-based research groups and research consortia. As part of this launch, you’ll hear what’s possible from some of the early adopters who helped guide the development of the service. These Australian researchers will highlight the benefits that Apollo is bringing to their genome annotation and curation workflows. Join us to find out how you can get access to the Australian Apollo Service. 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. - Degnan Lab - Apollo Launch Webinar (PDF): Slides presented by Professors Sandie and Bernie Degnan - Nelson - Apollo Launch Webinar (PDF): Slides presented by Dr Tiffanie Nelson - Voelker - Apollo Launch Webinar (PDF): Slides presented by Julia Voelker - Rane - Apollo Launch Webinar (PDF): Slides presented by Dr Rahul Rane. **Materials shared elsewhere:** A recording of this webinar is available on the Australian BioCommons YouTube Channel: https://youtu.be/o8jhRra-x4Y   Melissa Burke (melissa@biocommons.org.au) Genome Annotation, Genomics, Genome curation, Bioinformatics, Apollo software
WEBINAR: KBase - A knowledge base for systems biology

This record includes training materials associated with the Australian BioCommons webinar ‘KBase - A knowledge base for systems biology’. This webinar took place on 22 September 2021.

Event description

Developed for bench biologists and bioinformaticians, The Department of Energy...

Keywords: Systems Biology, FAIR Research, Open Source Software, Metagenomics, Microbiology

WEBINAR: KBase - A knowledge base for systems biology https://dresa.org.au/materials/webinar-kbase-a-knowledge-base-for-systems-biology This record includes training materials associated with the Australian BioCommons webinar ‘KBase - A knowledge base for systems biology’. This webinar took place on 22 September 2021. **Event description** Developed for bench biologists and bioinformaticians, The Department of Energy Systems Biology Knowledgebase (KBase) is a free, open source, software and data science platform designed to meet the grand challenge of systems biology: predicting and designing biological function. This webinar will provide an overview of the KBase mission and user community, as well as a tour of the online platform and basic functionality. You’ll learn how KBase can support your research: Upload data, run analysis tools (Apps), share your analysis with collaborators, and publish your data and reproducible workflows. We’ll highlight a brand new feature that enables users to link environment and measurement data to sequencing data. You’ll also find out how KBase supports findable, accessible, interoperable, and reusable (FAIR) research by providing open, reproducible, shareable bioinformatics workflows. 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. - Q&A for Australian BioCommons KBase Webinar [PDF]: Document containing answers to questions asked during the webinar and links to additional resources - Introduction to KBase: Australian BioCommons Webinar [PDF]: Slides presented during the webinar **Materials shared elsewhere:** A recording of the webinar is available on the Australian BioCommons YouTube Channel: https://youtu.be/tJ94i9gOJfU The slides are also available as Google slides:  https://tinyurl.com/KBase-webinar-slides Melissa Burke (melissa@biocommons.org.au) Systems Biology, FAIR Research, Open Source Software, Metagenomics, Microbiology
WEBINAR: Where to go when your bioinformatics outgrows your compute

This record includes training materials associated with the Australian BioCommons webinar ‘Where to go when your bioinformatics outgrows your compute’. This webinar took place on 19 August 2021.

Bioinformatics analyses are often complex, requiring multiple software tools and specialised...

Keywords: Computational Biology, Bioinformatics, High performance computing, HPC, Galaxy Australia, Nectar Research Cloud, Pawsey Supercomputing Centre, NCI, NCMAS, Cloud computing

WEBINAR: Where to go when your bioinformatics outgrows your compute https://dresa.org.au/materials/webinar-where-to-go-when-your-bioinformatics-outgrows-your-compute This record includes training materials associated with the Australian BioCommons webinar ‘Where to go when your bioinformatics outgrows your compute’. This webinar took place on 19 August 2021. Bioinformatics analyses are often complex, requiring multiple software tools and specialised compute resources. “I don’t know what compute resources I will need”, “My analysis won’t run and I don’t know why” and "Just getting it to work" are common pain points for researchers. In this webinar, you will learn how to understand the compute requirements for your bioinformatics workflows. You will also hear about ways of accessing compute that suits your needs as an Australian researcher, including Galaxy Australia, cloud and high-performance computing services offered by the Australian Research Data Commons, the National Compute Infrastructure (NCI) and Pawsey.  We also describe bioinformatics and computing support services available to Australian researchers.  This webinar was jointly organised with the Sydney Informatics Hub at the University of Sydney. 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. - Where to go when your bioinformatics outgrows your compute - slides (PDF and PPTX): Slides presented during the webinar - Australian research computing resources cheat sheet (PDF): A list of resources and useful links mentioned during the webinar. **Materials shared elsewhere:** A recording of the webinar is available on the Australian BioCommons YouTube Channel: https://youtu.be/hNTbngSc-W0 Melissa Burke (melissa@biocommons.org.au) Computational Biology, Bioinformatics, High performance computing, HPC, Galaxy Australia, Nectar Research Cloud, Pawsey Supercomputing Centre, NCI, NCMAS, Cloud computing
WEBINAR: High performance bioinformatics: submitting your best NCMAS application

This record includes training materials associated with the Australian BioCommons webinar ‘High performance bioinformatics: submitting your best NCMAS application’. This webinar took place on 20 August 2021.

