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Authors: Barlow, Melanie (orcid: 000...  or Bouquin, Daina (orcid: 0000...  or Bourke, Caitlin (orcid: 000...  or Pelagos 

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
MetaSat. An open, collaboratively-developed metadata toolkit to support the future of space exploration.

MetaSat is an open metadata toolkit for describing small satellite (and even large satellite) missions in a uniform and shareable way. Optimised for small satellite missions, MetaSat fills an informatics gap. Although there have been a number of relevant metadata sets, there has been a...

Keywords: Small satellites, metadata, vocabularies, training material

MetaSat. An open, collaboratively-developed metadata toolkit to support the future of space exploration. https://dresa.org.au/materials/metasat-an-open-collaboratively-developed-metadata-toolkit-to-support-the-future-of-space-exploration-49af7d4d-f0d1-4f95-9fbe-afbd45170a6a MetaSat is an open metadata toolkit for describing small satellite (and even large satellite) missions in a uniform and shareable way. Optimised for small satellite missions, MetaSat fills an informatics gap. Although there have been a number of relevant metadata sets, there has been a longstanding need for a vocabulary to span these community standards. A vocabulary to annotate the data and information outputs of these satellite missions, to enable search across disparate data repositories, and provide support for application of analytical services to retrieved datasets. A common problem among small satellite teams is finding information about how other small satellites were put together, what parts worked well, what weren't compatible, what were the mission goals and outcomes. A lot of this information can be found, but it's not usually described in a consistent and searchable way across projects. MetaSat helps by building a uniform language of description which can be embedded into small satellite databases and tools to connect information across projects. Although a relatively new vocabulary initiative, MetaSat has secured early adoption by SatNOGS, a global network of ground stations that collects, manages & enables access to satellite observations. Also partnering with NASA's Small Satellite Reliability Initiative, and in discussion with NASA concerning implementation of the vocabulary in other areas of its information infrastructure. You can watch the full presentation on YouTube here: https://www.youtube.com/watch?v=uaCOzNL1eh4 contact@ardc.edu.au Small satellites, metadata, vocabularies, training material
ARDC FAIR Data 101 self-guided

FAIR Data 101 v3.0 is a self-guided course covering the FAIR Data principles

The FAIR Data 101 virtual course was designed and delivered by the ARDC Skilled Workforce Program twice in 2020 and has now been reworked as a self-guided course.

The course structure was based on 'FAIR Data in the...

Keywords: training material, FAIR data, video, webinar, activities, quiz, FAIR, research data management

ARDC FAIR Data 101 self-guided https://dresa.org.au/materials/ardc-fair-data-101-self-guided-2d794a84-f0ff-4e11-a39c-fa8ea481e097 FAIR Data 101 v3.0 is a self-guided course covering the FAIR Data principles The FAIR Data 101 virtual course was designed and delivered by the ARDC Skilled Workforce Program twice in 2020 and has now been reworked as a self-guided course. The course structure was based on 'FAIR Data in the Scholarly Communications Lifecycle', run by Natasha Simons at the FORCE11 Scholarly Communications Institute. These training materials are hosted on GitHub. contact@ardc.edu.au training material, FAIR data, video, webinar, activities, quiz, FAIR, research data management
OpenCL

Supercomputers make use of accelerators from a variety of different hardware vendors, using devices such as multi-core CPU’s, GPU’s and even FPGA’s. OpenCL is a way for your HPC application to make effective use of heterogeneous computing devices, and to avoid code refactoring for new HPC...

Keywords: supercomputing, Pawsey Supercomputing Centre, CPUs, GPUs, OpenCL, FPGAs

Resource type: activity

OpenCL https://dresa.org.au/materials/opencl Supercomputers make use of accelerators from a variety of different hardware vendors, using devices such as multi-core CPU’s, GPU’s and even FPGA’s. OpenCL is a way for your HPC application to make effective use of heterogeneous computing devices, and to avoid code refactoring for new HPC infrastructure. training@pawsey.org.au Toby Potter supercomputing, Pawsey Supercomputing Centre, CPUs, GPUs, OpenCL, FPGAs masters ecr researcher support
HIP Workshop

The Heterogeneous Interface for Portability (HIP) provides a programming framework for harnessing the compute capabilities of multicore processors, such as the MI250X GPU’s on Setonix.

In this course we focus on the essentials of developing HIP applications with a focus on...

