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Authors: Harrison, Paul (orcid: 0000...  or Willet, Cali (orcid: 0000-0... 

WORKSHOP: Making sense of gene and protein lists with functional enrichment analysis

This record includes training materials associated with the Australian BioCommons workshop ‘Making sense of gene and protein lists with functional enrichment analysis’. This workshop took place over two, 3 hour sessions on 20, 21 November 2024.
Event description
Omics experiments often generate...

Keywords: Bioinformatics http://edamontology.org/topic_0091, Analysis http://edamontology.org/operation_2945, Enrichment analysis http://edamontology.org/operation_3501

WORKSHOP: Making sense of gene and protein lists with functional enrichment analysis https://dresa.org.au/materials/workshop-making-sense-of-gene-and-protein-lists-with-functional-enrichment-analysis This record includes training materials associated with the Australian BioCommons workshop ‘Making sense of gene and protein lists with functional enrichment analysis’. This workshop took place over two, 3 hour sessions on 20, 21 November 2024. Event description Omics experiments often generate long lists of genes or proteins. Functional enrichment analysis identifies biological trends in the data by assessing these lists against gene ontology and pathway information. This can help interpret the experimental results in the context of larger biological systems. This workshop continues from our introductory webinar and provides a practical introduction to functional enrichment analysis. Using example data you will get hands-on with some of the most commonly used databases and tools for over representation (ORA) and gene set enrichment analysis (GSEA) and for identifying enriched biological functions in a list of genes or proteins. We’ll focus on tools available online and in R. 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 Hossein Valipour Kahrood, Bioinformatician, Monash Genomics and Bioinformatics Platform Dr Cali Willet, Senior Research Bioinformatician, Sydney Informatics Hub, University of Sydney Facilitators: Georgina Samaha, Australian BioCommons Laura Perlaza-Jimenez, Monash Genomics and Bioinformatics Platform Infrastructure provision: Uwe Winter, Australian BioCommonsHost: Dr. Melissa Burke, Australian BioCommons Training materials Files and materials included in this record: Event metadata (PDF): Information about the event including, description, event URL, learning objectives, prerequisites, technical requirements etc. R notebooks (zip): R markdown and html rendered files, input files. Materials shared elsewhere: Training materials webpage Melissa Burke (melissa@biocommons.org.au) Bioinformatics http://edamontology.org/topic_0091, Analysis http://edamontology.org/operation_2945, Enrichment analysis http://edamontology.org/operation_3501
WEBINAR: Making sense of gene and protein lists with functional enrichment analysis

This record includes training materials associated with the Australian BioCommons webinar ‘Making sense of gene and protein lists with functional enrichment analysis’. This webinar took place on 23 October 2024.
Topic description
Do you have a long list of genes or proteins from omics experiments...

Keywords: Bioinformatics, Enrichment analysis

WEBINAR: Making sense of gene and protein lists with functional enrichment analysis https://dresa.org.au/materials/webinar-making-sense-of-gene-and-protein-lists-with-functional-enrichment-analysis This record includes training materials associated with the Australian BioCommons webinar ‘Making sense of gene and protein lists with functional enrichment analysis’. This webinar took place on 23 October 2024. Topic description Do you have a long list of genes or proteins from omics experiments that you don’t know what to do with? This webinar explains how functional enrichment analysis can be used to understand what these lists mean by employing gene ontology and pathway information to highlight the underlying biology. We’ll discuss the statistics that underpin enrichment analysis methods and some of the most commonly used tools, databases and workflows. Speakers: Dr Hossein Valipour Kahrood, Bioinformatician, Monash Genomics and Bioinformatics Platform Dr Cali Willet, Senior Research Bioinformatician, Sydney Informatics Hub, The University of Sydney Host: Dr Melissa Burke, 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. Functional_enrichment_webinar: 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://www.youtube.com/watch?v=AvpH2WMNXxA Melissa Burke (melissa@biocommons.org.au) Bioinformatics, Enrichment 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
WORKSHOP: Unlocking nf-core - customising workflows for your research

This record includes training materials associated with the Australian BioCommons workshop Unlocking nf-core - customising workflows for your research’. This workshop took place over two, 3 hour sessions on 18-19 May 2023.

Event description

Processing and analysing omics datasets poses many...

Keywords: Bioinformatics, Workflows, Nextflow, nf-core

WORKSHOP: Unlocking nf-core - customising workflows for your research https://dresa.org.au/materials/workshop-unlocking-nf-core-customising-workflows-for-your-research-1584ff39-e007-4422-9fd5-4e407df6b6c5 This record includes training materials associated with the Australian BioCommons workshop Unlocking nf-core - customising workflows for your research’. This workshop took place over two, 3 hour sessions on 18-19 May 2023. Event description Processing and analysing omics datasets poses many challenges to life scientists, particularly when we need to share our methods with other researchers and scale up our research. Public and reproducible bioinformatics workflows, like those developed by nf-core, are invaluable resources for the life science community. nf-core is a community-driven effort to provide high-quality bioinformatics workflows for common analyses including, RNAseq, mapping, variant calling, and single cell transcriptomics. A big advantage of using nf-core workflows is the ability to customise and optimise them for different computational environments, types and sizes of data and research goals.  This workshop will set you up with the foundational knowledge required to run and customise nf-core workflows in a reproducible manner. On day 1 you will learn about the nf-core tools utility, and step through the code structure of nf-core workflows. Then on day 2, using the nf-core/rnaseq workflow as an example, you will explore the various ways to adjust the workflow parameters, customise processes, and configure the workflow for your computational environment. This workshop event and accompanying materials were developed by the Sydney Informatics Hub, University of Sydney in partnership with Seqera Labs, Pawsey Supercomputing Research Centre, and Australia’s National Research Education Network (AARNet). The workshop was enabled through the Australian BioCommons - Bring Your Own Data Platforms project (Australian Research Data Commons and NCRIS via Bioplatforms Australia).  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. nfcore_Schedule: Schedule for the workshop providing a breakdown of topics and timings nfcore_Q_and_A: Archive of questions and their answers from the workshop Slack Channel. Materials shared elsewhere: This workshop follows the accompanying training materials that were developed by the Sydney Informatics Hub, University of Sydney in partnership with Seqera Labs, Pawsey Supercomputing Research Centre, and Australia’s National Research Education Network (AARNet).  https://sydney-informatics-hub.github.io/customising-nfcore-workshop Melissa Burke (melissa@biocommons.org.au) Bioinformatics, Workflows, Nextflow, nf-core
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