Plugin interface and framework for integrating external algorithms with sample data analysis software

• US 10,438,120 B2
• Filed: 05/09/2016
• Issued: 10/08/2019
• Est. Priority Date: 05/08/2015
• Status: Active Grant

• Current Assignee: FlowJo, LLC (Becton, Dickinson & Co)
• Original Assignee: FlowJo, LLC (Becton, Dickinson & Co)
• Inventors: Simm, Maciej, Almarode, Jay, Stadnisky, Michael D.
• Primary Examiner(s): Kraft, Shih-Wei
• Application Number:
  US15/150,106
• Publication Number:
  US 20160328249A1
• Time in Patent Office: 1,247 Days
• Field of Search: None
• CPC Class Codes: G06F 16/164 File meta data generation
• CPC Class Codes: G06F 9/44526 Plug-ins; Add-ons
• CPC Class Codes: G06N 5/01 Dynamic search techniques; Heuristics; Dynamic trees; Branch-and-bound
• CPC Class Codes: G06N 5/022 Knowledge engineering; Knowledge acquisition
• CPC Class Codes: G16B 50/00 ICT programming tools or database systems specially adapted for bioinformatics
• CPC Class Codes: G16B 50/30 Data warehousing; Computing architectures
• CPC Class Codes: H04L 63/102 Entity profiles
• CPC Class Codes: H04L 67/10 in which an application is distributed across nodes in the network software deployment G06F8/60; multiprogramming arrangements G06F9/46
• CPC Class Codes: H04L 67/141 Setup of application sessions admission control or resource allocation in data switching networks H04L47/70
• CPC Class Codes: H04L 67/143 Termination or inactivation of sessions, e.g. event-controlled end of session
• CPC Class Codes: H04L 67/53 using third party service providers

Abstract

A framework and interface for invoking and assimilating external algorithms and interacting with the algorithms in-session and real-time are described. Embodiments include reproducible, updatable nodes that can be leveraged for data-driven analysis whereby the data itself can direct the algorithm choice, variables, and presentation leading to iteration and optimization in an analysis workflow. Embodiments include an entire discovery or diagnosis process executed on a particular data set, thereby divorcing the discovery or diagnosis process from a specific data set such that the same discovery or diagnosis process, phenotype identification, and visualizations may be repeated on future experiments, published, validated, or shared with another investigator.

Claims

1. A system for providing a plug-in interface framework between data analysis software executed by a computer and an algorithm external to the data analysis software, the system comprising:

a server configured to store a database of information associated with a plurality of executed algorithms, wherein the information comprises results from the plurality of executed algorithms processing sample data; and

a plurality of processor-executable instructions that are resident on a non-transitory computer-readable storage medium and define the plug-in interface framework, wherein the instructions are configured, upon execution by a processor of the computer in communication with the database of information, to cause the computer to;

open a workspace relating to an analysis of a data set during a session of execution of the data analysis software;

create an external population node, wherein the external population node comprises (1) the data set representing data collected by an acquisition instrument, (2) an output folder destination, and (3) a markup language description of the data set, the markup language description including (i) meta-information about the data set and (ii) a specification of previous calculations used to arrive at the data set;

invoke an external algorithm based on the external population node, the external algorithm configured to perform processing on the data set, and wherein the output folder destination defines where the external algorithm is to save results from its processing;

receive, via a network, results from the external algorithm as a result of the processing performed by the external algorithm on the data set;

cause the server to identify a first executed algorithm stored in the database that matches the external algorithm;

cause the server to compare results from the first executed algorithm with the results from the external algorithm;

invoke the external algorithm with a change in the data set of the external population node to receive updated results at the output destination, wherein the change in the data set of the external population node is determined based on the comparison of the results from the first executed algorithm and the results from the external algorithm;

integrate the updated results from the external algorithm into the workspace; and

save the updated results in the workspace.

2. The system of claim 1 wherein the sample data comprises cell data from an experiment.

3. The system of claim 2 wherein the cell data comprises single cell data acquired by a flow cytometer.

4. The system of claim 2 wherein the plug-in interface framework comprises (1) an input file of the sample data, (2) the output destination, and (3) a data description of the sample data.

