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Authors: Barlow, Melanie (orcid: 000...  or Chung, Jessica (orcid: 0000...  or Chandrananda, Dineika (orci...  or Brian Ballsun-Stanton 

WORKSHOP: RNASeq: reads to differential genes and pathways

This record includes training materials associated with the Australian BioCommons workshop 'RNASeq: reads to differential genes and pathways'. This workshop took place over two, 3 hour sessions on 11 and 12 October 2023.Event descriptionRNA sequencing (RNAseq) is a popular and powerful technique...

Keywords: bioinformatics, transcriptomics, RNA-seq, RNAseq

WORKSHOP: RNASeq: reads to differential genes and pathways https://dresa.org.au/materials/workshop-rnaseq-reads-to-differential-genes-and-pathways This record includes training materials associated with the Australian BioCommons workshop 'RNASeq: reads to differential genes and pathways'. This workshop took place over two, 3 hour sessions on 11 and 12 October 2023.Event descriptionRNA sequencing (RNAseq) is a popular and powerful technique used to understand the activity of genes. Using differential gene profiling methods, we can use RNAseq data to gain valuable insights into gene activity and identify variability in gene expression between samples to understand the molecular pathways underpinning many different traits.  In this hands-on workshop, you will learn RNAseq fundamentals as you process, analyse, and interpret the results from a real RNAseq experiment on the command-line. In session one, you will convert raw sequence reads to analysis-ready count data with the nf-core/rnaseq workflow. In session two, you'll work interactively in RStudio to identify differentially expressed genes,perform functional enrichment analysis, and visualise and interpret your results using popular and best practice R packages.  This workshop was delivered as a part of the Australian BioCommons Bring Your Own Data Platforms Project and will provide you with an opportunity to explore services and infrastructure built specifically for life scientists working at the command line. By the end of the workshop, you will be familiar with Pawsey's Nimbus cloud platform and be able to process your own RNAseq datasets and perform differential expression analysis on the command-line. Materials are shared under a Creative Commons Attribution 4.0 International agreement unless otherwise specified and were current at the time of the event.Lead trainers: Dr Georgina Samaha (Sydney Informatics Hub), Dr Nandan Deshpande (Sydney Informatics Hub)Facilitators: Ching-Yu Lu and Jessica Chung.Infrastructure provision: Audrey Stott (Pawsey Supercomputing Research Centre), Alex Ip (AARNet)Host: Melissa Burke, Australian BioCommons Training materialsFiles 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:This workshop follows the tutorial 'Introduction to RNAseq workshop: reads to differential gene expression' developed by the Sydney Informatics Hub.https://sydney-informatics-hub.github.io/rnaseq-workshop-2023/Additional supporting materials are available via GitHubRstudio rnaseq container: https://github.com/Sydney-Informatics-Hub/Rstudio-rnaseq-contained/tree/mainRNAseq differential expression R notebook: https://github.com/Sydney-Informatics-Hub/rna-differential-expression-Rnotebook Melissa Burke (melissa@biocommons.org.au) bioinformatics, transcriptomics, RNA-seq, RNAseq
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
A hands on introduction to Large Language Models like Bing Chat and ChatGPT

Event run 7 June at the MQ Incubator. Event description:

A two-hour hands-on workshop giving a brief history of the last 4 months of development of "Generative AI."

These tools, these Large Language Models, offer present promise and peril -- disruption -- to ways of working and of...

