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Authors: Barlow, Melanie (orcid: 000...  or Doyle, Maria  or Downton, Matthew (orcid: 00...  or Morgan, Steven (orcid: 0000... 

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...

Keywords: Bioinformatics, Analysis, Workflows, Galaxy Australia

WORKSHOP: Online data analysis for biologists https://dresa.org.au/materials/workshop-online-data-analysis-for-biologists-08d66913-4ce3-4528-bdd6-0b0fcf234982 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
WORKSHOP: RNA-Seq: reads to differential genes and pathways

This record includes training materials associated with the Australian BioCommons workshop ‘RNA-Seq: reads to differential genes and pathways’. This workshop took place over two, 3.5 hour sessions on 27 and 28 September 2022.

Event description

RNA sequencing (RNA-seq) is a common method used to...

Keywords: Bioinformatics, Analysis, Transcriptomics, RNA-seq, Workflows, Nextflow, nf-co.re

WORKSHOP: RNA-Seq: reads to differential genes and pathways https://dresa.org.au/materials/workshop-rna-seq-reads-to-differential-genes-and-pathways-5a384156-d3de-4d5d-9797-e689bf6592f8 This record includes training materials associated with the Australian BioCommons workshop ‘RNA-Seq: reads to differential genes and pathways’. This workshop took place over two, 3.5 hour sessions on 27 and 28 September 2022. Event description RNA sequencing (RNA-seq) is a common method used to understand the differences in gene expression and molecular pathways between two or more groups. This workshop introduces the fundamental concepts of RNA sequencing experiments and will allow you to try out the analysis using data from a study of Williams-Beuren Syndrome, a rare disease.  In the first part of the workshop you will learn how to convert sequence reads into analysis ready count data. To do this we will use nf-core/rnaseq - a portable, scalable, reproducible and publicly available workflow on Pawsey Nimbus Cloud. In the second part of the workshop you will use the count data you created to identify differential genes and pathways using R/Rstudio. By the end of the workshop, you should be able to perform your own RNA-seq analysis for differential gene expression and pathway analysis! This workshop is presented by the Australian BioCommons and Sydney Informatics Hub 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. RNAseq reads to differential genes and pathways - Additional Resources (PDF): Additional resources compiled by the Sydney Informatics Hub rnaseq_DE_analysis_Day2.html: HTML version of code used on day 2 of the workshop rnaseq_DE_analysis_Day2.Rmd: R Markdown version of code used on day 2 of the workshop RNAseq reads to differential genes and pathways_Q_and_A (PDF): Archive of questions and their answers from the workshop Slack Channel. Materials shared elsewhere: This workshop follows the tutorial ‘RNA-seq: reads to differential gene expression workshop series’ developed by the Sydney Informatics Hub. https://sydney-informatics-hub.github.io/training.RNAseq.series-quarto/ Melissa Burke (melissa@biocommons.org.au) Bioinformatics, Analysis, Transcriptomics, RNA-seq, Workflows, Nextflow, nf-co.re
WORKSHOP: Single cell RNAseq analysis in R

This record includes training materials associated with the Australian BioCommons workshop ‘Single cell RNAseq analysis in R’. This workshop took place over two, 3.5 hour sessions on 22 and 3 August 2022.

Event description

Analysis and interpretation of single cell RNAseq (scRNAseq) data...

