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Keywords: R statistical software 

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EcoCommons Marine use case

This is a toy example with many of the steps required for a robust example not included. This does show how to pull together marine data from IMOS / AODN and summarise those environmental predictors and occurrence data by month. Then we show how you can pull together one model with predictors...

Keywords: Species Distribution Modelling, SDM temporal predictions, Ecology, Marine seasonal distributions, R statistical software

EcoCommons Marine use case https://dresa.org.au/materials/ecocommons-marine-use-case This is a toy example with many of the steps required for a robust example not included. This does show how to pull together marine data from IMOS / AODN and summarise those environmental predictors and occurrence data by month. Then we show how you can pull together one model with predictors that are both temporally (monthly) and spatially (Australian waters) explicit. Again, a robust example would need calibration and validation steps, but this example does show how SDMs can be developed across time. The data and code needed to run these examples is here: https://github.com/EcoCommons-Australia/educational_material/tree/main/Marine_use_case https://www.ecocommons.org.au/contact/ Species Distribution Modelling, SDM temporal predictions, Ecology, Marine seasonal distributions, R statistical software ugrad masters mbr phd ecr
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://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) R statistical software, R studio, Tidyverse, Bioinformatics, Data analysis
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://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) bioinformatics, transcriptomics, single cell RNA-seq, Seurat, R statistical software