09-12, 15:15–16:15 (Europe/Berlin), Workshop room I - MW 0337
In order to use the best performing methods for each step of the single-cell analysis process, bioinformaticians need to use multiple ecosystems and programming languages. This is unfortunately not that straightforward. We will give an overview of the different levels of interoperability, and how it is possible to integrate them in a single workflow.
For package developers, making methods accessible is important. We will provide information on how to do this well on the package and method level.
Any bioinformatician that has analysed a single-cell dataset knows that using methods developed for different ecosystems or programming languages is necessary but painful.
Any package developer has asked themselves the question on how to best provide access to their tool or method.
We will give an overview of the interoperability tools you can use when analysing a single-cell dataset: do you want to convert your data to a different data format, or is just calling one R function in your Jupyter notebook sufficient? Do you want fine-grained control over each step in the analysis pipeline or do you run a series of scripts that you really should convert to a workflow system?
We will give information on different options for package developers to provide better interoperability. Should you reimplement your package in a new language? How do you ensure that the results are the same?
In order to follow this workshop, we expect the participants to have some Python or R programming knowledge. You can find the documentation and slides at https://saeyslab.github.io/polygloty/
Previous knowledge expected
Computer science engineer with a passion for interactive analysis of multidimensional bioimaging and hackathons.
Robrecht, CTO at Data Intuitive (data-intuitive.com), is passionate about making single-cell analysis more accessible and reliable. As the lead developer of Viash, he's all about creating workflows that are easy to reproduce and reuse. He's also the lead developer of OpenProblems, a platform dedicated to establishing the best practices for single-cell analysis by rigorously testing different computational methods. These efforts drive the creation of new living best practices (sc-best-practices.org) and the development of modular single-cell workflows (openpipelines.bio).