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://zenodo.org/records/10042919
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)
Williams, Sarah
Barugahare, Adele (orcid: 0000-0002-8976-0094)
Harrison, Paul (orcid: 0000-0002-3980-268X)
Perlaza Jimenez, Laura (orcid: 0000-0002-8511-1134)
Matigan, Nicholas
Murigneux, Valentine (orcid: 0000-0002-1235-9462)
Antczak, Magdalena (orcid: 0000-0003-1503-1849)
Winter, Uwe
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://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: 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
Accelerating skills development in Data science and AI at scale
At the Monash Data Science and AI platform, we believe that upskilling our research community and building a workforce with data science skills are key to accelerating the application of data science in research. To achieve this, we create and leverage new and existing training capabilities...
Keywords: AI, machine learning, eresearch skills, training, train the trainer, volunteer instructors, training partnerships, training material
Accelerating skills development in Data science and AI at scale
https://zenodo.org/records/4287746
https://dresa.org.au/materials/accelerating-skills-development-in-data-science-and-ai-at-scale-2d8a65fa-f96e-44ad-a026-cfae3f38d128
At the Monash Data Science and AI platform, we believe that upskilling our research community and building a workforce with data science skills are key to accelerating the application of data science in research. To achieve this, we create and leverage new and existing training capabilities within and outside Monash University. In this talk, we will discuss the principles and purpose of establishing collaborative models to accelerate skills development at scale. We will talk about our approach to identifying gaps in the existing skills and training available in data science, key areas of interest as identified by the research community and various sources of training available in the marketplace. We will provide insights into the collaborations we currently have and intend to develop in the future within the university and also nationally.
The talk will also cover our approach as outlined below
• Combined survey of gaps in skills and trainings for Data science and AI
• Provide seats to partners
• Share associate instructors/helpers/volunteers
• Develop combined training materials
• Publish a repository of open source trainings
• Train the trainer activities
• Establish a network of volunteers to deliver trainings at their local regions
Industry plays a significant role in making some invaluable training available to the research community either through self learning platforms like AWS Machine Learning University or Instructor led courses like NVIDIA Deep Learning Institute. We will discuss how we leverage our partnerships with Industry to bring these trainings to our research community.
Finally, we will discuss how we map our training to the ARDC skills roadmap and how the ARDC platforms project “Environments to accelerate Machine Learning based Discovery” has enabled collaboration between Monash University and University of Queensland to develop and deliver training together.
contact@ardc.edu.au
Tang, Titus
AI, machine learning, eresearch skills, training, train the trainer, volunteer instructors, training partnerships, training material
Monash University - University of Queensland training partnership in Data science and AI
We describe the peer network exchange for training that has been recently created via an ARDC funded partnership between Monash University and Universities of Queensland under the umbrella of the Queensland Cyber Infrastructure Foundation (QCIF). As part of a training program in machine learning,...
Keywords: data skills, training partnerships, data science, AI, training material
Monash University - University of Queensland training partnership in Data science and AI
https://zenodo.org/records/4287864
https://dresa.org.au/materials/monash-university-university-of-queensland-training-partnership-in-data-science-and-ai-8082bf73-d20f-4214-ad8c-95123e25a36c
We describe the peer network exchange for training that has been recently created via an ARDC funded partnership between Monash University and Universities of Queensland under the umbrella of the Queensland Cyber Infrastructure Foundation (QCIF). As part of a training program in machine learning, visualisation, and computing tools, we have established a series of over 20 workshops over the year where either Monash or QCIF hosts the event for some 20-40 of their researchers and students, while some 5 places are offered to participants from the other institution. In the longer term we aim to share material developed at one institution and have trainers present it at the other. In this talk we will describe the many benefits we have found to this approach including access to a wider range of expertise in several rapidly developing fields, upskilling of trainers, faster identification of emerging training needs, and peer learning for trainers.
contact@ardc.edu.au
Tang, Titus
data skills, training partnerships, data science, AI, training material
National skills ecosystem - call to action
In this Community Action session working groups will be formed based on the challenges/opportunities that were prioritised in Community Action session #4.
Skilled trainers / facilitators
National training registry
National training event calendar
Jointly developed training
Research...
Keywords: national skills initiatives, data skills, training, skills community, training material
National skills ecosystem - call to action
https://zenodo.org/records/4289335
https://dresa.org.au/materials/national-skills-ecosystem-call-to-action-ffd9b4ed-b557-496b-ac35-72467c03c71b
In this Community Action session working groups will be formed based on the challenges/opportunities that were prioritised in Community Action session #4.
- Skilled trainers / facilitators
- National training registry
- National training event calendar
- Jointly developed training
- Research support professionals: career/progression
contact@ardc.edu.au
Padmanabhan, Komathy
Backhaus, Ann
Papaioannou, Anastasios (orcid: 0000-0002-8959-4559)
Tang, Titus
Crowe, Mark (orcid: 0000-0002-9514-2487)
Vanichkina, Darya (orcid: 0000-0002-0406-164X)
Unsworth, Kathryn (orcid: 0000-0002-5407-9987)
Stokes, Liz (orcid: 0000-0002-2973-5647)
Liffers, Matthias (orcid: 0000-0002-3639-2080)
national skills initiatives, data skills, training, skills community, training material