Methods for analysis of large sets of multiparameter data

• US 6,178,382 B1
• Filed: 06/23/1998
• Issued: 01/23/2001
• Est. Priority Date: 06/23/1998
• Status: Expired due to Term

• Current Assignee: Board of Trustees of the Leland Stanford Junior University (Stanford Management Co.)
• Original Assignee: Board of Trustees of the Leland Stanford Junior University (Stanford Management Co.)
• Inventors: Parks, David R., Roederer, Mario, Moore, Wayne A., Treister, Adam S., Herzenberg, Leonore A., Bigos, Martin
• Primary Examiner(s): Hoff, Marc S.
• Assistant Examiner(s): Bui, Bryan
• Application Number:
  US09/103,284
• Time in Patent Office: 945 Days
• Field of Search: 702/19-21, 345/346, 345/356, 435/7.1, 435/7.2, 435/69.3
• US Class Current: 702/21
• CPC Class Codes: G01N 33/50 Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing measuring or testing processes involving enzymes or microorganisms, compositions or test papers therefor; processes for forming such compositions, condition responsive control in microbiological or enzymological processes C12Q
• CPC Class Codes: G06T 11/206 Drawing of charts or graphs

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.

Claims

1. A computer-implemented method for analyzing complex multiparamenter data sets, the method comprising:

analyzing a first dataset by successive application of a first hierarchically structured set of algorithmic steps,

analyzing a second dataset by successive application of a second hierarchically structured set of algorithmic steps, wherein the first and second sets of algorithmic steps are structurally and functionally equivalent, and wherein the first and second sets contain distinct but similar algorithmic steps, and

displaying the analyzed data to a user.

2. The method of claim 1 wherein the distinct but similar algorithmic steps perform analogous computational functions on data sets having distinct structure but similar content.

3. The method of claim 1 wherein the first data set has a first set of parameters, the second data set has a second set of parameters, and the first set of parameters is identical to the second set of parameters.

4. The method of claim 1 wherein the first data set has a first set of parameters, the second data set has a second set of parameters, and the first set of parameters is different from the second set of parameters.

5. The method of claim 1 wherein the first data set and the second data set comprise data selected from the group consisting of discrete data, continuous data, and categorical data.

6. The method of claim 1 wherein the first data set and the second data set comprise flow cytometric data.

7. The method of claim 1 wherein the first hierarchically structured set of steps comprises top steps applied directly to the first data set, and dependent steps applied to data resulting from application of the top steps.

8. The method of claim 1 wherein the first hierarchically structured set of steps comprises analysis steps and data display steps.

9. The method of claim 8 wherein the analysis steps comprise subset selection steps and computational steps.

10. The method of claim 8 wherein the analysis steps comprise a parent step and children steps, wherein the children steps analyze data resulting from the parent step.

11. The method of claim 8 wherein the data display steps comprise generating a display chosen from the group consisting of a data graph and a data table.

12. The method of claim 1 further comprising displaying a graphical representation of the first hierarchically structured set of steps to the user.

13. The method of claim 12 wherein the graphical representation is a tree structure that displays the hierarchical dependence between the steps.

14. The method of claim 12 wherein sibling steps in the graphical representation have distinct labels.

15. The method of claim 12 wherein customized steps are displayed with a visual mark distinguishing them from uncustomized steps.

16. The method of claim 1 further comprising enabling the user to generate a duplicate of a hierarchically structured set of steps, and apply the duplicate to a specified data set.

17. The method of claim 16 wherein the user is enabled to generate the duplicate by selecting a portion of a graphical representation of the hierarchically structured set to be duplicated, and specifying a data set to which the duplicate is to be applied.

18. The method of claim 16 wherein the specified data set is a result of analysis steps.