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Keywords: fish  or reproducibility  or Analysis 

WORKSHOP: Fungal Genomics with Galaxy

This record includes training materials associated with the Bioplatforms Australia “Fungal Genomics with Galaxy Workshop”. This workshop took place over three days from 29-31 October 2024.
Event description
A three-day workshop organised by Bioplatforms Australia to introduce bioinformatics...

Keywords: Bioinformatics, Analysis, Fungi, Genome assembly, Genome annotation

WORKSHOP: Fungal Genomics with Galaxy https://dresa.org.au/materials/workshop-fungal-genomics-with-galaxy This record includes training materials associated with the Bioplatforms Australia “Fungal Genomics with Galaxy Workshop”. This workshop took place over three days from 29-31 October 2024. Event description A three-day workshop organised by Bioplatforms Australia to introduce bioinformatics theory and practice to researchers, citizen scientists, and industry involved in Bioplatforms fungi-themed National Initiatives: Australian Functional Fungi Initiative, and Plant Pathogen Omics Initiative. An in-person workshop, held over three days from ~9am-5pm.  The workshop included a series of interleaved presentations about fungal genomics theory and practical tutorials using the Galaxy Australia analysis platform, as well as discussion sessions and presentations from some of the attendees.  A breakdown of timings and topics is provided in the schedule. Registration was open to project representatives across the Australian Functional Fungi, and Plant Pathogen Omics Initiative.  Participation was free for registrants, and was supported by Bioplatforms National Initiatives.  Number of participants = 38 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:  Prof. Benjamin Schwessinger (Australian National University) Dr Alistair McTaggart (Psymbiotika Lab) Dr Gareth Price / Dr Anna Syme (Galaxy Australia Presenters: Dr Mareike Moeller (Australian National University) Rita Tam (Australian National University) Zhenyan Luo (Australian National University) Coordination: Dr Kelly Scarlett (BioPlatforms Australia) Dr Mabel Lum (BioPlatforms Australia) Dr Sophie Mazard (BioPlatforms Australia)    Files and materials included in this record: Event metadata (PDF): Information about the event including description, learning objectives, prerequisites, etc. Schedule of program inlcuding links to training materials and resources (PDF) Slide sets as PDFs (PDF) Table of links to Galaxy workflows and example histories (PDF) Copy of Galaxy workflows developed as examples for fungal data analysis (as .ga files)   Materials shared elsewhere: This workshop includes tutorials from the Galaxy Training Network which are linked in the schedule document.    Melissa Burke (melissa@biocommons.org.au) Bioinformatics, Analysis, Fungi, Genome assembly, Genome annotation
7 Steps towards Reproducible Research

This workshop aims to take you further down your reproducibility path, by providing concepts and tools you can use in your everyday workflows. It is discipline and experience agnostic, and no coding experience is needed.

We will also examine how Reproducible Research builds business continuity...

Keywords: reproducibility, Reproducibility, reproducible workflows

Resource type: full-course, tutorial

7 Steps towards Reproducible Research https://dresa.org.au/materials/7-steps-towards-reproducible-research This workshop aims to take you further down your reproducibility path, by providing concepts and tools you can use in your everyday workflows. It is discipline and experience agnostic, and no coding experience is needed. We will also examine how Reproducible Research builds business continuity into your research group, how the culture in your institute ecosystem can affect Reproducibility and how you can identify and address risks to your knowledge. The workshop can be used as self-paced or as an instructor Amanda Miotto - a.miotto@griffith.edu.au reproducibility, Reproducibility, reproducible workflows phd support
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
WORKSHOP: Introduction to Metabarcoding using QIIME2

This record includes training materials associated with the Australian BioCommons workshop ‘Introduction to Metabarcoding using QIIME2’. This workshop took place on 22 February 2022.

Event description

Metabarcoding has revolutionised the study of biodiversity science. By combining DNA taxonomy...

Keywords: Bioinformatics, Analysis, Workflows, Microbial ecology, Metabarcoding, Microbiome

WORKSHOP: Introduction to Metabarcoding using QIIME2 https://dresa.org.au/materials/workshop-introduction-to-metabarcoding-using-qiime2-d3a7ac82-63aa-47e6-9d8e-5126419f9982 This record includes training materials associated with the Australian BioCommons workshop ‘Introduction to Metabarcoding using QIIME2’. This workshop took place on 22 February 2022. Event description Metabarcoding has revolutionised the study of biodiversity science. By combining DNA taxonomy with high-throughput DNA sequencing, it offers the potential to observe a larger diversity in the taxa within a single sample, rapidly expanding the scope of microbial analysis and generating high-quality biodiversity data.  This workshop will introduce the topic of metabarcoding and how you can use Qiime2 to analyse 16S data and gain simultaneous identification of all taxa within a sample. Qiime2 is a popular tool used to perform powerful microbiome analysis that can transform your raw data into publication quality visuals and statistics. In this workshop, using example 16S data from the shallow-water marine anemone E. diaphana, you will learn how to use this pipeline to run essential steps in microbial analysis including generating taxonomic assignments and phylogenic trees, and performing both alpha- and beta- diversity analysis.  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 ‘Introduction to metabarcoding with QIIME2’ which has been made publicly available by Melbourne Bioinformatics. https://www.melbournebioinformatics.org.au/tutorials/tutorials/qiime2/qiime2/ Melissa Burke (melissa@biocommons.org.au) Bioinformatics, Analysis, Workflows, Microbial ecology, Metabarcoding, Microbiome
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
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
How can software containers help your research?