Bioinformaticians are increasingly turning to specialised compute infrastructure and...

Keywords: Computational Biology, Bioinformatics, High Performance Computing, HPC, NCMAS

WEBINAR: High performance bioinformatics: submitting your best NCMAS application https://dresa.org.au/materials/webinar-high-performance-bioinformatics-submitting-your-best-ncmas-application This record includes training materials associated with the Australian BioCommons webinar ‘High performance bioinformatics: submitting your best NCMAS application’. This webinar took place on 20 August 2021. Bioinformaticians are increasingly turning to specialised compute infrastructure and efficient, scalable workflows as their research becomes more data intensive. Australian researchers that require extensive compute resources to process large datasets can apply for access to national high performance computing facilities (e.g. Pawsey and NCI) to power their research through the National Computational Merit Allocation Scheme (NCMAS). NCMAS is a competitive, merit-based scheme and requires applicants to carefully consider how the compute infrastructure and workflows will be applied.  This webinar provides life science researchers with insights into what makes a strong NCMAS application, with a focus on the technical assessment, and how to design and present effective and efficient bioinformatic workflows for the various national compute facilities. It will be followed by a short Q&A session. 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. - High performance bioinformatics: submitting your best NCMAS application - slides (PDF and PPTX): Slides presented during the webinar **Materials shared elsewhere:** A recording of the webinar is available on the Australian BioCommons YouTube Channel: https://youtu.be/HeFGjguwS0Y Melissa Burke (melissa@biocommons.org.au) Computational Biology, Bioinformatics, High Performance Computing, HPC, NCMAS
WEBINAR: Getting started with R

This record includes training materials associated with the Australian BioCommons webinar ‘Getting started with R’. This webinar took place on 16 August 2021.

Data analysis skills are now central to most biological experiments. While Excel can cover some of your data analysis needs, it is not...

Keywords: R statistical software, R studio, Tidyverse, Bioinformatics, Data analysis

WEBINAR: Getting started with R https://dresa.org.au/materials/webinar-getting-started-with-r This record includes training materials associated with the Australian BioCommons webinar ‘Getting started with R’. This webinar took place on 16 August 2021. Data analysis skills are now central to most biological experiments. While Excel can cover some of your data analysis needs, it is not always the best choice, particularly for large and complex datasets. R is an open-source software and programming language that enables data exploration, statistical analysis visualisation and more. While it is the tool of choice for data analysis, getting started can be a little daunting for those without a background in statistics. In this webinar Saskia Freytag, an R user with over a decade of experience and member of the Bioconductor Community Advisory Board, will walk you through their hints and tips for getting started with R and data analysis. She’ll cover topics like R Studio and why you need it, where to get help, basic data manipulation, visualisations and extending R with libraries. The webinar will be followed by a short Q&A session 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. - Getting started with R - slides (PDF): Slides used in the presentation **Materials shared elsewhere:** A recording of the webinar is available on the Australian BioCommons YouTube Channel: https://youtu.be/JS7yZw7bnX8 Melissa Burke (melissa@biocommons.org.au) R statistical software, R studio, Tidyverse, Bioinformatics, Data analysis
WEBINAR: Making sense of phosphoproteomics data with Phosphomatics

This record includes training materials associated with the Australian BioCommons webinar  ‘Making sense of phosphoproteomics data with Phosphomatics’. This webinar took place on 2 June 2021.

Mass spectrometry-based phosphoproteomics is one of the most powerful tools available for...

