Other Open Access
Freytag, Saskia; Barugahare, Adele; Doyle, Maria; Ansell, Brendan; Varshney, Akriti; Bourke, Caitlin; Conradsen, Cara; Jung, Chol-Hee; Sandoval, Claudia; Chandrananda, Dineika; Zhang, Eden; Rosello, Fernando; Iacono, Giulia; Tarasova, Ilariya; Chung, Jessica; Moffet, Joel; Gustafsson, Johan; Ding, Ke; Feher, Kristen; Perlaza-Jimenez, Laura; Crowe, Mark; Ma, Mengyao; Kandhari, Nitika; Williams, Sarah; Nelson, Tiffanie; Schreiber, Veronika; Pinzon Perez, William
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.
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
Summarized experiments and getting started with Bioconductor
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.
This is derived from material produced as part of The Carpentries Incubator project
Index of training materials.pdf