Two days, four participants, four aims

The first Tidyomics community hackathon took place on 1st and 2nd June in Turku, Finland, as part of the EuroBioC2026 conference pre-events. Here, four researchers from around the globe joined efforts to extend the capabilities of tidy operations for omics data, focusing on solving current bugs.

Concretely, the hackathon focused on four key aspects:

1. Development
2. Bugs
3. Enhancements
4. Learning

What’s new?

The advances produced during this hackathon are available and described in detail in the BioHackrXiv publication. In summary:

1. tidyAnnData has been introduced as a new package to provide tidy operations for AnnData objects generated by the anndataR package
2. Information access to core Tidyomics packages was inconsistent and some links were broken in the main GitHub page; taking advantage of this hackathon, access to correct information was restored
3. The DFplyr package was enhanced by improving current methods (e.g. GroupedDataFrame and count.DataFrame) and making them suitable for universal column names
4. The tidybulk package was enhanced to adjust the lfcShrink() function to use the different available methods (apeglm and ashr) and to generate a reduced dimensionality-based plot (PCA) for visual inspection of e.g. batch effects and outlier detection
5. A standardised vignette for tidySingleCellExperiment has been developed to provide an extensive and concise guide for new users, encompassing both examples comparable to base R code and best practices on single-cell analysis using tidy operations

What’s next?

Five major contributions in two productive days is all a win!

Beyond this wonderful experience, there is work to do: finalising the development of tidyAnnData to make it publicly available, fixing additional bugs and enhancing current packages, and standardising the rest of the Tidyomics packages’ vignettes. These efforts open the doors for future events and continuing open-science work.

We look forward to seeing you at the coming Tidyomics hackathon events to speed up software development, bug fixing, and new material development from open problems in Tidyomics, or to work on your own ideas for providing tidy operations in omics data analysis.