Keywords: Bioinformatics, Analysis, Transcriptomics, R software, Single cell RNAseq, scRNAseq

WORKSHOP: Single cell RNAseq analysis in R https://dresa.org.au/materials/workshop-single-cell-rnaseq-analysis-in-r-4f60b82d-2f1e-4021-9569-6955878dd945 This record includes training materials associated with the Australian BioCommons workshop ‘Single cell RNAseq analysis in R’. This workshop took place over two, 3.5 hour sessions on 22 and 3 August 2022. Event description Analysis and interpretation of single cell RNAseq (scRNAseq) data requires dedicated workflows. In this hands-on workshop we will show you how to perform single cell analysis using Seurat - an R package for QC, analysis, and exploration of single-cell RNAseq data.  We will discuss the ‘why’ behind each step and cover reading in the count data, quality control, filtering, normalisation, clustering, UMAP layout and identification of cluster markers. We will also explore various ways of visualising single cell expression data. This workshop is presented by the Australian BioCommons and Queensland Cyber Infrastructure Foundation (QCIF) 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. scRNAseq_Slides (PDF): Slides used to introduce topics scRNAseq_Schedule (PDF): A breakdown of the topics and timings for the workshop scRNAseq_Resources (PDF): A list of resources recommended by trainers and participants scRNAseq_QandA(PDF): Archive of questions and their answers from the workshop Slack Channel.   Materials shared elsewhere: This workshop follows the tutorial ‘scRNAseq Analysis in R with Seurat’ https://swbioinf.github.io/scRNAseqInR_Doco/index.html This material is based on the introductory Guided Clustering Tutorial tutorial from Seurat. It is also drawing from a similar workshop held by Monash Bioinformatics Platform Single-Cell-Workshop, with material here. Melissa Burke (melissa@biocommons.org.au) Bioinformatics, Analysis, Transcriptomics, R software, Single cell RNAseq, scRNAseq
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
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: 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...

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-714004ba-0348-47c8-a68f-038a1f8ccfb1 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
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: RNA-Seq: reads to differential genes and pathways

This record includes training materials associated with the Australian BioCommons workshop ‘RNA-Seq: reads to differential genes and pathways’. This workshop took place over two, 3.5 hour sessions on 27 and 28 September 2022.

Event description

RNA sequencing (RNA-seq) is a common method...

Keywords: Bioinformatics, Analysis, Transcriptomics, RNA-seq, Workflows, Nextflow, nf-co.re

WORKSHOP: RNA-Seq: reads to differential genes and pathways https://dresa.org.au/materials/workshop-rna-seq-reads-to-differential-genes-and-pathways This record includes training materials associated with the Australian BioCommons workshop ‘RNA-Seq: reads to differential genes and pathways’. This workshop took place over two, 3.5 hour sessions on 27 and 28 September 2022. **Event description** RNA sequencing (RNA-seq) is a common method used to understand the differences in gene expression and molecular pathways between two or more groups. This workshop introduces the fundamental concepts of RNA sequencing experiments and will allow you to try out the analysis using data from a study of Williams-Beuren Syndrome, a rare disease.  In the first part of the workshop you will learn how to convert sequence reads into analysis ready count data. To do this we will use nf-core/rnaseq - a portable, scalable, reproducible and publicly available workflow on Pawsey Nimbus Cloud. In the second part of the workshop you will use the count data you created to identify differential genes and pathways using R/Rstudio. By the end of the workshop, you should be able to perform your own RNA-seq analysis for differential gene expression and pathway analysis! This workshop is presented by the Australian BioCommons and Sydney Informatics Hub 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. * RNAseq reads to differential genes and pathways - Additional Resources (PDF): Additional resources compiled by the Sydney Informatics Hub * rnaseq_DE_analysis_Day2.html: HTML version of code used on day 2 of the workshop * rnaseq_DE_analysis_Day2.Rmd: R Markdown version of code used on day 2 of the workshop * RNAseq reads to differential genes and pathways_Q_and_A (PDF): Archive of questions and their answers from the workshop Slack Channel. **Materials shared elsewhere:** This workshop follows the tutorial ‘RNA-seq: reads to differential gene expression workshop series’ developed by the Sydney Informatics Hub. https://sydney-informatics-hub.github.io/training.RNAseq.series-quarto/ Melissa Burke (melissa@biocommons.org.au) Bioinformatics, Analysis, Transcriptomics, RNA-seq, Workflows, Nextflow, nf-co.re
Introduction to Unix

A hands-on workshop covering the basics of the Unix command line interface.

