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://zenodo.org/records/7072910
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)
Williams, Sarah
Mehdi, Ahmed (orcid: 0000-0002-9300-2341)
Matigan, Nick
Barugahare, Adele (orcid: 0000-0002-8976-0094)
Harrison, Paul (orcid: 0000-0002-3980-268X)
Morgan, Steven (orcid: 0000-0001-6038-6126)
Whitfield, Holly (orcid: 0000-0002-7282-387X)
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://zenodo.org/records/6766951
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)
Freytag, Saskia (orcid: 0000-0002-2185-7068)
Barugahare, Adele (orcid: 0000-0002-8976-0094)
Doyle, Maria
Ansell, Brendan (orcid: 0000-0003-0297-897X)
Varshney, Akriti
Bourke, Caitlin (orcid: 0000-0002-4466-6563)
Conradsen, Cara (orcid: 0000-0001-9797-3412)
Jung, Chol-Hee (orcid: 0000-0002-2992-3162)
Sandoval, Claudia
Chandrananda, Dineika (orcid: 0000-0002-8834-9500)
Zhang, Eden (orcid: 0000-0003-0294-3734)
Rosello, Fernando (orcid: 0000-0003-3885-8777)
Iacono, Giulia (orcid: 0000-0002-1527-0754)
Tarasova, Ilariya (orcid: 0000-0002-0895-9385)
Chung, Jessica (orcid: 0000-0002-0627-0955)
Moffet, Joel
Gustafsson, Johan (orcid: 0000-0002-2977-5032)
Ding, Ke
Feher, Kristen
Perlaza-Jimenez, Laura (orcid: 0000-0002-8511-1134)
Crowe, Mark (orcid: 0000-0002-9514-2487)
Ma, Mengyao
Kandhari, Nitika (orcid: 0000-0002-0261-727X)
Williams, Sarah
Nelson, Tiffanie (orcid: 0000-0002-5341-312X)
Schreiber, Veronika (orcid: 0000-0001-6088-7828)
Pinzon Perez, William
Bioinformatics, Analysis, Statistics, R software, RStudio, Data visualisation
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://zenodo.org/records/5781776
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)
Harrison, Paul (orcid: 0000-0002-3980-268X)
Deshpande, Nandan (orcid: 0000-0002-0324-8728)
Barugahare, Adele (orcid: 0000-0002-8976-0094)
Perry, Andrew (orcid: 0000-0001-9256-6068)
Wong, Nick (orcid: 0000-0003-4393-7541)
Reames, Benjamin
R software, Bioconductor, Bioinformatics, Analysis, Genomics, Sequence analysis