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 21 August 2024.
Topic description
Galaxy is a web-based platform that lets you conduct accessible, reproducible, and transparent...
Keywords: Bioinformatics, Data analysis, Galaxy
WORKSHOP: Online data analysis for biologists
https://zenodo.org/records/13948826
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 21 August 2024.
Topic description
Galaxy is a web-based platform that lets you conduct accessible, reproducible, and transparent computational biological research. Widely used by researchers world wide, Galaxy gives you access to 1000’s of popular tools for analysis and processing of biological data. It is perfect for working with a wide range of big and small datasets including genome assembly, annotation, epigenetics, metabolomics, metagenomics, proteomics, statistics, transcriptomics, variant analysis and visualisation.
This workshop provides an introduction to using Galaxy and available tools. Using an example dataset, you’ll practice uploading data, choosing and running tools, and viewing the results. We’ll share our top tips for managing your experiments and speeding up your analysis with workflows.
Lead trainer: Dr Gareth Price, Galaxy Australia
Facilitator: Mike Thang, Galaxy Australia / QCIF
Infrastructure provision: Galaxy Australia
Host: Dr Melissa Burke, Australian BioCommons
Training 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_Online_data_analysis_for_biologists_210824 (PDF): Information about the event logistics including, description, event URL, learning objectives, prerequisites, technical requirements etc.
Schedule_Online_data_analysis_for_biologists_210824 (PDF): Schedule for the workshop providing a breakdown of topics and timings
Materials shared elsewhere:
This workshop is based on the Galaxy Training Network tutorial ‘Galaxy basics for everyone’: https://training.galaxyproject.org/training-material/topics/introduction/tutorials/galaxy-intro-101-everyone/tutorial.html
A recording of this workshop is available on the Australian BioCommons YouTube Channel: https://www.youtube.com/watch?v=PF39KjOvreM
Melissa Burke (melissa@biocommons.org.au)
Price, Gareth (orcid: 0000-0003-2439-8650)
Thang, Michael
Bioinformatics, Data analysis, Galaxy
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://amandamiotto.github.io/ReproducibleResearch/
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
Amanda Miotto
reproducibility, Reproducibility, reproducible workflows
phd
support
WEBINAR: Getting started with R
This record includes training materials associated with the Australian BioCommons webinar ‘Getting started with R’. This webinar took place on 16 August 2021.
Data analysis skills are now central to most biological experiments. While Excel can cover some of your data analysis needs, it is not...
Keywords: R statistical software, R studio, Tidyverse, Bioinformatics, Data analysis
WEBINAR: Getting started with R
https://zenodo.org/records/5214277
https://dresa.org.au/materials/webinar-getting-started-with-r-1c8f2b21-bc4b-4b42-9a5d-d6096a2afbe6
This record includes training materials associated with the Australian BioCommons webinar ‘Getting started with R’. This webinar took place on 16 August 2021.
Data analysis skills are now central to most biological experiments. While Excel can cover some of your data analysis needs, it is not always the best choice, particularly for large and complex datasets.
R is an open-source software and programming language that enables data exploration, statistical analysis visualisation and more. While it is the tool of choice for data analysis, getting started can be a little daunting for those without a background in statistics.
In this webinar Saskia Freytag, an R user with over a decade of experience and member of the Bioconductor Community Advisory Board, will walk you through their hints and tips for getting started with R and data analysis. She’ll cover topics like R Studio and why you need it, where to get help, basic data manipulation, visualisations and extending R with libraries. The webinar will be followed by a short Q&A session
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.
Getting started with R - slides (PDF): Slides used in the presentation
Materials shared elsewhere:
A recording of the webinar is available on the Australian BioCommons YouTube Channel:
https://youtu.be/JS7yZw7bnX8
Melissa Burke (melissa@biocommons.org.au)
Freytag, Saskia (orcid: 0000-0002-2185-7068)
R statistical software, R studio, Tidyverse, Bioinformatics, Data 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://zenodo.org/records/5091260
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
Australian Research Data Commons
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://globalarchivemanual.github.io/CheckEM/articles/manuals/CheckEM_user_guide.html
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
Brooke Gibbons
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://globalarchivemanual.github.io/CheckEM/articles/manuals/EventMeasure_annotation_guide.html
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
Brooke Gibbons
Tim Langlois
Claude Spencer
fish, stereo-video, annotation
Exploratory Data Analysis
This is the second of three modules in our exciting new machine learning workshop series by the Sydney Informatics Hub (SIH).
Module 1: https://youtu.be/dMwHFhKWRRI
Module 3:...