This video explains software containers to a research audience. It is an introduction to why containers are beneficial for research. These benefits are standardisation, portability, reliability and reproducibility. 

Software Containers in research are a solution that addresses the challenge of a...

Keywords: containers, software, research, reproducibility, RSE, standard, agility, portable, reusable, code, application, reproducible, standardisation, package, system, cloud, server, version, reliability, program, collaborator, ARDC_AU, training material

How can software containers help your research? https://dresa.org.au/materials/how-can-software-containers-help-your-research-ca0f9d41-d83b-463b-a548-402c6c642fbf This video explains software containers to a research audience. It is an introduction to why containers are beneficial for research. These benefits are standardisation, portability, reliability and reproducibility.  Software Containers in research are a solution that addresses the challenge of a replicable computational environment and supports reproducibility of research results. Understanding the concept of software containers enables researchers to better communicate their research needs with their colleagues and other researchers using and developing containers. Watch the video here: https://www.youtube.com/watch?v=HelrQnm3v4g If you want to share this video please use this: Australian Research Data Commons, 2021. How can software containers help your research?. [video] Available at: https://www.youtube.com/watch?v=HelrQnm3v4g DOI: http://doi.org/10.5281/zenodo.5091260 [Accessed dd Month YYYY]. contact@ardc.edu.au Martinez, Paula Andrea (type: ProjectLeader) Sam Muirhead (type: Producer) The ARDC Communications Team (type: Editor) The ARDC Skills and Workforce Development Team (type: ProjectMember) The ARDC eResearch Infrastructure & Services (type: ProjectMember) The ARDC Nectar Cloud Services team (type: ProjectMember) containers, software, research, reproducibility, RSE, standard, agility, portable, reusable, code, application, reproducible, standardisation, package, system, cloud, server, version, reliability, program, collaborator, ARDC_AU, training material
CheckEM User Guide

CheckEM is an open-source web based application which provides quality control assessments on metadata and image annotations of fish stereo-imagery. It is available at marine-ecology.shinyapps.io/CheckEM. The application can assess a range of sampling methods and annotation data formats for...

Keywords: stereo-video, fish, annotation

CheckEM User Guide https://dresa.org.au/materials/checkem-user-guide CheckEM is an open-source web based application which provides quality control assessments on metadata and image annotations of fish stereo-imagery. It is available at marine-ecology.shinyapps.io/CheckEM. The application can assess a range of sampling methods and annotation data formats for common inaccuracies made whilst annotating stereo imagery. CheckEM creates interactive plots and tables in a graphical interface, and provides summarised data and a report of potential errors to download. brooke.gibbons@uwa.edu.au stereo-video, fish, annotation
EventMeasure Annotation Guide

EventMeasure annotation guide for baited remote underwater stereo video systems (stereo-BRUVs) for count and length

Keywords: fish, stereo-video, annotation

EventMeasure Annotation Guide https://dresa.org.au/materials/eventmeasure-annotation-guide EventMeasure annotation guide for baited remote underwater stereo video systems (stereo-BRUVs) for count and length tim.langlois@uwa.edu.au fish, stereo-video, annotation
Stereo-video workflows for fish and benthic ecologists

Stereo imagery is widely used by research institutions and management bodies around the world as a cost-effective and non-destructive method to research and monitor fish and habitats (Whitmarsh, Fairweather and Huveneers, 2017). Stereo-video can provide accurate and precise size and range...

Keywords: stereo-video, fish, sharks, habitats

Resource type: tutorial

Stereo-video workflows for fish and benthic ecologists https://dresa.org.au/materials/stereo-video-workflows-for-fish-and-benthic-ecologists Stereo imagery is widely used by research institutions and management bodies around the world as a cost-effective and non-destructive method to research and monitor fish and habitats (Whitmarsh, Fairweather and Huveneers, 2017). Stereo-video can provide accurate and precise size and range measurements and can be used to study spatial and temporal patterns in fish assemblages (McLean et al., 2016), habitat composition and complexity (Collins et al., 2017), behaviour (Goetze et al., 2017), responses to anthropogenic pressures (Bosch et al., 2022) and the recovery and growth of benthic fauna (Langlois et al. 2020). It is important that users of stereo-video collect, annotate, quality control and store their data in a consistent manner, to ensure data produced is of the highest quality possible and to enable large scale collaborations. Here we collate existing best practices and propose new tools to equip ecologists to ensure that all aspects of the stereo-video workflow are performed in a consistent way. tim.langlois@uwa.edu.au stereo-video, fish, sharks, habitats
10 Reproducible Research things - Building Business Continuity

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

Keywords: reproducibility, data management

Resource type: tutorial, video

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