5. The system of claim 4 wherein the data description comprises (1) metadata about the sample data, (2) an identification of one or more previous calculations used to arrive at the sample data, and (3) an identification of one or more transformations that are used to process and visualize the sample data.

6. The system of claim 2 wherein the instructions are further configured, upon execution by the processor, to cause the computer to:

manage artifacts generated by the external algorithm.

7. The system of claim 2 wherein the instructions are written in a first language, the first language being configured to support calls to programs in a second language, and wherein the external algorithm is written in the second language.

8. The system of claim 7 wherein the first language is an object oriented cross-platform programming language.

9. The system of claim 8 wherein the second language is C.

10. The system of claim 8 wherein the second language is R.

11. The system of claim 8 wherein the second language is a web-based calculation engine language.

12. The system of claim 2 wherein the instructions are further configured, upon execution by the processor, to cause the computer to:

create a derived parameter for the sample data, the derived parameter for use by the data analysis software to create subpopulations within the sample data.

13. The system of claim 2 wherein the data input specification comprises at least one member of the group consisting of (1) a file path for the sample data, (2) a number of parameters for the sample data, (3) a number of clusters for the sample data, (4) a variable for dimension reduction with respect to the sample data, (5) a color selection, (6) a visualization type, and (7) an image type.

14. The system of claim 2 wherein the external algorithm comprises a population identification algorithm.

15. The computer program product of claim 2 wherein the specified algorithm comprises a geometric gating algorithm.

16. The system of claim 2 wherein the specified algorithm comprises a report generation algorithm.

17. The system of claim 2 wherein the specified algorithm comprises a analysis visualization algorithm.

18. The system of claim 2 wherein the specified algorithm comprises a member of the group consisting of a high throughput genomics analysis algorithm and a high throughput phenomic data analysis algorithm.

19. The system of claim 2 wherein the instructions are part of the data analysis software.

20. The system of claim 2 wherein the instructions are configured for execution by the processor of the computer without intervention by a user of the data analysis software.

21. A method for analyzing scientific data comprising:

opening an analysis workspace file relating to an analysis of a data set during a session of execution of a data analysis software;

creating an external population node, wherein the external population node comprises (1) the data set representing data collected by an acquisition instrument, (2) an output folder destination, and (3) a markup language description of the data set, the markup language description including (i) meta-information about the data set and (ii) a specification of previous calculations used to arrive at the data set;

invoking an external algorithm based on the external population node, the external algorithm configured to perform processing on the data set, and wherein the output folder destination defines where the external algorithm is to save results from its processing;

receiving, via a network, results from the external algorithm as a result of the processing performed by the external algorithm on the data set;

causing a remote server to identify a first executed algorithm stored in a database in the remote server that matches the external algorithm, wherein the database stores information associated with a plurality of executed algorithms, and wherein the information comprises results from the plurality of executed algorithms processing sample data;

causing the remote server to compare results from the first executed algorithm with the results from the external algorithm;

invoking the external algorithm with a change in the data set of the external population node to receive updated results at the output destination, wherein the change in the data set of the external population node is determined based on the comparison of the results from the first executed algorithm and the results from the external algorithm;

integrating the updated results from the external algorithm into the analysis workspace file; and

saving the updated results in the analysis workspace file,

wherein the method is performed by a processor of a computing device.

22. The method of claim 21 wherein the external algorithm comprises a cell population identification algorithm.

23. The method of claim 21 wherein the external algorithm comprises a high-throughput genomic data analysis algorithm.

24. The method of claim 21 wherein the external algorithm generates reports and visualizations of analysis results.

25. The method of claim 21 wherein creating the external population node comprises the processor:

requesting, from a user, operational variables to be used by the external algorithm; and

receiving an input including at least one of the operational variables.

26. The method of claim 21 wherein the external algorithm results comprises at least one of:

(1) a comma separated values (CSV) file, (2) a classification results (CLR) file, (3) a Gating markup language file, and (4) a flow cytometry standard (FCS) file.

27. The method of claim 21 further comprising the processor:

detecting a change to the data set; and

in response to detecting the change, re-invoking the external algorithm.