Tutorials to learn how to use STAN
Stan tutorials offer links to exceptional tutorial papers, videos and statistics to learn Bayesian statistical methods and applied statistics.
Keywords: Statistics, applied statistics, Bayesian statistics, R software, Python, MATLAB
Tutorials to learn how to use STAN
https://mc-stan.org/users/documentation/tutorials.html
https://dresa.org.au/materials/tutorials-to-learn-how-to-use-stan
Stan tutorials offer links to exceptional tutorial papers, videos and statistics to learn Bayesian statistical methods and applied statistics.
https://mc-stan.org/about/team/
Statistics, applied statistics, Bayesian statistics, R software, Python, MATLAB
Species Distribution Modelling in R
This set of scripts and videos provide an introduction to running SDMs in R and include some steps to consider that go beyond what's available in the EcoCommons SDM point-and-click tools.
Five videos include: 1. An introduction to SDM in R, 2. occurrence data, 3. environmental data, 4. fitting...
Keywords: Species Distribution Modelling, Ecology, R software, EcoCommons
Species Distribution Modelling in R
https://www.ecocommons.org.au/educational-material4-mastering-species-distribution-modelling-in-r/
https://dresa.org.au/materials/species-distribution-modelling-in-r
This set of scripts and videos provide an introduction to running SDMs in R and include some steps to consider that go beyond what's available in the EcoCommons SDM point-and-click tools.
Five videos include: 1. An introduction to SDM in R, 2. occurrence data, 3. environmental data, 4. fitting your model, 5. model evaluation
Scripts and files are available here:
https://github.com/EcoCommons-Australia/educational_material/tree/main/SDMs_in_R/Scripts
Scripts for all four modules are here: https://www.ecocommons.org.au/wp-content/uploads/EcoCommons_steps_1_to_4.html
https://www.ecocommons.org.au/contact/
https://orcid.org/0000-0002-1359-5133
Species Distribution Modelling, Ecology, R software, EcoCommons
ugrad
mbr
phd
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://zenodo.org/records/7072910
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)
Williams, Sarah
Mehdi, Ahmed (orcid: 0000-0002-9300-2341)
Matigan, Nick
Barugahare, Adele (orcid: 0000-0002-8976-0094)
Harrison, Paul (orcid: 0000-0002-3980-268X)
Morgan, Steven (orcid: 0000-0001-6038-6126)
Whitfield, Holly (orcid: 0000-0002-7282-387X)
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://zenodo.org/records/6766951
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)
Freytag, Saskia (orcid: 0000-0002-2185-7068)
Barugahare, Adele (orcid: 0000-0002-8976-0094)
Doyle, Maria
Ansell, Brendan (orcid: 0000-0003-0297-897X)
Varshney, Akriti
Bourke, Caitlin (orcid: 0000-0002-4466-6563)
Conradsen, Cara (orcid: 0000-0001-9797-3412)
Jung, Chol-Hee (orcid: 0000-0002-2992-3162)
Sandoval, Claudia
Chandrananda, Dineika (orcid: 0000-0002-8834-9500)
Zhang, Eden (orcid: 0000-0003-0294-3734)
Rosello, Fernando (orcid: 0000-0003-3885-8777)
Iacono, Giulia (orcid: 0000-0002-1527-0754)
Tarasova, Ilariya (orcid: 0000-0002-0895-9385)
Chung, Jessica (orcid: 0000-0002-0627-0955)
Moffet, Joel
Gustafsson, Johan (orcid: 0000-0002-2977-5032)
Ding, Ke
Feher, Kristen
Perlaza-Jimenez, Laura (orcid: 0000-0002-8511-1134)
Crowe, Mark (orcid: 0000-0002-9514-2487)
Ma, Mengyao
Kandhari, Nitika (orcid: 0000-0002-0261-727X)
Williams, Sarah
Nelson, Tiffanie (orcid: 0000-0002-5341-312X)
Schreiber, Veronika (orcid: 0000-0001-6088-7828)
Pinzon Perez, William
Bioinformatics, Analysis, Statistics, R software, RStudio, Data visualisation
WEBINAR: Establishing Gen3 to enable better human genome data sharing in Australia
This record includes training materials associated with the Australian BioCommons webinar ‘Establishing Gen3 to enable better human genome data sharing in Australia’. This webinar took place on 16 February 2022.
Event description
Australian human genome initiatives are generating vast amounts...
Keywords: Bioinformatics, Genomics, Human genomics, Digital infrastructure, Gen3, Data sharing, Data management
WEBINAR: Establishing Gen3 to enable better human genome data sharing in Australia
https://zenodo.org/records/6233075
https://dresa.org.au/materials/webinar-establishing-gen3-to-enable-better-human-genome-data-sharing-in-australia-d8caf8c8-d447-4218-be01-95dfd0377f3e
This record includes training materials associated with the Australian BioCommons webinar ‘Establishing Gen3 to enable better human genome data sharing in Australia’. This webinar took place on 16 February 2022.
Event description
Australian human genome initiatives are generating vast amounts of human genome data. There is a desire and need to share data with collaborators but researchers face significant infrastructural, technical and administrative barriers in achieving this. To efficiently share and distribute their genome data they need scalable services and infrastructure that: is easily administered; allows for the efficient data management; enables sharing and interoperability; and is aligned with global standards for human genome data sharing.
Australian BioCommons has brought together a team from Zero Childhood Cancer (Zero), the University of Melbourne Centre for Cancer Research (UMCCR) and Australian Access Federation to explore the use of Gen3 technology. Establishing systems for easier management and sharing of their human genome data holdings is no simple task, and the group wants to ensure that other Australian providers and Institutions can benefit from their experience and easily deploy the same solution in the future.
