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8 materials found

Authors: Harrison, Paul (orcid: 0000...  or Tim Sherratt 

Sharing a Trove List as a CollectionBuilder exhibition

You’ve been collecting and annotating items relating to your research project in a Trove List. You’d like to display the contents of your list as an online exhibition for others to explore. CollectionBuilder creates online exhibitions using static web...

Keywords: Trove, Trove List, CollectionBuilder, collection, GLAM Workbench, exhibition, HASS

Resource type: tutorial

Sharing a Trove List as a CollectionBuilder exhibition https://dresa.org.au/materials/sharing-a-trove-list-as-a-collectionbuilder-exhibition You’ve been collecting and annotating items relating to your research project in a Trove List. You’d like to display the contents of your list as an online exhibition for others to explore. [CollectionBuilder](https://collectionbuilder.github.io/) creates online exhibitions using static web technologies. But how do you get your List data from Trove into CollectionBuilder? This tutorial from the Trove Data Guide walks through the complete process step-by-step. Tim Sherratt (tim@timsherratt.au) ARDC Community Data Lab Trove, Trove List, CollectionBuilder, collection, GLAM Workbench, exhibition, HASS
Create a layer in the Gazetteer of Historical Australian Placenames using metadata from Trove’s digitised maps

Trove includes thousands of digitised maps, created and published across the last few centuries. You want to create a collection of maps relating to your area of interest and explore it using the Gazetteer of Historical Australian Placenames (GHAP). You know it’s possible to add layers to GHAP,...

Keywords: Trove, maps, Gazetteer of Historical Australian Placenames (GHAP), GLAM Workbench, geospatial, HASS

Resource type: tutorial

Create a layer in the Gazetteer of Historical Australian Placenames using metadata from Trove’s digitised maps https://dresa.org.au/materials/create-a-layer-in-the-gazetteer-of-historical-australian-placenames-using-metadata-from-trove-s-digitised-maps Trove includes thousands of digitised maps, created and published across the last few centuries. You want to create a collection of maps relating to your area of interest and explore it using the Gazetteer of Historical Australian Placenames (GHAP). You know it’s possible to add layers to GHAP, but how do you get the data from Trove in a format that can be uploaded as a layer? This tutorial from the Trove Data Guide walks through the complete process step-by-step. Tim Sherratt (tim@timsherratt.au) ARDC Community Data Lab Trove, maps, Gazetteer of Historical Australian Placenames (GHAP), GLAM Workbench, geospatial, HASS
Comparing manuscript collections from Trove in Mirador

You want to compare the contents of two digitised manuscript collections and examine individual documents side-by-side. The Mirador viewer can be configured as a flexible, research workspace that displays multiple images from different sources, but how do you get...

Keywords: Trove, images, manuscripts, GLAM Workbench, IIIF, HASS, Mirador

Resource type: tutorial

Comparing manuscript collections from Trove in Mirador https://dresa.org.au/materials/comparing-manuscript-collections-in-mirador You want to compare the contents of two digitised manuscript collections and examine individual documents side-by-side. The [Mirador viewer](https://projectmirador.org/) can be configured as a flexible, research workspace that displays multiple images from different sources, but how do you get manuscript collections from Trove to Mirador? This tutorial from the Trove Data Guide walks through the complete process step-by-step. Tim Sherratt (tim@timsherratt.au) ARDC Community Data Lab Trove, images, manuscripts, GLAM Workbench, IIIF, HASS, Mirador
Working with a Trove collection in Tropy

You want to be able to work on a collection of digitised images from Trove on your desktop – adding notes, transcriptions, and annotations. Tropy is a useful tool for managing collections of research images, but how do you import a collection of images from Trove into...

Keywords: Trove, images, Tropy, IIIF, GLAM Workbench, HASS

Resource type: tutorial

Working with a Trove collection in Tropy https://dresa.org.au/materials/working-with-a-trove-collection-in-tropy You want to be able to work on a collection of digitised images from Trove on your desktop – adding notes, transcriptions, and annotations. [Tropy](https://tropy.org/) is a useful tool for managing collections of research images, but how do you import a collection of images from Trove into Tropy? This tutorial from the [Trove Data Guide](https://tdg.glam-workbench.net/home.html) walks through the complete process step-by-step. Tim Sherratt (tim@timsherratt.au) ARDC Community Data Lab Trove, images, Tropy, IIIF, GLAM Workbench, HASS
Analysing keywords in Trove’s digitised newspapers

You want to explore differences in language use across a collection of digitised newspaper articles. The Australian Text Analytics Platform provides a Keywords Analysis tool that helps you...

Keywords: text analysis, Australian Text Analytics Platform (ATAP), Trove, GLAM Workbench, Trove Newspaper and Gazette Harvester, newspapers, HASS

Resource type: tutorial

Analysing keywords in Trove’s digitised newspapers https://dresa.org.au/materials/analysing-keywords-in-trove-s-digitised-newspapers You want to explore differences in language use across a collection of digitised newspaper articles. The [Australian Text Analytics Platform](https://www.atap.edu.au/) provides a [Keywords Analysis tool](https://github.com/Australian-Text-Analytics-Platform/keywords-analysis) that helps you examine whether particular words are over or under-represented across collections of text. But how do get data from Trove’s newspapers to the keyword analysis tool? This tutorial from the [Trove Data Guide](https://tdg.glam-workbench.net/home.html) walks through the complete process step-by-step. Tim Sherratt (tim@timsherratt.au) ARDC Community Data Lab text analysis, Australian Text Analytics Platform (ATAP), Trove, GLAM Workbench, Trove Newspaper and Gazette Harvester, newspapers, HASS
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