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Authors: Barlow, Melanie (orcid: 000...  or Doyle, Maria  or Downton, Matthew (orcid: 00...  or Freytag, Saskia (orcid: 000... 

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-1c8f2b21-bc4b-4b42-9a5d-d6096a2afbe6 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: Pro tips for scaling bioinformatics workflows to HPC

This record includes training materials associated with the Australian BioCommons webinar ‘Pro tips for scaling bioinformatics workflows to HPC’. This webinar took place on 31 May 2023.

Event description 

High Performance Computing (HPC) infrastructures offer the computational scale and...

Keywords: Bioinformatics, Workflows, HPC, High Performance Computing

WEBINAR: Pro tips for scaling bioinformatics workflows to HPC https://dresa.org.au/materials/webinar-pro-tips-for-scaling-bioinformatics-workflows-to-hpc-9f2a8b90-88da-433b-83b2-b1ab262dd9df This record includes training materials associated with the Australian BioCommons webinar ‘Pro tips for scaling bioinformatics workflows to HPC’. This webinar took place on 31 May 2023. Event description  High Performance Computing (HPC) infrastructures offer the computational scale and efficiency that life scientists need to handle complex biological datasets and multi-step computational workflows. But scaling workflows to HPC from smaller, more familiar computational infrastructures brings with it new jargon, expectations, and processes to learn. To make the most of HPC resources, bioinformatics workflows need to be designed for distributed computing environments and carefully manage varying resource requirements, and data scale related to biology.   In this webinar, Dr Georgina Samaha from the Sydney Informatics Hub, Dr Matthew Downton from the National Computational Infrastructure (NCI) and Dr Sarah Beecroft from the Pawsey Supercomputing Research Centre help you navigate the world of HPC for running and developing bioinformatics workflows. They explain when you should take your workflows to HPC and highlight the architectural features you should make the most of to scale your analyses once you’re there. You’ll hear pro-tips for dealing with common pain points like software installation, optimising for parallel computing and resource management, and will find out how to get access to Australia’s National HPC infrastructures at NCI and Pawsey.  Materials 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. Pro-tips_HPC_Slides: 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/YKJDRXCmGMo Melissa Burke (melissa@biocommons.org.au) Bioinformatics, Workflows, HPC, High Performance Computing
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-81aa00db-63ad-4962-a7ac-b885bf9f676b 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
ARDC FAIR Data 101 self-guided

FAIR Data 101 v3.0 is a self-guided course covering the FAIR Data principles

The FAIR Data 101 virtual course was designed and delivered by the ARDC Skilled Workforce Program twice in 2020 and has now been reworked as a self-guided course.

The course structure was based on 'FAIR Data in the...

Keywords: training material, FAIR data, video, webinar, activities, quiz, FAIR, research data management

ARDC FAIR Data 101 self-guided https://dresa.org.au/materials/ardc-fair-data-101-self-guided-2d794a84-f0ff-4e11-a39c-fa8ea481e097 FAIR Data 101 v3.0 is a self-guided course covering the FAIR Data principles The FAIR Data 101 virtual course was designed and delivered by the ARDC Skilled Workforce Program twice in 2020 and has now been reworked as a self-guided course. The course structure was based on 'FAIR Data in the Scholarly Communications Lifecycle', run by Natasha Simons at the FORCE11 Scholarly Communications Institute. These training materials are hosted on GitHub. contact@ardc.edu.au training material, FAIR data, video, webinar, activities, quiz, FAIR, research data management
WEBINAR: Pro tips for scaling bioinformatics workflows to HPC

This record includes training materials associated with the Australian BioCommons webinar ‘Pro tips for scaling bioinformatics workflows to HPC’. This webinar took place on 31 May 2023.

Event description 

High Performance Computing (HPC) infrastructures offer the computational scale and...

Keywords: Bioinformatics, Workflows, HPC, High Performance Computing

WEBINAR: Pro tips for scaling bioinformatics workflows to HPC https://dresa.org.au/materials/webinar-pro-tips-for-scaling-bioinformatics-workflows-to-hpc This record includes training materials associated with the Australian BioCommons webinar ‘Pro tips for scaling bioinformatics workflows to HPC’. This webinar took place on 31 May 2023. Event description  High Performance Computing (HPC) infrastructures offer the computational scale and efficiency that life scientists need to handle complex biological datasets and multi-step computational workflows. But scaling workflows to HPC from smaller, more familiar computational infrastructures brings with it new jargon, expectations, and processes to learn. To make the most of HPC resources, bioinformatics workflows need to be designed for distributed computing environments and carefully manage varying resource requirements, and data scale related to biology.   In this webinar, Dr Georgina Samaha from the Sydney Informatics Hub, Dr Matthew Downton from the National Computational Infrastructure (NCI) and Dr Sarah Beecroft from the Pawsey Supercomputing Research Centre help you navigate the world of HPC for running and developing bioinformatics workflows. They explain when you should take your workflows to HPC and highlight the architectural features you should make the most of to scale your analyses once you’re there. You’ll hear pro-tips for dealing with common pain points like software installation, optimising for parallel computing and resource management, and will find out how to get access to Australia’s National HPC infrastructures at NCI and Pawsey.  Materials 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. Pro-tips_HPC_Slides: 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/YKJDRXCmGMo Melissa Burke (melissa@biocommons.org.au) Bioinformatics, Workflows, HPC, High Performance Computing
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: 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
ARDC FAIR Data 101 self-guided

FAIR Data 101 v3.0 is a self-guided course covering the FAIR Data principles

The FAIR Data 101 virtual course was designed and delivered by the ARDC Skilled Workforce Program twice in 2020 and has now been reworked as a self-guided course.

The course structure was based on 'FAIR Data in the...

Keywords: training material, FAIR data, video, webinar, activities, quiz, FAIR, research data management

ARDC FAIR Data 101 self-guided https://dresa.org.au/materials/ardc-fair-data-101-self-guided-bba41a59-8479-4f4f-b9ee-337b9eb294bf FAIR Data 101 v3.0 is a self-guided course covering the FAIR Data principles The FAIR Data 101 virtual course was designed and delivered by the ARDC Skilled Workforce Program twice in 2020 and has now been reworked as a self-guided course. The course structure was based on 'FAIR Data in the Scholarly Communications Lifecycle', run by Natasha Simons at the FORCE11 Scholarly Communications Institute. These training materials are hosted on GitHub. contact@ardc.edu.au training material, FAIR data, video, webinar, activities, quiz, FAIR, research data management