Knowledge of the Unix operating system is fundamental to the use of many popular bioinformatics command-line tools. Whether you choose to run your analyses locally or on a high-performance computing system, knowing...

Keywords: Unix, Command line, Command-line, CLI

Resource type: tutorial

Introduction to Unix https://dresa.org.au/materials/introduction-to-unix A hands-on workshop covering the basics of the Unix command line interface. Knowledge of the Unix operating system is fundamental to the use of many popular bioinformatics command-line tools. Whether you choose to run your analyses locally or on a high-performance computing system, knowing your way around a command-line interface is highly valuable. This workshop will introduce you to Unix concepts by way of a series of hands-on exercises. This workshop is designed for participants with little or no command-line knowledge. Tools: Standard Unix commands, FileZilla Topic overview: Section 1: Getting started Section 2: Exploring your current directory Section 3: Making and changing directories Section 4: Viewing and manipulating files Section 5: Removing files and directories Section 6: Searching files Section 7: Putting it all together Section 8: Transferring files Tutorial instructions available here: https://www.melbournebioinformatics.org.au/tutorials/tutorials/unix/unix/ For queries relating to this workshop, contact Melbourne Bioinformatics (bioinformatics-training@unimelb.edu.au). Find out when we are next running this training as an in-person workshop, by visiting the Melbourne Bioinformaitcs Eventbrite page: https://www.eventbrite.com.au/o/melbourne-bioinformatics-13058846490 For queries relating to this workshop, contact Melbourne Bioinformatics (bioinformatics-training@unimelb.edu.au). Unix, Command line, Command-line, CLI ugrad masters mbr phd ecr researcher support professional
WORKSHOP: Single cell RNAseq analysis in R

This record includes training materials associated with the Australian BioCommons workshop Single cell RNAseq analysis in R. This workshop took place over two, 3.5 hour sessions on 22 and 3 August 2022.

Event description

Analysis and interpretation of single cell RNAseq (scRNAseq) data...

Keywords: Bioinformatics, Analysis, Transcriptomics, R software, Single cell RNAseq, scRNAseq

WORKSHOP: Single cell RNAseq analysis in R https://dresa.org.au/materials/workshop-single-cell-rnaseq-analysis-in-r This record includes training materials associated with the Australian BioCommons workshop Single cell RNAseq analysis in R. This workshop took place over two, 3.5 hour sessions on 22 and 3 August 2022. **Event description** Analysis and interpretation of single cell RNAseq (scRNAseq) data requires dedicated workflows. In this hands-on workshop we will show you how to perform single cell analysis using Seurat - an R package for QC, analysis, and exploration of single-cell RNAseq data.  We will discuss the ‘why’ behind each step and cover reading in the count data, quality control, filtering, normalisation, clustering, UMAP layout and identification of cluster markers. We will also explore various ways of visualising single cell expression data. This workshop is presented by the Australian BioCommons and Queensland Cyber Infrastructure Foundation (QCIF) 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. * scRNAseq_Slides (PDF): Slides used to introduce topics * scRNAseq_Schedule (PDF): A breakdown of the topics and timings for the workshop * scRNAseq_Resources (PDF): A list of resources recommended by trainers and participants * scRNAseq_QandA(PDF): Archive of questions and their answers from the workshop Slack Channel. Materials shared elsewhere: This workshop follows the tutorial ‘scRNAseq Analysis in R with Seurat’ https://swbioinf.github.io/scRNAseqInR_Doco/index.html This material is based on the introductory Guided Clustering Tutorial tutorial from Seurat. It is also drawing from a similar workshop held by Monash Bioinformatics Platform Single-Cell-Workshop, with material here. Melissa Burke (melissa@biocommons.org.au) Bioinformatics, Analysis, Transcriptomics, R software, Single cell RNAseq, scRNAseq
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
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: 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
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