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Keywords: R software  or RNA-seq 

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://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://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/ Species Distribution Modelling, Ecology, R software, EcoCommons ugrad mbr phd
WORKSHOP: RNA-Seq: reads to differential genes and pathways

This record includes training materials associated with the Australian BioCommons workshop ‘RNA-Seq: reads to differential genes and pathways’. This workshop took place over two, 3.5 hour sessions on 27 and 28 September 2022.

Event description

RNA sequencing (RNA-seq) is a common method used to...

Keywords: Bioinformatics, Analysis, Transcriptomics, RNA-seq, Workflows, Nextflow, nf-co.re

WORKSHOP: RNA-Seq: reads to differential genes and pathways https://dresa.org.au/materials/workshop-rna-seq-reads-to-differential-genes-and-pathways-5a384156-d3de-4d5d-9797-e689bf6592f8 This record includes training materials associated with the Australian BioCommons workshop ‘RNA-Seq: reads to differential genes and pathways’. This workshop took place over two, 3.5 hour sessions on 27 and 28 September 2022. Event description RNA sequencing (RNA-seq) is a common method used to understand the differences in gene expression and molecular pathways between two or more groups. This workshop introduces the fundamental concepts of RNA sequencing experiments and will allow you to try out the analysis using data from a study of Williams-Beuren Syndrome, a rare disease.  In the first part of the workshop you will learn how to convert sequence reads into analysis ready count data. To do this we will use nf-core/rnaseq - a portable, scalable, reproducible and publicly available workflow on Pawsey Nimbus Cloud. In the second part of the workshop you will use the count data you created to identify differential genes and pathways using R/Rstudio. By the end of the workshop, you should be able to perform your own RNA-seq analysis for differential gene expression and pathway analysis! This workshop is presented by the Australian BioCommons and Sydney Informatics Hub 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. RNAseq reads to differential genes and pathways - Additional Resources (PDF): Additional resources compiled by the Sydney Informatics Hub rnaseq_DE_analysis_Day2.html: HTML version of code used on day 2 of the workshop rnaseq_DE_analysis_Day2.Rmd: R Markdown version of code used on day 2 of the workshop RNAseq reads to differential genes and pathways_Q_and_A (PDF): Archive of questions and their answers from the workshop Slack Channel. Materials shared elsewhere: This workshop follows the tutorial ‘RNA-seq: reads to differential gene expression workshop series’ developed by the Sydney Informatics Hub. https://sydney-informatics-hub.github.io/training.RNAseq.series-quarto/ Melissa Burke (melissa@biocommons.org.au) Bioinformatics, Analysis, Transcriptomics, RNA-seq, Workflows, Nextflow, nf-co.re
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://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) 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://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
WORKSHOP: RNASeq: reads to differential genes and pathways

This record includes training materials associated with the Australian BioCommons workshop 'RNASeq: reads to differential genes and pathways'. This workshop took place over two, 3 hour sessions on 11 and 12 October 2023.Event descriptionRNA sequencing (RNAseq) is a popular and powerful technique...

