Tidyomics: Enabling Tidy Data Analysis Workflows for Complex Biological Data

The Love lab develops statistical methods and open source software for analysis of high dimensional biological data. We collaborate with groups in Genetics, Biology, Computer Science, Neuroscience/Psychiatry, and Cancer Epidemiology, to improve data analysis tools and workflows, with a focus on transcriptomics. Here I will talk about updates from an international team within R/Bioconductor working to enable tidy data analysis for complex objects, such as genome annotations or single cell expression sets.