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Authors: Coddington, Paul (orcid: 00...  or Bourke, Caitlin (orcid: 000...  or Brooke Gibbons  or Paul Harrison 

WEBINAR: Where to go when your bioinformatics outgrows your compute

This record includes training materials associated with the Australian BioCommons webinar ‘Where to go when your bioinformatics outgrows your compute’. This webinar took place on 19 August 2021.

Bioinformatics analyses are often complex, requiring multiple software tools and specialised compute...

Keywords: Computational Biology, Bioinformatics, High performance computing, HPC, Galaxy Australia, Nectar Research Cloud, Pawsey Supercomputing Centre, NCI, NCMAS, Cloud computing

WEBINAR: Where to go when your bioinformatics outgrows your compute https://dresa.org.au/materials/webinar-where-to-go-when-your-bioinformatics-outgrows-your-compute-7a5a0ff8-8f4f-4fd0-af20-a88d515a6554 This record includes training materials associated with the Australian BioCommons webinar ‘Where to go when your bioinformatics outgrows your compute’. This webinar took place on 19 August 2021. Bioinformatics analyses are often complex, requiring multiple software tools and specialised compute resources. “I don’t know what compute resources I will need”, “My analysis won’t run and I don’t know why” and "Just getting it to work" are common pain points for researchers. In this webinar, you will learn how to understand the compute requirements for your bioinformatics workflows. You will also hear about ways of accessing compute that suits your needs as an Australian researcher, including Galaxy Australia, cloud and high-performance computing services offered by the Australian Research Data Commons, the National Compute Infrastructure (NCI) and Pawsey.  We also describe bioinformatics and computing support services available to Australian researchers.  This webinar was jointly organised with the Sydney Informatics Hub at the University of Sydney. 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. Where to go when your bioinformatics outgrows your compute - slides (PDF and PPTX): Slides presented during the webinar Australian research computing resources cheat sheet (PDF): A list of resources and useful links mentioned during the webinar. Materials shared elsewhere: A recording of the webinar is available on the Australian BioCommons YouTube Channel: https://youtu.be/hNTbngSc-W0 Melissa Burke (melissa@biocommons.org.au) Computational Biology, Bioinformatics, High performance computing, HPC, Galaxy Australia, Nectar Research Cloud, Pawsey Supercomputing Centre, NCI, NCMAS, Cloud computing
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
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
TransectMeasure Annotation Guide

Annotation guide: benthic composition and relief for horizontally facing imagery

Keywords: benthos, video, annotation

TransectMeasure Annotation Guide https://dresa.org.au/materials/transectmeasure-annotation-guide Annotation guide: benthic composition and relief for horizontally facing imagery tim.langlois@uwa.edu.au benthos, video, 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
Programming and tidy data analysis in R

A workshop to expand the skill-set of someone who has basic familiarity with R. Covers programming constructs such as functions and for-loops, and working with data frames using the dplyr and tidyr packages. Explains the importance of a "tidy" data representation, and goes through common steps...

Keywords: R, Tidyverse, Programming

Resource type: tutorial

Programming and tidy data analysis in R https://dresa.org.au/materials/programming-and-tidy-data-analysis-in-r A workshop to expand the skill-set of someone who has basic familiarity with R. Covers programming constructs such as functions and for-loops, and working with data frames using the dplyr and tidyr packages. Explains the importance of a "tidy" data representation, and goes through common steps needed to load data and convert it into a tidy form. To be taught as a hands on workshop, typically as two half-days. Developed by the Monash Bioinformatics Platform and taught as part of the Data Fluency program at Monash University. License is CC-BY-4. You are free to share and adapt the material so long as attribution is given. Paul Harrison paul.harrison@monash.edu R, Tidyverse, Programming phd ecr researcher
Linear models in R

A workshop on linear models in R. Learning to use linear models provides a foundation for modelling, estimation, prediction, and statistical testing in R. Many commonly used statistical tests can be performed using linear models. Ideas introduced using linear models are applicable to many of the...

Keywords: R statistics

Resource type: tutorial

Linear models in R https://dresa.org.au/materials/linear-models-in-r A workshop on linear models in R. Learning to use linear models provides a foundation for modelling, estimation, prediction, and statistical testing in R. Many commonly used statistical tests can be performed using linear models. Ideas introduced using linear models are applicable to many of the more complicated statistical and machine learning models available in R. To be taught as a hands on workshop, typically as two half-days. Developed by the Monash Bioinformatics Platform and taught as part of the Data Fluency program at Monash University. License is CC-BY-4. You are free to share and adapt the material so long as attribution is given. Paul Harrison paul.harrison@monash.edu R statistics phd ecr researcher
Introduction to R

An introduction to R, for people with zero coding experience.

To be taught as a hands on workshop, typically as two half-days.

Developed by the Monash Bioinformatics Platform and taught as part of the Data Fluency program at Monash University. License is CC-BY-4. You are free to share and...

Keywords: R

Resource type: tutorial

Introduction to R https://dresa.org.au/materials/introduction-to-r An introduction to R, for people with zero coding experience. To be taught as a hands on workshop, typically as two half-days. Developed by the Monash Bioinformatics Platform and taught as part of the Data Fluency program at Monash University. License is CC-BY-4. You are free to share and adapt the material so long as attribution is given. Paul Harrison paul.harrison@monash.edu R phd ecr researcher
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
WEBINAR: Where to go when your bioinformatics outgrows your compute

This record includes training materials associated with the Australian BioCommons webinar ‘Where to go when your bioinformatics outgrows your compute’. This webinar took place on 19 August 2021.

Bioinformatics analyses are often complex, requiring multiple software tools and specialised...

Keywords: Computational Biology, Bioinformatics, High performance computing, HPC, Galaxy Australia, Nectar Research Cloud, Pawsey Supercomputing Centre, NCI, NCMAS, Cloud computing

WEBINAR: Where to go when your bioinformatics outgrows your compute https://dresa.org.au/materials/webinar-where-to-go-when-your-bioinformatics-outgrows-your-compute This record includes training materials associated with the Australian BioCommons webinar ‘Where to go when your bioinformatics outgrows your compute’. This webinar took place on 19 August 2021. Bioinformatics analyses are often complex, requiring multiple software tools and specialised compute resources. “I don’t know what compute resources I will need”, “My analysis won’t run and I don’t know why” and "Just getting it to work" are common pain points for researchers. In this webinar, you will learn how to understand the compute requirements for your bioinformatics workflows. You will also hear about ways of accessing compute that suits your needs as an Australian researcher, including Galaxy Australia, cloud and high-performance computing services offered by the Australian Research Data Commons, the National Compute Infrastructure (NCI) and Pawsey.  We also describe bioinformatics and computing support services available to Australian researchers.  This webinar was jointly organised with the Sydney Informatics Hub at the University of Sydney. 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. - Where to go when your bioinformatics outgrows your compute - slides (PDF and PPTX): Slides presented during the webinar - Australian research computing resources cheat sheet (PDF): A list of resources and useful links mentioned during the webinar. **Materials shared elsewhere:** A recording of the webinar is available on the Australian BioCommons YouTube Channel: https://youtu.be/hNTbngSc-W0 Melissa Burke (melissa@biocommons.org.au) Computational Biology, Bioinformatics, High performance computing, HPC, Galaxy Australia, Nectar Research Cloud, Pawsey Supercomputing Centre, NCI, NCMAS, Cloud computing