We recently hosted a very popular webinar, “Placing viSNE in Your Toolbox” featuring special guest Dr. Anna Belkina of Boston University School of Medicine. More than 500 investigators registered for our event to learn about cutting-edge tools and techniques for optimizing results from high-dimensional cytometry datasets.
Missed our latest viSNE presentation?
View the webinar recording here:
High-dimensional flow cytometry data (both fluorescent or mass) require new visualization and analysis tools such as viSNE/t-SNE. Cytobank is equipped to handle these high parameter data and transform it quickly into results.
In last week’s webinar, we explored and demonstrated how to leverage advanced viSNE techniques (more specifically, Cytobank’s advanced viSNE tools) to automate and optimize analysis of large cytometry datasets with precision. Read on to see our top five takeaways from the webinar.
Five key points from Dr. Anna Belkina’s presentation,
“Placing viSNE in Your Toolbox”:
- viSNE is a dimensionality-reduction algorithm that works well for flow cytometry data, as well as many other data types. Cytobank will soon accept direct uploads of many more new data types. Keep an eye out for an invitation in Cytobank to beta test as soon as this new feature goes live.
- Analyze many cell events to detect rare populations:
- viSNE parameters require adjustment to resolve major and minor cell populations in large datasets.
- Cytobank’s viSNE implementation provides the necessary flexibility to define and optimize viSNE parameters, such as iterations and perplexity.
- Combining data analysis tools, for example viSNE+SPADE, creates an analysis pipeline aimed at extracting maximum information from high parameter data.
- viSNE analysis is available on Cytobank Premium or Enterprise editions only:
- Please send any general viSNE comments or questions to our support team.
- For specific questions regarding Dr. Belkina’s research please contact her directly at email@example.com.