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Authors: Dow, Ellen (orcid: 0000-000...  or Conradsen, Cara (orcid: 000...  or Williams, Sarah 

WEBINAR: KBase - A knowledge base for systems biology

This record includes training materials associated with the Australian BioCommons webinar ‘KBase - A knowledge base for systems biology’. This webinar took place on 22 September 2021.

Event description 

Developed for bench biologists and bioinformaticians, The Department of Energy Systems...

Keywords: Systems Biology, FAIR Research, Open Source Software, Metagenomics, Microbiology

WEBINAR: KBase - A knowledge base for systems biology https://dresa.org.au/materials/webinar-kbase-a-knowledge-base-for-systems-biology-653d9753-989d-4194-9230-6e2d90652955 This record includes training materials associated with the Australian BioCommons webinar ‘KBase - A knowledge base for systems biology’. This webinar took place on 22 September 2021. Event description  Developed for bench biologists and bioinformaticians, The Department of Energy Systems Biology Knowledgebase (KBase) is a free, open source, software and data science platform designed to meet the grand challenge of systems biology: predicting and designing biological function. This webinar will provide an overview of the KBase mission and user community, as well as a tour of the online platform and basic functionality. You’ll learn how KBase can support your research: Upload data, run analysis tools (Apps), share your analysis with collaborators, and publish your data and reproducible workflows. We’ll highlight a brand new feature that enables users to link environment and measurement data to sequencing data. You’ll also find out how KBase supports findable, accessible, interoperable, and reusable (FAIR) research by providing open, reproducible, shareable bioinformatics workflows. 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. Q&A for Australian BioCommons KBase Webinar [PDF]: Document containing answers to questions asked during the webinar and links to additional resources Introduction to KBase: Australian BioCommons Webinar [PDF]: Slides presented during the webinar Materials shared elsewhere: A recording of the webinar is available on the Australian BioCommons YouTube Channel: https://youtu.be/tJ94i9gOJfU The slides are also available as Google slides:  https://tinyurl.com/KBase-webinar-slides Melissa Burke (melissa@biocommons.org.au) Systems Biology, FAIR Research, Open Source Software, Metagenomics, Microbiology
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: 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
WORKSHOP: Refining genome annotations with Apollo

This record includes training materials associated with the Australian BioCommons  workshop ‘Refining genome annotations with Apollo’. This workshop took place on 17 November 2021.

Workshop description 

Genome annotation is crucial to defining the function of genomic sequences. This process...

Keywords: Apollo Software, Bioinformatics, Analysis, Workflows, Genomics, Genome annotation

WORKSHOP: Refining genome annotations with Apollo https://dresa.org.au/materials/workshop-refining-genome-annotations-with-apollo-d8f95fb3-7dc4-40e0-87d5-e7a4b2ceaf16 This record includes training materials associated with the Australian BioCommons  workshop ‘Refining genome annotations with Apollo’. This workshop took place on 17 November 2021. Workshop description  Genome annotation is crucial to defining the function of genomic sequences. This process typically involves a round of automated annotation followed by manual curation. Manual curation allows you to visualise your annotations so you can understand what your organism looks like, and then to manually refine these annotations along with any additional data you might have. This process is typically performed collaboratively as part of a team effort. Apollo is a popular tool for facilitating real-time collaborative, manual curation and genome annotation editing. In this workshop we will learn how to use Apollo to refine genome annotations using example data from an E. coli strain. We’ll focus on the basics like getting data into Apollo, viewing evidence tracks, editing and adding structural and functional annotation, visualising the results and collaborating on genome annotations. This workshop made use of a training instance of  the new Australian Apollo Service. This service enables Australian-based research groups and consortia to access Apollo and host genome assembly and supporting evidence files for free. This service has been made possible by The Australian BioCommons and partners at QCIF and Pawsey. To learn more about the Australian Apollo Service you can watch the Australian Apollo Launch Webinar. This workshop was presented by the Australian BioCommons and Queensland Cyber Infrastructure Foundation (QCIF) . The Australian Apollo Service is operated by QCIF and underpinned by computational resources provided by the Pawsey Supercomputing Research Centre and receives NCRIS funding through Bioplatforms Australia and the Australian Research Data Commons as well as Queensland Government RICF funding. The training materials presented in this workshop were developed by Anthony Bretaudeau, Helena Rasche, Nathan Dunn, Mateo Boudet for the Galaxy Training Network. Helena and Anthony are part of the Gallantries project which is supported by Erasmus Programme of the European Union. 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 2021 Apollo Training Intro (PPTX and PDF): Slides used to introduce the Australian Apollo Service Augustus.gff3 (gff3): E.coli derived data file used in the tutorial. Data was obtained from the Galaxy Training Network and pre-processed using Galaxy Australia. Blastp_vs_swissprot.gff3: E.coli derived data file used in the tutorial. Data was obtained from the Galaxy Training Network and pre-processed using Galaxy Australia. Materials shared elsewhere: This workshop is based on the tutorial ‘Refining genome annotations with Apollo’ which was developed for the Galaxy Training Network. Anthony Bretaudeau, Helena Rasche, Nathan Dunn, Mateo Boudet, Erasmus Programme, 2021 Refining Genome Annotations with Apollo (Galaxy Training Materials). https://training.galaxyproject.org/training-material/topics/genome-annotation/tutorials/apollo/tutorial.html Online; accessed Wed Dec 15 2021 See also: Batut et al., 2018 Community-Driven Data Analysis Training for Biology Cell Systems 10.1016/j.cels.2018.05.012 Melissa Burke (melissa@biocommons.org.au) Apollo Software, Bioinformatics, Analysis, Workflows, Genomics, Genome annotation