WORKSHOP: R: fundamental skills for biologists
Creators: name: Freytag, Saskia
name: Barugahare, Adele
name: Doyle, Maria
name: Ansell, Brendan
name: Varshney, Akriti
name: Bourke, Caitlin
name: Conradsen, Cara
name: Jung, Chol-Hee
name: Sandoval, Claudia
name: Chandrananda, Dineika
name: Zhang, Eden
name: Rosello, Fernando
name: Iacono, Giulia
name: Tarasova, Ilariya
name: Chung, Jessica
name: Moffet, Joel
name: Gustafsson, Johan
name: Ding, Ke
name: Feher, Kristen
name: Perlaza-Jimenez, Laura
name: Crowe, Mark
name: Ma, Mengyao
name: Kandhari, Nitika
name: Williams, Sarah
name: Nelson, Tiffanie
name: Schreiber, Veronika
name: Pinzon Perez, William
Publisher: name: Zenodo
Year: 2022
Subjects: subject: Bioinformatics
subject: FOS: Computer and information sciences
subject: Analysis
subject: Statistics
subject: FOS: Mathematics
subject: R software
subject: RStudio
subject: Data visualisation
subject: http://edamontology.org/topic_0091
subject: http://edamontology.org/operation_2945
subject: http://edamontology.org/topic_2269
subject: http://edamontology.org/topic_0092

description: 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. <strong>Event description</strong> 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. <strong>Files and materials included in this record:</strong> 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. <strong>Materials shared elsewhere:</strong> 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/