Enhancing flow cytometry discrimination with geometric transformation
In flow cytometry, particles ( 2 ) can be distinguished between populations ( 8 ) by combining n-dimensional parameter data, which may be derived from signal data from a particle, to mathematically achieve numerical results representative of an alteration ( 48 ). An alteration may include a rotational alteration, a scaled alteration, or perhaps even a translational alteration. Alterations may enhance separation of data points which may provide real-time classification ( 49 ) of signal data corresponding to individual particles into one of at least two populations.
1. A flow cytometer comprising:
a nozzle for entraining particles in a fluid stream;
laser focusing optics for focusing a laser beam onto an interrogation point on the fluid stream;
a first detector for producing a first signal affiliated with individual particles in the fluid stream;
a second detector for producing at least one additional signal affiliated with said individual particles in the fluid stream; and
one or more processors having computer readable memory and instructions written thereon to:
detect a first signal from the first detector based on individual particles in the stream;
detect at least one additional signal from the second detector based on individual particles in the stream;
convert said first signal and said at least one additional signal affiliated with said individual particles into n-dimensional parameter data, where n is equal to the number of signals, wherein at least two populations of said individual particles overlap in one of said n-dimensions;
mathematically alter the n-dimensional parameter data by at least rotating the n-dimensional parameter data to increase the spatial separation in the dimension having the overlap;
real-time classifying said n-dimensional parameter data of each of said individual particles into one of said at least two populations using said rotated n-dimensional parameter data; and
discriminate between said individual particles based upon said real-time classification.
2. The flow cytometer of claim 1 , wherein the second detector comprises a side detector.
3. The flow cytometer of claim 1 , wherein the one or more processors having computer readable memory further comprises instructions written thereon for simultaneously processing said n-dimensional parameter data to mathematically achieve numerical results of said rotational alteration in addition to a scaled alteration and a translation alteration.
4. The flow cytometer of claim 1 , wherein the one or more processors having computer readable memory further comprises instructions written thereon for generating a graphical representation of said at least two populations of said n-dimensional parameter data.
5. The flow cytometer of claim 4 , wherein said graphical representation of said at least two populations of said n-dimensional parameter data comprises an n-parameter data plot in a Cartesian coordinate system.
6. The flow cytometer of claim 1 , wherein said particles comprise sperm and wherein at least one of the two populations comprises an X-bearing sperm population or a Y-bearing sperm population.