*Apologies, this course is now full*
We may offer the course again next year, so please stay tuned.
The increasingly easy access to large SNP datasets for wild organisms means that it’s an exciting time to be working in population genomics and molecular ecology. The size of these datasets opens up a wealth of possibilities for deeper and more diverse analyses and understandings of biological process. Yet, it also means that the computational demands of analysis are far greater than before, and poorly suited to stand-alone executable software that worked well for microsatellite DNA, mtDNA, AFLPs etc.
Enter stage left a rapidly growing number of packages for the R statistical software platform. R packages offer many analysis options to the keen molecular ecologist, and are often under active improvement as authors add new features. Another useful feature of R packages is that with some knowledge of R scripting, multiple packages can be strung together to create complete workflows, incorporating all steps from data quality control, to sophisticated analyses, to output of publication-ready figures.
But, all this can be confusing for somebody entering the field. Even for experienced scientists, the smorgasbord of available packages with their many and varied data formats means that progress can be slow.
The Environomics FSP and our collaborators are keen to help you get the most out of R for your population genomics research. We will be holding a training workshop in early April 2019 run by designers of popular R packages and experienced practitioners. The course format would be a mixture of conceptual presentations, followed by hands-on tutorials where you’d get a chance to analyse your own data. The content of the course will be guided in part by a survey of people who register an expression of interest with Alex Bouma.
Would you be interested in attending a course on analysis of population genomics in R with SNP markers?
Places will be limited so please register your interest to stay updated on further details
Hosted by the CSIRO Environomics Future Science Platform
Banner image credit: Sequence alignment by Shaury Nash at https://www.flickr.com/photos/shaury/2653833040/ under a Creative Commons Attribution ShareAlike 2.0 generic. Full terms at https://creativecommons.org/licenses/by-sa/2.0/