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Authors: Harrison, Paul (orcid: 0000...  or Brandies, Parice (orcid: 00... 

WEBINAR: Getting started with command line bioinformatics

This record includes training materials associated with the Australian BioCommons webinar ‘Getting started with command line bioinformatics’. This webinar took place on 22 June 2021. 

Bioinformatics skills are in demand like never before and biologists are stepping up to the challenge of...

Keywords: Bioinformatics, Command line, Workflows, Bash, Computational biology

WEBINAR: Getting started with command line bioinformatics https://dresa.org.au/materials/webinar-getting-started-with-command-line-bioinformatics-248027d1-0773-485a-b511-831e2fd4cc64 This record includes training materials associated with the Australian BioCommons webinar ‘Getting started with command line bioinformatics’. This webinar took place on 22 June 2021.  Bioinformatics skills are in demand like never before and biologists are stepping up to the challenge of learning to analyse large and ever growing datasets. Learning how to use the command line can open up many options for data analysis but getting started can be a little daunting for those without a background in computer science. Parice Brandies and Carolyn Hogg have recently put together ten simple rules for getting started with command-line bioinformatics to help biologists begin their computational journeys. In this webinar Parice walks you through their hints and tips for getting started with the command line. She covers topics like learning tech speak, evaluating your data and workflows, assessing computational requirements, computing options, the basics of software installation, curating and testing scripts, a bit of bash and keeping good records. The webinar will be followed by a short Q&A session. The slides were created by Parice Brandies and are based on the publication ‘Ten simple rules for getting started with command-line bioinformatics’ (https://doi.org/10.1371/journal.pcbi.1008645). The slides are shared under a Creative Commons Attribution 4.0 International unless otherwise specified and were current at the time of the webinar. 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 command line bioinformatics - slides (PDF): Slides presented during the webinar Materials shared elsewhere: A recording of the webinar is available on the Australian BioCommons YouTube Channel https://youtu.be/p7pA4OLB2X4 Melissa Burke (melissa@biocommons.org.au) Hogg, Carolyn (type: Supervisor) Bioinformatics, Command line, Workflows, Bash, Computational biology
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
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: 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