Gen3 is an open source software suite that makes use of private and public clouds to tackle the challenges of data management, interoperability, data sharing and analysis. It has been used in several very large NIH-funded projects that collectively house and describe data derived from hundreds of thousands of human samples (e.g. NCI Genomic Data Commons, BioData Catalyst, BloodPAC, BrainCommons, Kids First Data Commons).
In this webinar you’ll hear from UMCCR and Zero about their experiences and progress towards establishing Gen3 instances to better enable better human genome data sharing in Australia. They will outline the challenges and opportunities that have arisen through this Australian BioCommons project and demonstrate the capabilities of Gen3 for human genome research.
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.
Gen3_Webinar_Slides (PDF): Slides presented during the webinar
Materials shared elsewhere:
A recording of this webinar is available on the Australian BioCommons YouTube Channel:
https://youtu.be/1F6B03Byigk
Melissa Burke (melissa@biocommons.org.au)
Pope, Bernie (orcid: 0000-0002-4840-1095)
Hofmann, Oliver (orcid: 0000-0002-7738-1513)
Wong-Erasmus, Marie (orcid: 0000-0003-0066-6606)
Taouk, Kamile (orcid: 0000-0001-8389-510X)
Bioinformatics, Genomics, Human genomics, Digital infrastructure, Gen3, Data sharing, Data management
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://zenodo.org/records/5781776
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)
Harrison, Paul (orcid: 0000-0002-3980-268X)
Deshpande, Nandan (orcid: 0000-0002-0324-8728)
Barugahare, Adele (orcid: 0000-0002-8976-0094)
Perry, Andrew (orcid: 0000-0001-9256-6068)
Wong, Nick (orcid: 0000-0003-4393-7541)
Reames, Benjamin
R software, Bioconductor, Bioinformatics, Analysis, Genomics, Sequence analysis
Sharing Approaches to Implementing the Data Guide at Medical Research Institutes (MRIs) Workshop
Co-authored by the Australian Research Council (ARC), the National Health and Medical Research Council (NHMRC) and Universities Australia (UA), the Management of Data and Information in Research Guide contains guidance for institutions and researchers on how they can implement the new Code as it...
Keywords: Data management, ARC, NHMRC, research data, Research Data Guide, Funding, training material
Sharing Approaches to Implementing the Data Guide at Medical Research Institutes (MRIs) Workshop
https://zenodo.org/records/4291067
https://dresa.org.au/materials/sharing-approaches-to-implementing-the-data-guide-at-medical-research-institutes-mris-workshop-66fd5cb3-e161-44e2-aa96-514f195ab54d
Co-authored by the Australian Research Council (ARC), the National Health and Medical Research Council (NHMRC) and Universities Australia (UA), the Management of Data and Information in Research Guide contains guidance for institutions and researchers on how they can implement the new Code as it relates to the subject of research data.
This workshop included presentations and breakout discussions considering MRI approaches to data management practices in light of the Code and Guide.
This workshop was delivered as part of the Management of Data and Information in Research Guide Event. The aims of the Event were to enable research offices within universities and Medical Research Institutes (MRIs) to have a clear and consistent understanding of the data management requirements and responsibilities as outlined in the Code and the Data Guide.
contact@ardc.edu.au
Kang, Kristan
Radhouane, Aniba
McLaren, Tara
Data management, ARC, NHMRC, research data, Research Data Guide, Funding, training material
Data Management at CLEX
In this presentation, Paula Petrelli outlines the opportunities and challenges of data management for climate science, and how she implemented DMPOnline to facilitate better workflows for publishing research data. This talk was presented to the Australasian Data Management Plans Interest Group on...
Keywords: Data management, DMP, Data management planning, DMP Online, Climate research, Data publishing, DOIs, training material
Data Management at CLEX
https://zenodo.org/records/5403344
https://dresa.org.au/materials/data-management-at-clex-4351940a-b868-4c6d-879b-2cae212ff172
In this presentation, Paula Petrelli outlines the opportunities and challenges of data management for climate science, and how she implemented DMPOnline to facilitate better workflows for publishing research data. This talk was presented to the Australasian Data Management Plans Interest Group on 19 August 2021. The group is hosted by Liz Stokes and meets every two months to discuss data management planning infrastructure.
contact@ardc.edu.au
Petrelli, Paula (orcid: 0000-0002-0164-5105)
Stokes, Liz (type: Other)
Data management, DMP, Data management planning, DMP Online, Climate research, Data publishing, DOIs, training material
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
Heurist Tutorials
A set of video tutorials with accompanying walkthroughs for building your first Heurist database and website. The first three tutorials show you how to get started in Heurist. The five subsequent tutorials introduce you to the five main menus in the Heurist interface.
Keywords: Heurist, Data management, Data visualisation, Digital Humanities, Databasing, website
Resource type: tutorial
Heurist Tutorials
https://heuristnetwork.org/tutorials
https://dresa.org.au/materials/heurist-tutorials
A set of video tutorials with accompanying walkthroughs for building your first Heurist database and website. The first three tutorials show you how to get started in Heurist. The five subsequent tutorials introduce you to the five main menus in the Heurist interface.
michael.falk@sydney.edu.au
Falk, Michael
Johnson, Ian
Osmakov, Artem
Heurist, Data management, Data visualisation, Digital Humanities, Databasing, website
mbr
phd
ecr
researcher
support