Leland Stanford Junior University

Darya Y Orlova

Leonore A Herzenberg

David R Parks

Wayne A Moore

Stephen W Meehan

Guenther Walther

Andrei Vitalievich Chernyshev

Alexander E Moskalensky

Connor Meehan

Connor G W Meehan

Some embodiments provide methods, systems and computer-readable media that employ adaptive binning and dissimilarity scores based on a quadratic form distance for multidimensional data for matching clusters in data corresponding to different sample. Some embodiments provide methods, systems and computer-readable media for rendering a first interactive display including a two-dimensional plot of at least a portion of a multidimensional data set and a corresponding second interactive display including a plurality of single parameter charts or histograms, each displaying information corresponding to one-dimensional measurements of a different parameter in the multidimensional data set.

Systems and methods for cluster matching across samples and guided visualization of multidimensional cytometry data

The described invention provides a method and/or system for analyzing data using population clustering through density based merging, and a method for guiding clustering strategy through entropy-based ranking score.

Cluster processing and ranking methods including methods applicable to clusters developed through density based merging

The described invention provides a method for quantifying cellular antigens that is independent of specially prepared calibration beads and antibody reagents. The described method can be applied to both low and high affinity antibodies, under both saturating and non-saturating binding conditions.

Quantification of antigen molecules using dynamic flow cytometry

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Menlo Park, CA, United States of America

Darya Y Orlova