Keywords: bioinformatics, transcriptomics, RNA-seq, RNAseq

WORKSHOP: RNASeq: reads to differential genes and pathways https://dresa.org.au/materials/workshop-rnaseq-reads-to-differential-genes-and-pathways This record includes training materials associated with the Australian BioCommons workshop 'RNASeq: reads to differential genes and pathways'. This workshop took place over two, 3 hour sessions on 11 and 12 October 2023.Event descriptionRNA sequencing (RNAseq) is a popular and powerful technique used to understand the activity of genes. Using differential gene profiling methods, we can use RNAseq data to gain valuable insights into gene activity and identify variability in gene expression between samples to understand the molecular pathways underpinning many different traits.  In this hands-on workshop, you will learn RNAseq fundamentals as you process, analyse, and interpret the results from a real RNAseq experiment on the command-line. In session one, you will convert raw sequence reads to analysis-ready count data with the nf-core/rnaseq workflow. In session two, you'll work interactively in RStudio to identify differentially expressed genes,perform functional enrichment analysis, and visualise and interpret your results using popular and best practice R packages.  This workshop was delivered as a part of the Australian BioCommons Bring Your Own Data Platforms Project and will provide you with an opportunity to explore services and infrastructure built specifically for life scientists working at the command line. By the end of the workshop, you will be familiar with Pawsey's Nimbus cloud platform and be able to process your own RNAseq datasets and perform differential expression analysis on the command-line. Materials are shared under a Creative Commons Attribution 4.0 International agreement unless otherwise specified and were current at the time of the event.Lead trainers: Dr Georgina Samaha (Sydney Informatics Hub), Dr Nandan Deshpande (Sydney Informatics Hub)Facilitators: Ching-Yu Lu and Jessica Chung.Infrastructure provision: Audrey Stott (Pawsey Supercomputing Research Centre), Alex Ip (AARNet)Host: Melissa Burke, Australian BioCommons Training materialsFiles 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.Materials shared elsewhere:This workshop follows the tutorial 'Introduction to RNAseq workshop: reads to differential gene expression' developed by the Sydney Informatics Hub.https://sydney-informatics-hub.github.io/rnaseq-workshop-2023/Additional supporting materials are available via GitHubRstudio rnaseq container: https://github.com/Sydney-Informatics-Hub/Rstudio-rnaseq-contained/tree/mainRNAseq differential expression R notebook: https://github.com/Sydney-Informatics-Hub/rna-differential-expression-Rnotebook Melissa Burke (melissa@biocommons.org.au) bioinformatics, transcriptomics, RNA-seq, RNAseq
WEBINAR: Getting started with RNAseq: Transforming raw reads into biological insights

This record includes training materials associated with the Australian BioCommons webinar ‘Getting started with RNAseq: Transforming raw reads into biological insights’. This webinar took place on 6 September 2023.

Event description 

RNA sequencing (RNAseq) is a powerful technique for...

Keywords: Bioinformatics, Transcriptomics, RNA-seq, RNAseq, Gene expression

WEBINAR: Getting started with RNAseq: Transforming raw reads into biological insights https://dresa.org.au/materials/webinar-getting-started-with-rnaseq-transforming-raw-reads-into-biological-insights-1f7db385-e282-4332-a1c4-d1d73a769b1b This record includes training materials associated with the Australian BioCommons webinar ‘Getting started with RNAseq: Transforming raw reads into biological insights’. This webinar took place on 6 September 2023. Event description  RNA sequencing (RNAseq) is a powerful technique for investigating gene expression in biological samples. Processing and analysing RNAseq data involves multiple steps to align raw sequence reads to a reference genome, count the number of reads mapped to each gene, and perform statistical analyses to identify differentially expressed genes and functionally annotate them. RNAseq experiments have many different applications as we apply them to a variety of research questions and organisms. This diversity of applications can make it challenging to appreciate all the design considerations, processing requirements, and limitations of RNAseq experiments as they apply to you. In this webinar, you will gain an understanding of the key considerations for designing and performing your own successful experiments with bulk RNA. We’ll start at the lab bench with RNA extraction, quality control, and library preparation, then move to the sequencing machine where you will make essential decisions about sequencing platforms, optimal sequencing depth, and the importance of replicates. We’ll talk about bioinformatics workflows for RNAseq data processing and the computational requirements of transforming raw sequencing reads to analysis-ready count data. Finally, we’ll discuss how to apply differential expression and functional enrichment analyses to gain biological insights from differentially expressed genes. This webinar was developed by the Sydney Informatics Hub in collaboration with the Australian BioCommons. Training materials 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 RNAseq: A PDF copy of the slides presented during the webinar. Materials shared elsewhere: A recording of this webinar is available on the Australian BioCommons YouTube Channel: https://youtu.be/tITR3WR_jWI Melissa Burke (melissa@biocommons.org.au) Bioinformatics, Transcriptomics, RNA-seq, RNAseq, Gene expression
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://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) R software, Bioconductor, Bioinformatics, Analysis, Genomics, Sequence analysis
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://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