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9 materials found

Authors: Barlow, Melanie (orcid: 000...  or Freytag, Saskia (orcid: 000...  or Amanda Miotto 


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
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
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
Create a website resume

Written for the Qld Research Bazaar conference 2021, this self paced lesson breaks down how to use Github pages to make a resume, with a simple and basic template to start off with. It discusses how to use Markdown and minimum HTML to customize the template, and offers explanations on how the...

Keywords: personal development, website

Resource type: tutorial, guide

Create a website resume https://dresa.org.au/materials/create-a-website-resume Written for the Qld Research Bazaar conference 2021, this self paced lesson breaks down how to use Github pages to make a resume, with a simple and basic template to start off with. It discusses how to use Markdown and minimum HTML to customize the template, and offers explanations on how the components work together. a.miotto@griffith.edu.au personal development, website
10 Reproducible Research things - Building Business Continuity

The idea that you can duplicate an experiment and get the same conclusion is the basis for all scientific discoveries. Reproducible research is data analysis that starts with the raw data and offers a transparent workflow to arrive at the same results and conclusions. However not all studies are...

Keywords: reproducibility, data management

Resource type: tutorial, video

10 Reproducible Research things - Building Business Continuity https://dresa.org.au/materials/9-reproducible-research-things-building-business-continuity The idea that you can duplicate an experiment and get the same conclusion is the basis for all scientific discoveries. Reproducible research is data analysis that starts with the raw data and offers a transparent workflow to arrive at the same results and conclusions. However not all studies are replicable due to lack of information on the process. Therefore, reproducibility in research is extremely important. Researchers genuinely want to make their research more reproducible, but sometimes don’t know where to start and often don’t have the available time to investigate or establish methods on how reproducible research can speed up every day work. We aim for the philosophy “Be better than you were yesterday”. Reproducibility is a process, and we highlight there is no expectation to go from beginner to expert in a single workshop. Instead, we offer some steps you can take towards the reproducibility path following our Steps to Reproducible Research self paced program. Video: https://www.youtube.com/watch?v=bANTr9RvnGg Tutorial: https://guereslib.github.io/ten-reproducible-research-things/ a.miotto@griffith.edu.au; s.stapleton@griffith.edu.au; i.jennings@griffith.edu.au; Sharron Stapleton Isaac Jennings reproducibility, data management masters phd ecr researcher support
Data Storytelling

Nowadays, more information created than our audience could possibly analyse on their own! A study by Stanford professor Chip Heath found that during the recall of speeches, 63% of people remember stories and how they made them feel, but only 5% remember a single statistic. So, you should convert...

Keywords: data storytelling, data visualisation

Data Storytelling https://dresa.org.au/materials/data-storytelling Nowadays, more information created than our audience could possibly analyse on their own! A study by Stanford professor Chip Heath found that during the recall of speeches, 63% of people remember stories and how they made them feel, but only 5% remember a single statistic. So, you should convert your insights and discovery from data into stories to share with non-experts with a language they understand. But how? This tutorial helps you construct stories that incite an emotional response and create meaning and understanding for the audience by applying data storytelling techniques. m.yamaguchi@griffith.edu.au a.miotto@griffith.edu.au data storytelling, data visualisation support masters phd researcher