Multi-channel system and methods for sorting particles

Patent metadata

Field	Value
Publication number	US-10100278-B2
Application number	US-201615179722-A
Country	US
Kind code	B2
Filing date	Jun 10, 2016
Priority date	Mar 28, 2003
Publication date	Oct 16, 2018
Grant date	Oct 16, 2018

Abstract

A multi-channel system for classifying particles in a mixture of particles according to one or more characteristics including a common source of electromagnetic radiation for producing a beam of electromagnetic radiation and a beam splitter for producing multiple beams of electromagnetic radiation for directing multiple beams of electromagnetic radiation to each interrogation location associated with each flow channel of the multi-channel system.

First claim

We claim:

1. A method of analyzing sperm comprising:
a. detecting fluorescence emissions produced by stained sperm illuminated with a laser beam;
b. producing waveform pulses based on detected fluorescence emissions produced by stained sperm illuminated with the laser beam;
c. extracting features of the waveform pulses in the form of values;
d. representing the values of the extracted features in a feature space;
e. calculating a posteriori probability the stained sperm belongs to at least a first population of X chromosome bearing sperm and a second population of Y chromosome bearing sperm based on positions of the represented extracted feature values in the feature space and a priori probabilities associated with those same positions in the feature space; and
f. classifying individual sperm as belonging to the first population of X chromosome bearing sperm or the second population of Y chromosome bearing sperm based on which population has a higher posteriori probability.

2. The method of claim 1 wherein the feature space comprises values having multiple components with uni-variate Gaussian distributions of extracted features or values having multiple components with bi-variate Gaussian distributions of extracted features.

3. The method of claim 2 wherein the priori probabilities associated with the positions in the feature space are based on a model selected from: a model having two components with Gaussian distributions, a model having three components with Gaussian distributions; and a model having four components with Gaussian distributions.

4. The method of claim 1 , wherein a third population of stained sperm comprises unaligned X- and Y-chromosome bearing sperm.

5. The method of claim 1 , wherein a third population of stained sperm comprises unaligned X-chromosome bearing sperm and a fourth population of stained sperm comprises unaligned Y-chromosome bearing sperm.

6. The method of claim 1 wherein the extracted features include a peak height and a peak area of the waveform pulses produced by stained sperm.

7. The method of claim 1 further comprising a step of establishing a decision boundary at which the posteriori probability of a stained sperm belonging to the first population of X chromosome bearing sperm is equal to the posteriori probability of the stained sperm belonging to the second population of Y chromosome bearing sperm.

8. The method of claim 1 wherein steps e) and f) are only applied to sperm having waveform pulses including extracted features having a pulse width indicative of a single X- or Y-chromosome bearing sperm.

9. The method of claim 1 , wherein the priori probabilities associated with the positions in the feature space are based on a Gaussian mixture model.

10. A method of sorting sperm comprising:
a. detecting fluorescence emissions produced by stained sperm illuminated with a laser beam;
b. producing waveform pules based on detected fluorescence emissions produced by stained sperm illuminated with the laser beam;
c. extracting features of the waveform pulses in the form of values
d. representing the values of the extracted features in a feature space;
e. calculating a posteriori probability the stained sperm belongs to at least a first population of X chromosome bearing sperm and a second population of Y chromosome bearing sperm based on positions of the represented extracted feature values in the feature space and a priori probabilities associated with those same positions in the feature space; and
f. classifying individual sperm as belonging to the first population of X chromosome bearing sperm or the second population of Y chromosome bearing sperm based on which population has a higher posteriori probability; and
g. sorting sperm based on the classification.

11. The method of claim 10 , wherein the feature space comprises values having multiple components with uni-variate Gaussian distributions of extracted features or values having multiple components with bi-variate Gaussian distributions of extracted features.

12. The method of claim 11 , wherein the priori probabilities associated with the positions in the feature space are based on a model selected from: a model having two components with Gaussian distributions, a model having three components with Gaussian distributions; and a model having four components with Gaussian distributions.

13. The method of claim 10 , wherein a third population of stained sperm comprises unaligned X- and Y-chromosome bearing sperm.

14. The method of claim 10 , wherein a third population of stained sperm comprises unaligned X-chromosome bearing sperm and a fourth population of stained sperm comprises unaligned Y-chromosome bearing sperm.

15. The method of claim 10 , wherein the extracted features include a peak height and a peak area of the waveform pulses produced by stained sperm.

16. The method of claim 10 , further comprising a step of establishing a decision boundary at which the posteriori probability of a stained sperm belonging to the first population of X chromosome bearing sperm is equal to the posteriori probability of the stained sperm belonging to the second population of Y chromosome bearing sperm.

17. The method of claim 10 , wherein the step of sorting sperm based on the classification further comprises separating sperm by electromagnetic deflection based on the classification.

18. The method of claim 10 , wherein the step of sorting sperm based on the classification further comprises photo-damaging sperm based on the classification.

19. The method of claim 10 , wherein the priori probabilities associated with the positions in the feature space are based on a Gaussian mixture model.

Assignees

• Inguran Llc

Inventors

• Durack Gary
• Wallace Jeffrey D
• Vandre Gary P
• Westfall Lon A
• Hatcher Jeremy T
• Nayak Niraj V

Classifications

• G01N2015/1415

  Control of particle position · CPC title

• Y10T436/2525

  Stabilizing or preserving · CPC title

• Y10T436/25

  including sample preparation · CPC title

• G01N2021/6439

  with indicators, stains, dyes, tags, labels, marks · CPC title

• C12N5/0612 Primary

  sorting of gametes, e.g. according to sex or motility · CPC title