Keywords: HIP, supercomputing, Programming, GPUs, MPI, debugging

Resource type: full-course

HIP Workshop https://dresa.org.au/materials/hip-workshop The Heterogeneous Interface for Portability (HIP) provides a programming framework for harnessing the compute capabilities of multicore processors, such as the MI250X GPU’s on Setonix. In this course we focus on the essentials of developing HIP applications with a focus on supercomputing. Agenda - Introduction to HIP and high level features - How to build and run applications on Setonix with HIP and MPI - A complete line-by-line walkthrough of a HIP-enabled application - Tools and techniques for debugging and measuring the performance of HIP applications training@pawsey.org.au HIP, supercomputing, Programming, GPUs, MPI, debugging
C/C++ Refresher

The C++ programming language and its C subset is used extensively in research environments. In particular it is the language utilised in the parallel programming frameworks CUDA, HIP, and OpenCL.

This workshop is designed to equip participants with “Survival C++”, an understanding of the basic...

Keywords: supercomputing, C/C++, Programming

Resource type: activity

C/C++ Refresher https://dresa.org.au/materials/c-c-refresher The C++ programming language and its C subset is used extensively in research environments. In particular it is the language utilised in the parallel programming frameworks CUDA, HIP, and OpenCL. This workshop is designed to equip participants with “Survival C++”, an understanding of the basic syntax, how information is encoded in binary format, and how to compile and debug C++ software. training@pawsey.org.au supercomputing, C/C++, Programming
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 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
MetaSat. An open, collaboratively-developed metadata toolkit to support the future of space exploration.

MetaSat is an open metadata toolkit for describing small satellite (and even large satellite) missions in a uniform and shareable way. Optimised for small satellite missions, MetaSat fills an informatics gap. Although there have been a number of relevant metadata sets, there has been a...

Keywords: Small satellites, metadata, vocabularies, training material

MetaSat. An open, collaboratively-developed metadata toolkit to support the future of space exploration. https://dresa.org.au/materials/metasat-an-open-collaboratively-developed-metadata-toolkit-to-support-the-future-of-space-exploration MetaSat is an open metadata toolkit for describing small satellite (and even large satellite) missions in a uniform and shareable way. Optimised for small satellite missions, MetaSat fills an informatics gap. Although there have been a number of relevant metadata sets, there has been a longstanding need for a vocabulary to span these community standards. A vocabulary to annotate the data and information outputs of these satellite missions, to enable search across disparate data repositories, and provide support for application of analytical services to retrieved datasets. A common problem among small satellite teams is finding information about how other small satellites were put together, what parts worked well, what weren't compatible, what were the mission goals and outcomes. A lot of this information can be found, but it's not usually described in a consistent and searchable way across projects. MetaSat helps by building a uniform language of description which can be embedded into small satellite databases and tools to connect information across projects. Although a relatively new vocabulary initiative, MetaSat has secured early adoption by SatNOGS, a global network of ground stations that collects, manages & enables access to satellite observations. Also partnering with NASA's Small Satellite Reliability Initiative, and in discussion with NASA concerning implementation of the vocabulary in other areas of its information infrastructure. You can watch the full presentation on YouTube here: https://www.youtube.com/watch?v=uaCOzNL1eh4 contact@ardc.edu.au Small satellites, metadata, vocabularies, training material
ARDC FAIR Data 101 self-guided

FAIR Data 101 v3.0 is a self-guided course covering the FAIR Data principles

The FAIR Data 101 virtual course was designed and delivered by the ARDC Skilled Workforce Program twice in 2020 and has now been reworked as a self-guided course.

The course structure was based on 'FAIR Data in the...

Keywords: training material, FAIR data, video, webinar, activities, quiz, FAIR, research data management

ARDC FAIR Data 101 self-guided https://dresa.org.au/materials/ardc-fair-data-101-self-guided-bba41a59-8479-4f4f-b9ee-337b9eb294bf FAIR Data 101 v3.0 is a self-guided course covering the FAIR Data principles The FAIR Data 101 virtual course was designed and delivered by the ARDC Skilled Workforce Program twice in 2020 and has now been reworked as a self-guided course. The course structure was based on 'FAIR Data in the Scholarly Communications Lifecycle', run by Natasha Simons at the FORCE11 Scholarly Communications Institute. These training materials are hosted on GitHub. contact@ardc.edu.au training material, FAIR data, video, webinar, activities, quiz, FAIR, research data management