Cluster Analysis – Current Trends 2021

Organized by: Juliette Griffié (EPFL), Daniel Nieves (University of Birmingham), Dylan Owen (University of Birmingham), Daniel Sage (EPFL)

This special session on cluster analysis tools for SMLM is aimed at method development specialists and users alike. It will include a short series of technical talks on novel approaches to clustering as well as benchmarking. This year edition will however put users in the spotlight, with talks focusing on cutting edge applications to SMLM cluster analysis in cellular biology.

Cluster Analysis Benchmarking

To method developers: A recent paper [1] published by D.J Nieves & D.M. Owen et al provides the tools for standardized benchmarking of state of the art and novel cluster analysis methods. In the context of SMLMS, we offer the opportunity to compare your method using both these data sets and metrics. You will find them below.

The data consists of spatial points pattern in the absence or presence of multiple blinking. For more information, join us on Slack.

Please, send us the results and metrics by August 23rd to be taken into consideration for the dedicated talk on benchmarking during the conference.

[1] Daniel J. Nieves, Jeremy A. Pike, Florian Levet, Juliette Griffié, Daniel Sage, Edward A.K. Cohen, Jean-Baptiste Sibarita, Mike Heilemann, Dylan M. Owen, “A framework for evaluating the performance of SMLM cluster analysis algorithms”, biorxiv, 2021.