November 30, 2018  |  Announcements, FlowSOM, Release Notes  |  By  |  0 Comments

Announcing: Cytobank 7.0 with FlowSOM

We are delighted to introduce our latest version of Cytobank.


Included in this release are many performance and interface improvements, as well as a notable new addition to our repertoire of integrated algorithms. As we continue to evolve and improve our platform in response to your needs and feedback, we also look to leaders in our field to expand our capabilities and bring high-level developments in bioinformatics to you in an approachable and easy-to-use way.
In this spirit, we introduce
FlowSOM in Cytobank

FlowSOM is an algorithm that utilizes self-organizing maps (SOMs), an unsupervised Machine Learning technique, for automated clustering and dimensionality reduction. FlowSOM speeds time to analysis and quality of clustering with maps that can reveal how markers are behaving on all cells, and can detect subsets that might otherwise be missed. We worked closely with Sofie Van Gassen and Yvan Saeys the original authors of the algorithm, as well as the seminal publication, to integrate FlowSOM seamlessly into our platform. And now, you can employ this advanced analysis method with Cytobank’s easy-to-use user interface (no R required!).

Explore more with FlowSOM, now available in Premium and Enterprise editions, to see and learn the advantages of adding it to your toolbox. Some of these advantages include:

Boost your productivity with more events, faster in the cloud

Courtesy of the power of the cloud, you can execute multiple FlowSOM runs in parallel for rapid exploration, and you can also run up to 90 million events (with upgraded compute). And you never need to wrestle with installing R or any packages – we make complex algorithms easy to use.

Go deeper with interactive and reproducible results

starplotWhen you run multiple concurrent files through FlowSOM in Cytobank, you don’t have to concatenate, so the per-file analysis is always preserved in the output. FlowSOM output is not limited to just a static image. Cytobank automatically creates a FlowSOM analysis experiment after each run finishes, and it auto-gates the FlowSOM-identified metaclusters. These dynamic results can then be refined, and metaclusters can be adjusted and probed within Cytobank with our interactive tools. SOMs can also be reused for new datasets to compare results or to maintain consistency for longitudinal studies.

Combine with the power of viSNE to verify results and optimize settings

flowsomimage4Take your analysis one step further and overlay FlowSOM metaclusters on a viSNE map to better assess the quality of your metaclustering, and inform how you may need to refine and iterate various settings such as target number of metaclusters and normalization.

Get Started with FlowSOM:

Not Already a Cytobank User?