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Authors: Barlow, Melanie (orcid: 000...  or Emilia Decker  or Martinez, Paula Andrea (orc...  or Zhang, Eden (orcid: 0000-00... 

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 Training Materials Metadata Checklist v1.1

The ARDC Training Materials Metadata Checklist aims to support learning designers, training materials creators, trainers and national training infrastructure providers to capture key information and apply appropriate mechanisms to enable sharing and reuse of their training materials

Keywords: checklist, Training material, FAIR, standard, requirements, metadata

ARDC Training Materials Metadata Checklist v1.1 https://dresa.org.au/materials/ardc-training-materials-metadata-checklist-v1-1 The ARDC Training Materials Metadata Checklist aims to support learning designers, training materials creators, trainers and national training infrastructure providers to capture key information and apply appropriate mechanisms to enable sharing and reuse of their training materials contact@ardc.edu.au checklist, Training material, FAIR, standard, requirements, metadata
Training resources for sharing and reuse

This presentation outlines the work completed during a consultancy for ARDC by Dr Paula Martinez to develop new and publish existing national skills materials for reuse by the sector. She was responsible for the work package targeted to co-develop national skills materials with a strong emphasis...

Keywords: FAIR training material, training material, guides, software citation, software publishing, containers, software licensing, training materials checklist, research data governance

Training resources for sharing and reuse https://dresa.org.au/materials/training-resources-for-sharing-and-reuse-6ecee7a3-6821-4149-92ab-e335daa571a8 This presentation outlines the work completed during a consultancy for ARDC by Dr Paula Martinez to develop new and publish existing national skills materials for reuse by the sector. She was responsible for the work package targeted to co-develop national skills materials with a strong emphasis on sharing and reuse. This was a very collaborative project with the opportunity to work with different target audiences, topics and support expertise. To accommodate for a short timeline. We defined the scope to six topics. 1) Containers in Research 2) Data Governance 3) Software citation and Licensing 4) FAIR Data 101 5) Metadata for Training Materials 6) Machine Learning Resources. You can watch the video on YouTube here: https://youtu.be/10Yv_BFa-mw contact@ardc.edu.au FAIR training material, training material, guides, software citation, software publishing, containers, software licensing, training materials checklist, research data governance
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
Exploratory Data Analysis

This is the second of three modules in our exciting new machine learning workshop series by the Sydney Informatics Hub (SIH).

Module 1: https://youtu.be/dMwHFhKWRRI

Module 3:...

Keywords: Data analysis, training material

Exploratory Data Analysis https://dresa.org.au/materials/exploratory-data-analysis This is the second of three modules in our exciting new machine learning workshop series by the Sydney Informatics Hub (SIH). **Module 1**: [https://youtu.be/dMwHFhKWRRI](https://youtu.be/dMwHFhKWRRI) **Module 3**: [https://github.com/Sydney-Informatics-Hub/Module3R](https://github.com/Sydney-Informatics-Hub/Module3R) *The Sydney Informatics Hub is a Core Research Facility at The University of Sydney, enabling excellence in research* [https://sydney.edu.au/informatics-hub](https://sydney.edu.au/informatics-hub) sih.training@sydney.edu.au Mori, Giorgia (orcid: 0000-0003-3469-5632) Data analysis, training material
Fundamentals of Machine Learning

This is the first of four modules in our exciting new machine learning workshop series by the Sydney Informatics Hub (SIH).

Module 2: https://youtu.be/HVAFflj2PS0
Module 3:...

Keywords: Machine Learning, training material

Fundamentals of Machine Learning https://dresa.org.au/materials/fundamentals-of-machine-learning This is the first of four modules in our exciting new machine learning workshop series by the Sydney Informatics Hub (SIH). **Module 2**: [https://youtu.be/HVAFflj2PS0](https://youtu.be/HVAFflj2PS0) **Module 3**: [https://github.com/Sydney-Informatics-Hub/Module3R](https://github.com/Sydney-Informatics-Hub/Module3R) *The Sydney Informatics Hub is a Core Research Facility at The University of Sydney, enabling excellence in research* [https://sydney.edu.au/informatics-hub](https://sydney.edu.au/informatics-hub) sih.training@sydney.edu.au Machine Learning, training material
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
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
Training resources for sharing and reuse

This presentation outlines the work completed during a consultancy for ARDC by Dr Paula Martinez to develop new and publish existing national skills materials for reuse by the sector. She was responsible for the work package targeted to co-develop national skills materials with a strong emphasis...

Keywords: FAIR training material, training material, guides, software citation, software publishing, containers, software licensing, training materials checklist, research data governance

Training resources for sharing and reuse https://dresa.org.au/materials/training-resources-for-sharing-and-reuse This presentation outlines the work completed during a consultancy for ARDC by Dr Paula Martinez to develop new and publish existing national skills materials for reuse by the sector. She was responsible for the work package targeted to co-develop national skills materials with a strong emphasis on sharing and reuse. This was a very collaborative project with the opportunity to work with different target audiences, topics and support expertise. To accommodate for a short timeline. We defined the scope to six topics. 1) Containers in Research 2) Data Governance 3) Software citation and Licensing 4) FAIR Data 101 5) Metadata for Training Materials 6) Machine Learning Resources. You can watch the video on YouTube here: https://youtu.be/10Yv_BFa-mw contact@ardc.edu.au FAIR training material, training material, guides, software citation, software publishing, containers, software licensing, training materials checklist, research data governance