Keywords: Large Language Model, ChatGPT

A hands on introduction to Large Language Models like Bing Chat and ChatGPT https://dresa.org.au/materials/a-hands-on-introduction-to-large-language-models-like-bing-chat-and-chatgpt Event run 7 June at the MQ Incubator. Event description: A two-hour hands-on workshop giving a brief history of the last 4 months of development of "Generative AI." These tools, these Large Language Models, offer present promise and peril -- disruption -- to ways of working and of learning. Outside the "hype," these tools are "calculators for words" and allow the same manipulation and reflection of a user's words as a calculator offers for a user's numbers. The workshop will guide users into using various free and paid tools, and the effective use of Large Language Models through chain of thought prompting. Remember: a LLM is "Always confident and usually correct." OSF Description (LLM generated): This two-hour workshop provides a comprehensive introduction to the world of Large Language Models (LLMs), focusing on the recent advancements in Generative AI. Participants will gain insights into the development and functionality of prominent LLMs such as Bing Chat and ChatGPT. The workshop will delve into the concept of LLMs as "calculators for words," highlighting their potential to revolutionize ways of working and learning. The session will explore the principles of Prompt Engineering and Transactional Prompting, demonstrating how consistent prompts can yield reliable and reproducible results. Participants will also learn about the practical applications of LLMs, including editing and proofreading papers, generating technical documentation, recipe ideation, and more. The workshop emphasizes the importance of understanding the terms of use and the responsibilities that come with using these powerful AI tools. By the end of the session, participants will be equipped with the knowledge and skills to effectively use LLMs in various contexts, guided by the mantra that a LLM is "Always confident and usually correct." Brian Ballsun-Stanton (brian.ballsun-stanton@mq.edu.au) Large Language Model, ChatGPT researcher
Managing Active Research Data

In this train-the-trainer workshop, we will be exploring and discussing methods for active data management.

Participants will become familiar with cloud storage and associated tools and services for managing active research data. Learn how to organise, maintain, store and analyse active data,...

Keywords: RDM Training, CloudStor, cloud

Resource type: lesson

Managing Active Research Data https://dresa.org.au/materials/managing-active-research-data In this train-the-trainer workshop, we will be exploring and discussing methods for active data management. Participants will become familiar with cloud storage and associated tools and services for managing active research data. Learn how to organise, maintain, store and analyse active data, and understand safe and secure ways of sharing and storing data. Topics such as cloud storage, collaborative editing, versioning and data sharing will be discussed and demonstrated. Sara King RDM Training, CloudStor, cloud phd support masters ecr researcher
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
Research Data Management (RDM) Online Orientation Module (Macquarie University)

This is a self-paced, guided orientation to the essential elements of Research Data Management. It is available for others to use and modify.
The course introduces the following topics: data policies, data sensitivity, data management planning, storage and security, organisation and metadata,...

Keywords: research data, data management, FAIR data, training

Resource type: quiz, activity, other

Research Data Management (RDM) Online Orientation Module (Macquarie University) https://dresa.org.au/materials/macquarie-university-research-data-management-rdm-online This is a self-paced, guided orientation to the essential elements of Research Data Management. It is available for others to use and modify. The course introduces the following topics: data policies, data sensitivity, data management planning, storage and security, organisation and metadata, benefits of data sharing, licensing, repositories, and best practice including the FAIR principles. Embedded activities and examples help extend learner experience and awareness. The course was designed to assist research students and early career researchers in complying with policies and legislative requirements, understand safe data practices, raise awareness of the benefits of data curation and data sharing (efficiency and impact) and equip them with the required knowledge to plan their data management early in their projects. This course is divided into four sections 1. Crawl - What is Research Data and why care for it? Policy and legislative requirements. The Research Data Life-cycle. Data Management Planning (~30 mins) 2. Walk - Data sensitivity, identifiability, storage, and security (~60 mins) 3. Run - Record keeping, data retention, file naming, folder structures, version control, metadata, data sharing, open data, licences, data repositories, data citation, and ethics (~75 mins) 4. Jump - Best practice FAIR data principles (~45 mins) 5. Fight - Review - a quiz designed to review and reinforce knowledge (~15 mins) https://rise.articulate.com/share/-AWqSPaEI_jTbHwzQHdmQ43R50edrCl0 * *Password: "FAIR" *Password: "FAIR" Any queries or suggestions for course improvement can be directed to the Macquarie University Research Integrity Team: Dr Paul Sou (paul.sou@mq.edu.au) or Dr Shannon Smith (shannon.smith@mq.edu.au). Scorm files can be made available upon request. research data, data management, FAIR data, training