Methods for analysis of large sets of multiparameter data

US6178382A · kind A · utility

Assignee

• The Board of Trustees of the Leland Stanford Junior University · US

Inventors

• Mario Roederer · Bethesda, US
• Adam S. Treister · Redwood City, US
• Martin Bigos · San Francisco, US
• David R. Parks · San Francisco, US
• Wayne Moore · San Francisco, US
• Leonore A. Herzenberg · Stanford, US

Key dates

• Filing date: Jun 23, 1998
• Grant date: Jan 23, 2001
• Expiry date: Jun 23, 2018

Classification

• Technology area (CPC G): Physics
• CPC primary: G01N33/50
• WIPO field: Measurement
• WIPO sector: Instruments

Abstract

This invention relates a series of methods for the visual representation and subsequent application of analyses on complex data sets. In particular, this invention is useful for the analysis of multiple sample sets that share common features, for which similar types of analyses are desired. Three concepts are embodied to aid in this analysis: "Functional equivalence by Algorithmic Polymorphism" (FEAP), in which an analysis algorithm is abstracted through the use of an associated name; a genealogical metaphor for the representation of successive or parallel analysis steps, in which "families" of analyses can be easily copied between different sample data sets; and batch analysis through the creation of multi-sample analysis surrogates (MSAS), which are groups of samples wherein analyses applied to an MSAS is then applied to every sample within the MSAS group. This invention has particular utility in the analysis of data derived from flow cytometers, the analysis of complex demographic data, and other similar data sets.