Detection system and user interface for a flow cytometer system

• US 8,229,684 B2
• Filed: 04/29/2010
• Issued: 07/24/2012
• Est. Priority Date: 12/22/2006
• Status: Active Grant

• Current Assignee: Accuri Cytometers, Inc. (Becton Dickinson & Co)
• Original Assignee: Accuri Cytometers, Inc. (Becton Dickinson & Co)
• Inventors: Goebel, Clement James, Rich, Collin A.
• Primary Examiner(s): Wachsman, Hal
• Application Number:
  US12/770,341
• Publication Number:
  US 20100271620A1
• Time in Patent Office: 817 Days
• Field of Search: 702/45, 702/21, 702/32
• US Class Current: 702/45
• CPC Class Codes: G01N 15/1459 the analysis being performed on a sample stream
• CPC Class Codes: G01N 2015/0092 Monitoring flocculation or agglomeration
• CPC Class Codes: G01N 2015/1477 Multiparameters

Abstract

The detection system of the first preferred embodiment includes a detector, having a wide dynamic range, that receives photonic inputs from an interrogation zone and produces an analog signal; and an analog-to-digital converter (ADC), having a high bit resolution, that is coupled to the detector and converts an analog signal to a digital signal. The digital signal includes an initial data set of the full dynamic range of the input signals from the flow cytometer sample. The method of extracting and analyzing data from a flow cytometer system of the first preferred embodiment preferably includes the steps of: collecting a full dynamic range of input signals from a flow cytometer sample; recognizing and annotating aggregate particle events; and storing an initial data set and an annotated data set of the full dynamic range of the input signals from the flow cytometer sample.

Claims

1. A method of extracting and analyzing data from a flow cytometer system comprising the steps of:

collecting a full dynamic range of input signals from a flow cytometer sample in the flow cytometer system;

storing an initial data set of the full dynamic range of the input signals from the flow cytometer sample;

recognizing aggregate particle events in the stored initial data set with use of an algorithm; and

annotating the aggregate particle events in the initial data set to create an annotated data set of the full dynamic range of the input signals from the flow cytometer sample.

2. The method of claim 1, further comprising the steps of:

storing the annotated data set; and

displaying at least one of the initial data set and the annotated data set.

3. The method of claim 2, wherein displaying at least one of the initial data set and the annotated data set occurs after collecting the full dynamic range of input signals from the flow cytometer sample.

4. The method of claim 1, wherein annotating aggregate particle events in the initial data set includes at least one of labeling an aggregate particle event as an “

aggregate particle event” and

labeling a non-aggregate particle event as a “

non-aggregate particle event”

.

5. The method of claim 1 wherein recognizing aggregate particle events in the stored initial data set includes identifying a “

peak-trough-peak”

waveform produced by aggregate particle events.

6. The method of claim 1, further comprising the step of allowing modification of at least one of the initial data set and the annotated data set.

7. The method of claim 6 wherein allowing modification of at least one of the initial data set and the annotated data set further includes utilizing a graphical, menu-driven format that accepts and displays data sets.

8. The method of claim 7 wherein utilizing a graphical, menu-driven format includes displaying separate graphs that are generated from the initial data set, the annotated data set, and the modified data set in separate frames.

9. The method of claim 7 wherein utilizing a graphical, menu-driven format includes displaying a graph generated from at least two of the initial data set, the annotated data set, and the modified data set superimposed on one another in the same graph frame.

10. The method of claim 6 wherein allowing modification of at least one of the initial data set and the annotated data set further includes utilizing a numerical display format that accepts and displays data sets numerically.

11. The method of claim 6, wherein annotating aggregate particle events further includes labeling an aggregate particle event with a descriptor of the separation between particles.

12. The method of claim 6, wherein annotating aggregate particle events further includes labeling an aggregate particle event with the number of aggregate particles in the event.

13. The method of claim 12, wherein allowing modification of at least one of the initial data set and the annotated data set includes altering the number of annotated aggregate particle events in at least one of the initial data set and the annotated data set.

14. The method of claim 13, wherein altering the number of annotated aggregate particle events in at least one of the initial data set and the annotated data set includes permitting a user to remove an annotated aggregate particle event.

15. The method of claim 6 wherein allowing modification of at least one of the initial data set and the annotated data set includes permitting a user to observe at least one of the initial data set and the annotated data set from the full dynamic range of input signals, and permitting the user to identify the appropriate modifications for at least one of the initial data set and the annotated data set.

16. The method of claim 6 wherein allowing modification of at least one of the initial data set and the annotated data set includes permitting a user to manipulate at least one of the initial data set and the annotated data set across the full dynamic range of input signals from the flow cytometer sample and to generate a modified data set.

17. The method of claim 16 wherein allowing modification of at least one of the initial data set and the annotated data set further includes permitting the user to perform at least one of the following:

perform real-time comparisons between the initial data set, the annotated data set, and the modified data set on a single flow cytometer sample;

adjust or undo modifications, to make multiple adjustments on the same initial data set or annotated data set; and

generate at least one subset of data that corresponds to one or more sample populations contained within at least one of the initial data set and the annotated data set.

18. The method of claim 1, further comprising the step of acting upon information generated based on the recognition of one or more aggregate particle events.

19. The method of claim 18, wherein acting upon information includes signaling to a user upon the occurrence of a pattern of aggregate particle events.

20. A method of extracting and analyzing data from a flow cytometer system comprising the steps of:

collecting a full dynamic range of input signals from a flow cytometer sample in the flow cytometer system;

storing an initial data set of the full dynamic range of the input signals from the flow cytometer sample;

recognizing aggregate particle events in the initial data set with use of an algorithm, wherein recognizing aggregate particle events in the initial data set occurs substantially simultaneously with collecting the full dynamic range of input signals from a flow cytometer sample; and

annotating the aggregate particle events in the initial data set to create an annotated data set of the full dynamic range of the input signals from the flow cytometer sample.

21. The method of claim 20, further comprising the steps of:

storing the annotated data set; and

displaying at least one of the initial data set and the annotated data set.

22. The method of claim 20, wherein annotating aggregate particle events in the initial data set includes at least one of labeling an aggregate particle event as an “

aggregate particle event” and

labeling a non-aggregate particle event as a “

non-aggregate particle event”

.

23. The method of claim 20, further comprising the step of allowing modification of at least one of the initial data set and the annotated data set.

24. The method of claim 23 wherein allowing modification of at least one of the initial data set and the annotated data set further includes utilizing a graphical, menu-driven format that accepts and displays data sets.

25. The method of claim 23, wherein allowing modification of at least one of the initial data set and the annotated data set includes altering the number of annotated aggregate particle events in at least one of the initial data set and the annotated data set.

26. The method of claim 25, wherein allowing modification of at least one of the initial data set and the annotated data set includes permitting a user to remove an annotated aggregate particle event.

27. The method of claim 20, further comprising the step of acting upon information generated based on the recognition of one or more aggregate particle events.

28. The method of claim 27, wherein acting upon information includes sorting a particle based on whether the particle is an aggregate particle.

29. A method of extracting and analyzing data from a flow cytometer system comprising the steps of:

collecting a full dynamic range of input signals from a flow cytometer sample in the flow cytometer system;

storing an initial data set of the full dynamic range of the input signals from the flow cytometer sample;

recognizing aggregate particle events in the initial data set with use of an algorithm;

annotating the aggregate particle events in the initial data set to create an annotated data set of the full dynamic range of the input signals from the flow cytometer sample; and

acting upon information generated based on the recognition of one or more aggregate particle events, wherein acting upon information includes sorting a particle based on whether the particle is an aggregate particle.