Keywords: Data analysis, training material
Exploratory Data Analysis
https://youtu.be/HVAFflj2PS0
https://dresa.org.au/materials/exploratory-data-analysis
This is the second of three modules in our exciting new machine learning workshop series by the Sydney Informatics Hub (SIH).
**Module 1**: [https://youtu.be/dMwHFhKWRRI](https://youtu.be/dMwHFhKWRRI)
**Module 3**: [https://github.com/Sydney-Informatics-Hub/Module3R](https://github.com/Sydney-Informatics-Hub/Module3R)
*The Sydney Informatics Hub is a Core Research Facility at The University of Sydney, enabling excellence in research* [https://sydney.edu.au/informatics-hub](https://sydney.edu.au/informatics-hub)
sih.training@sydney.edu.au
Zhang, Eden (orcid: 0000-0003-0294-3734)
Mori, Giorgia (orcid: 0000-0003-3469-5632)
Data analysis, training material
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://globalarchivemanual.github.io/CheckEM/index.html
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
Tim Langlois
Brooke Gibbons
Claude Spencer
stereo-video, fish, sharks, habitats
National Transfusion Dataset Secure eResearch Platform (SeRP)/SafeHaven Training
A short training video for NTD users on how to access and use the SeRP once data access is granted.
Keywords: research data, Data analysis, research data management
National Transfusion Dataset Secure eResearch Platform (SeRP)/SafeHaven Training
https://www.transfusiondataset.com/training-and-user-guides
https://dresa.org.au/materials/national-transfusion-dataset-secure-eresearch-platform-serp-safehaven-training
A short training video for NTD users on how to access and use the SeRP once data access is granted.
sphpm.ntd@monash.edu
research data, Data analysis, research data management
Introduction to Data Cleaning with OpenRefine
Learn basic data cleaning techniques in this self-paced online workshop using open data from data.qld.gov.au and open source tool OpenRefine openrefine.org. Learn techniques to prepare messy tabular data for comupational analysis. Of most relevance to HASS disciplines, working with textual data...
Keywords: data skills, Data analysis
Resource type: tutorial
Introduction to Data Cleaning with OpenRefine
https://griffithunilibrary.github.io/data-cleaning-intro/
https://dresa.org.au/materials/introduction-to-data-cleaning-with-openrefine
Learn basic data cleaning techniques in this self-paced online workshop using open data from data.qld.gov.au and open source tool OpenRefine openrefine.org. Learn techniques to prepare messy tabular data for comupational analysis. Of most relevance to HASS disciplines, working with textual data in a structured or semi-structured format.
s.stapleton@griffith.edu.au;
Sharron Stapleton
data skills, Data analysis
mbr
phd
ecr
researcher
support
professional
VOSON Lab Code Blog
The VOSON Lab Code Blog is a space to share methods, tips, examples and code. Blog posts provide techniques to construct and analyse networks from various API and other online data sources, using the VOSON open-source software and other R based packages.
Keywords: visualisation, Data analysis, data collections, R software, Social network analysis, social media data, Computational Social Science, quantitative, Text Analytics
Resource type: tutorial, other
VOSON Lab Code Blog
https://vosonlab.github.io/
https://dresa.org.au/materials/voson-lab-code-blog
The VOSON Lab Code Blog is a space to share methods, tips, examples and code. Blog posts provide techniques to construct and analyse networks from various API and other online data sources, using the VOSON open-source software and other R based packages.
robert.ackland@anu.edu.au
visualisation, Data analysis, data collections, R software, Social network analysis, social media data, Computational Social Science, quantitative, Text Analytics
researcher
support
phd
masters
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://guereslib.github.io/ten-reproducible-research-things/
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;
Amanda Miotto
Julie Toohey
Sharron Stapleton
Isaac Jennings
reproducibility, data management
masters
phd
ecr
researcher
support
Galaxy Training
Galaxy is a hosted web-accessible platform that lets you conduct accessible, reproducible, and transparent computational biological research. It is an international, community driven effort to make it easy for life scientists to analyse their data for free and without the need for programmatic...
Keywords: Galaxy Australia, Galaxy Project, Bioinformatics, Data analysis
Galaxy Training
https://training.galaxyproject.org/training-material/
https://dresa.org.au/materials/galaxy-training
Galaxy is a hosted web-accessible platform that lets you conduct accessible, reproducible, and transparent computational biological research. It is an international, community driven effort to make it easy for life scientists to analyse their data for free and without the need for programmatic skills.
This is a collection of tutorials developed and maintained by the worldwide Galaxy community that show you how to analyse a variety of biological data using Galaxy.
Melissa (melissa@biocommons.org.au)
Galaxy Australia, Galaxy Project, Bioinformatics, Data analysis