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Authors: Harrison, Paul (orcid: 0000...  or Hall, Grace (orcid: 0000-00... 

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: 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 26 and 27 October 2023.Event descriptionAnalysis and interpretation of single cell RNAseq (scRNAseq) data requires...

Keywords: bioinformatics, transcriptomics, single cell RNA-seq, Seurat, R statistical software

WORKSHOP: Single cell RNAseq analysis in R https://dresa.org.au/materials/workshop-single-cell-rnaseq-analysis-in-r-6a1126cf-7105-43ec-bf55-7c492f758301 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 26 and 27 October 2023.Event descriptionAnalysis 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, Queensland Cyber Infrastructure Foundation (QCIF) and the Monash Genomics and Bioinformatics Platform with the assistance of a network of facilitators from the national Bioinformatics Training Cooperative.Lead trainers: Sarah Williams, Adele Barugahare, Paul Harrison, Laura Perlaza JimenezFacilitators: Nick Matigan, Valentine Murigneux, Magdalena (Magda) AntczakInfrastructure provision: Uwe WinterCoordinator: Melissa BurkeTraining materialsMaterials 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_Schedule (PDF): A breakdown of the topics and timings for the workshopMaterials shared elsewhere:This workshop follows the tutorial 'scRNAseq Analysis in R with Seurat'https://swbioinf.github.io/scRNAseqInR_Doco/index.htmlSlides used to introduce key topics are available via GitHubhttps://github.com/swbioinf/scRNAseqInR_Doco/tree/main/slidesThis 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, transcriptomics, single cell RNA-seq, Seurat, R statistical software
WORKSHOP: Translating workflows into Nextflow with Janis

This record includes training materials associated with the Australian BioCommons workshop ‘Translating workflows into Nextflow with Janis’. This workshop took place online on 19 June 2023.

Event description

Bioinformatics workflows are critical for reproducibly transferring methodologies...

Keywords: Bioinformatics, Workflows, Nextflow, CWL, Galaxy

WORKSHOP: Translating workflows into Nextflow with Janis https://dresa.org.au/materials/workshop-translating-workflows-into-nextflow-with-janis-36386c6d-f9a2-4b4d-afa9-062ce3b8ac5d This record includes training materials associated with the Australian BioCommons workshop ‘Translating workflows into Nextflow with Janis’. This workshop took place online on 19 June 2023. Event description Bioinformatics workflows are critical for reproducibly transferring methodologies between research groups and for scaling between computational infrastructures. Research groups currently invest a lot of time and effort in creating and updating workflows; the ability to translate from one workflow language into another can make them easier to share, and maintain with minimal effort. For example, research groups that would like to run an existing Galaxy workflow on HPC, or extend it for their use, might find translating the workflow to Nextflow more suitable for their ongoing use-cases.  Janis is a framework that provides an abstraction layer for describing workflows, and a tool that can translate workflows between existing languages such as CWL, WDL, Galaxy and Nextflow. Janis aims to translate as much as it can, leaving the user to validate the workflow and make small manual adjustments where direct translations are not possible. Originating from the Portable Pipelines Project between Melbourne Bioinformatics, the Peter MacCallum Cancer Centre, and the Walter and Eliza Hall Institute of Medical Research, this tool is now available for everyone to use. This workshop provides an introduction to Janis and how it can be used to translate Galaxy and CWL based tools and workflows into Nextflow. Using hands-on examples we’ll step you through the process and demonstrate how to optimise, troubleshoot and test the translated workflows. This workshop event and accompanying materials were developed by the Melbourne Bioinformatics and the Peter MacCallum Cancer Centre. The workshop was enabled through the Australian BioCommons - Bring Your Own Data Platforms project funded by the Australian Research Data Commons and NCRIS via Bioplatforms Australia.    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. Intro to Galaxy (PDF): Slides presented during the workshop Intro to CWL (PDF): Slides presented during the workshop Intro to the session & Janis (PDF): Slides presented during the workshop Janis_Schedule (PDF): Schedule for the workshop providing a breakdown of topics and timings Materials shared elsewhere: This workshop follows the accompanying training materials: https://www.melbournebioinformatics.org.au/tutorials/tutorials/janis_translate/janis_translate   A recording of the workshop is available on the Australian BioCommons YouTube channel: https://youtu.be/0IiY1GEx_BY Melissa Burke (melissa@biocommons.org.au) Bioinformatics, Workflows, Nextflow, CWL, Galaxy
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: 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
WORKSHOP: Working with genomics sequences and features in R with Bioconductor

This record includes training materials associated with the Australian BioCommons workshop ‘Working with genomics sequences and features in R with Bioconductor’. This workshop took place on 23 September 2021.

Workshop description

Explore the many useful functions that the Bioconductor...

Keywords: R software, Bioconductor, Bioinformatics, Analysis, Genomics, Sequence analysis

WORKSHOP: Working with genomics sequences and features in R with Bioconductor https://dresa.org.au/materials/workshop-working-with-genomics-sequences-and-features-in-r-with-bioconductor-8399bf0d-1e9e-48f3-a840-3f70f23254bb This record includes training materials associated with the Australian BioCommons workshop ‘Working with genomics sequences and features in R with Bioconductor’. This workshop took place on 23 September 2021. Workshop description Explore the many useful functions that the Bioconductor environment offers for working with genomic data and other biological sequences.  DNA and proteins are often represented as files containing strings of nucleic acids or amino acids. They are associated with text files that provide additional contextual information such as genome annotations. This workshop provides hands-on experience with tools, software and packages available in R via Bioconductor for manipulating, exploring and extracting information from biological sequences and annotation files. We will look at tools for working with some commonly used file formats including FASTA, GFF3, GTF, methods for identifying regions of interest, and easy methods for obtaining data packages such as genome assemblies.  This workshop is presented by the Australian BioCommons and Monash Bioinformatics Platform 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): schedule for the workshop providing a breakdown of topics and timings   Materials shared elsewhere: This workshop follows the tutorial ‘Working with DNA sequences and features in R with Bioconductor - version 2’ developed for Monash Bioinformatics Platform and Monash Data Fluency by Paul Harrison. https://monashdatafluency.github.io/r-bioc-2/ Melissa Burke (melissa@biocommons.org.au) R software, Bioconductor, Bioinformatics, Analysis, Genomics, Sequence analysis