Keywords: Phosphoproteomics, Proteomics, Mass spectrometry

WEBINAR: Making sense of phosphoproteomics data with Phosphomatics https://dresa.org.au/materials/webinar-making-sense-of-phosphoproteomics-data-with-phosphomatics This record includes training materials associated with the Australian BioCommons webinar  ‘Making sense of phosphoproteomics data with Phosphomatics’. This webinar took place on 2 June 2021. Mass spectrometry-based phosphoproteomics is one of the most powerful tools available for investigating the detailed molecular events that occur in response to cellular stimuli. Experiments can routinely detect and quantify thousands of phosphorylated peptides, and interpreting this data, and extracting biological meaning, remains challenging.  This webinar provides an overview of the phosphoproteomics data analysis website, Phosphomatics, that incorporates a suite of tools and resources for statistical and functional analysis that aim to simplify the process of extracting meaningful insights from experimental results. Phosphomatics can natively import search and quantitation results from major search engines including MaxQuant and Proteome Discoverer and employs intuitive ‘wizards’ to guide users through data preprocessing routines such as filtering, normalization and transformation. A graphical platform of interactive univariate and multivariate analysis features is provided that allow subgroups of the uploaded data containing phosphosites of statistical interest to be created and interrogated through further functional analysis. A range of databases have been integrated that, for example, provide ligand and inhibitor information for key proteins or highlight key modification sites known to be involved in functional state regulation. At each step, published literature is natively incorporated along with a ‘bibliography builder’ that allows references of interest to be assembled and exported in various formats. Taken together, these expanded features aim to provide a ‘one-stop-shop’ for phosphoproteomics data analysis. The webinar is followed by a short Q&A session. 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. - Phosphomatics -slides  (PDF and PPTX): Slides used in the presentation **Materials shared elsewhere:** A recording of the webinar is available on the Australian BioCommons YouTube Channel: https://youtu.be/_WpeL5t2DSI Melissa Burke (melissa@biocommons.org.au) Phosphoproteomics, Proteomics, Mass spectrometry
WEBINAR: Getting started with deep learning

This record includes training materials associated with the Australian BioCommons webinar  ‘Getting started with deep learning’. This webinar took place on 21 July 2021.

Are you wondering what deep learning is and how it might be useful in your research? This high level overview introduces...

Keywords: Deep learning, Neural networks, Machine learning

WEBINAR: Getting started with deep learning https://dresa.org.au/materials/webinar-getting-started-with-deep-learning-d7b1fac1-ebae-426d-8bc0-d82cfda8e8ad This record includes training materials associated with the Australian BioCommons webinar  ‘Getting started with deep learning’. This webinar took place on 21 July 2021. Are you wondering what deep learning is and how it might be useful in your research? This high level overview introduces deep learning ‘in a nutshell’ and provides tips on which concepts and skills you will need to know to build a deep learning application. The presentation also provides pointers to various resources you can use to get started in deep learning. The webinar is followed by a short Q&A session. 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. - Getting Started with Deep Learning - Slides (PDF): Slides used in the presentation **Materials shared elsewhere:** A recording of the webinar is available on the Australian BioCommons YouTube Channel: https://youtu.be/I1TmpnZUuiQ Melissa Burke (melissa@biocommons.org.au) Deep learning, Neural networks, Machine learning
WEBINAR: Detection of and phasing of hybrid accessions in a target capture dataset

This record includes training materials associated with the Australian BioCommons webinar ‘Detection of and phasing of hybrid accessions in a target capture dataset’. This webinar took place on 10 June 2021.

Hybridisation plays an important role in evolution, leading to the exchange of genes...

Keywords: Phylogenetics, Bioinformatics, Phylogeny, Genomics, Target capture sequencing

WEBINAR: Detection of and phasing of hybrid accessions in a target capture dataset https://dresa.org.au/materials/webinar-detection-of-and-phasing-of-hybrid-accessions-in-a-target-capture-dataset This record includes training materials associated with the Australian BioCommons webinar ‘Detection of and phasing of hybrid accessions in a target capture dataset’. This webinar took place on 10 June 2021. Hybridisation plays an important role in evolution, leading to the exchange of genes between species and, in some cases, generate new lineages. The use of molecular methods has revealed the frequency and importance of reticulation events is higher than previously thought and this insight continues with the ongoing development of phylogenomic methods that allow novel insights into the role and extent of hybridisation. Hybrids notoriously provide challenges for the reconstruction of evolutionary relationships, as they contain conflicting genetic information from their divergent parental lineages. However, this also provides the opportunity to gain insights into the origin of hybrids (including autopolyploids). This webinar explores some of the challenges and opportunities that occur when hybrids are included in a target capture sequence dataset. In particular, it describes the impact of hybrid accessions on sequence assembly and phylogenetic analysis and further explores how the information of the conflicting phylogenetic signal can be used to detect and resolve hybrid accessions. The webinar showcases a novel bioinformatic workflow, HybPhaser, that can be used to detect and phase hybrids in target capture datasets and will provide the theoretical background and concepts behind the workflow. This webinar is part of a series of webinars and workshops developed by the Genomics for Australian Plants (GAP) Initiative that focuses on the analysis of target capture sequence data. In addition to two public webinars, the GAP bioinformatics working group is offering training workshops in the use of newly developed and existing scripts in an integrated workflow to participants in the 2021 virtual Australasian Systematic Botany Society Conference. The materials are shared under a Creative Commons 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. - Nauheimer_hybphaser_slides (PDF): Slides presented during the webinar **Materials shared elsewhere:** A recording of the webinar is available on the Australian BioCommons YouTube Channel: https://youtu.be/japXwTAhA5U Melissa Burke (melissa@biocommons.org.au) Phylogenetics, Bioinformatics, Phylogeny, Genomics, Target capture sequencing