Method and system for determining ideal gain of a detector - Patents.com

Abstract

A method is provided for determining an ideal gain for a detector in an optical detection system of a flow cytometer. The method of interest includes illuminating a flow stream with light from a light source, incrementally increasing the gain of the detector such that the detector collects light from the flow stream at each of a plurality of successively increasing gains, obtaining a baseline noise level from the detector at each of the plurality of successively increasing gains, calculating a limit of detection (LoD) for each of the plurality of successively increasing gains, and evaluating the calculated LoDs to determine the ideal gain. Systems and computer readable storage media for carrying out the invention are further provided.

Description

[Background technology]

[0001] Characterization of analytes in biological fluids has become an important part of biological research, medical diagnosis, and the evaluation of a patient's overall health and wellness. Detecting analytes in biological fluids, such as human blood or blood-derived products, can provide results that may be involved in determining treatment protocols for patients with various medical conditions.

[0002] Flow cytometry is a technique used to characterize and often sort biological material, such as cells in a blood sample or particles of interest in another type of biological or chemical sample. A flow cytometer typically includes a sample reservoir for receiving a fluid sample, such as a blood sample, and a sheath reservoir containing a sheath fluid. The flow cytometer carries particles (including cells) in the fluid sample as a cell stream to a flow cell, while further directing the sheath fluid to the flow cell. To characterize the components in the flow stream, light is illuminated into the flow stream. Changes in the biological material in the flow stream, such as morphology or the presence of fluorescent labels, may change the light observed, and these changes allow for characterization and separation. To characterize the components in the flow stream, light must be directed into the flow stream and collected. The light source in the flow cytometer can be a variety of light sources and may include one or more broad spectrum lamps, light emitting diodes, and single wavelength lasers. The light source is aligned with the flow stream, and optical responses from the illuminated particles are collected and quantified.

[0003] A flow cytometer includes a light detection system, which consists of optics, detectors, and electronics that allow for efficient detection of optical signals and conversion of the optical signals into corresponding electrical signals. The electronic signals are processed to obtain parameters that the user can utilize to perform the desired analysis. Flow cytometers include different types of photodetectors to detect the signals. When an optical signal (from a sample being analyzed in the flow cytometer) enters the photodetector, an electrical signal proportional to the optical signal is generated at the output of the photodetector. The gain of the photodetector is determined from the ratio of the output signal to the input signal. The gain of the photodetector can be used to control the operating range of detection by the photodetector, for example to ensure with a high degree of confidence that the fluorescence of the sample occurs within the operating range of the photodetector. Typically, the gain of the photodetector is positively correlated with the voltage so that it can be controlled by modulating the voltage applied to the photodetector. However, this correlation is complicated by a number of parameters, including the type of photodetector, the wavelength of the incident light, and the temperature.

[0004] Parameters measured using a flow cytometer typically include light at the excitation wavelength that is scattered by the particles at narrow angles primarily in the forward direction, termed forward scatter (FSC), excitation light that is scattered by the particles in a direction perpendicular to the excitation laser, termed side scatter (SSC), and light emitted by fluorescent molecules in one or more detectors that measure signals across a range of spectral wavelengths, or light emitted by fluorescent dyes that are primarily detected at that particular detector or array of detectors. Different cell types can be distinguished by their light scattering properties and fluorescent emission by labeling different cellular proteins or other components with fluorochrome-labeled antibodies or other fluorescent probes.

[0005] The flow cytometer may further comprise means for recording the measurement data and for analyzing the measurement data. For example, data storage and analysis may be performed using a computer connected to the detection electronics. For example, the data may be stored in a table format, with each row corresponding to the data of one particle and the columns corresponding to each of the measured features. The use of a standard file format, such as the "FCS" file format, for storing data from the particle analyzer facilitates analysis of the data using another program and / or machine. Using current analysis methods, the data is typically displayed in a one-dimensional histogram or two-dimensional (2D) plot for ease of visualization, although other methods may be used to visualize multidimensional data.

[0006] A common goal of flow cytometry analysis is to classify different populations of flow cytometer data in association with one or more different parameters. This classification is influenced by how well the different populations of flow cytometer data are separated. The degree of separation between two populations is determined by the difference in the mean or median of the two populations and the spread of the two populations. Although the difference in the mean between the populations of flow cytometer data received from a stained sample is already determined, the user can achieve better separation between the different populations by adjusting the gain of each detector to reduce the population spread. Summary of the Invention [Problem to be solved by the invention]

[0007] Conventional techniques for determining detector gain often involve a voltration process (or "voltage titration"). Voltration generally involves analyzing single-stained fluorescent beads or stained cells at a series of different voltage settings. The resulting flow cytometer data may then be plotted against the different voltages. This method may be used to separate the fluorescent signal from background noise and autofluorescence. A further conventional technique uses broad-spectrum fluorescent beads instead of a common sample. In general, it is assumed that the gain determined to be optimal for broad-spectrum beads will work for most samples, or at least provide a suitable starting gain that may be adjusted later. However, for bead techniques, a voltration process is still required for instruments with different optical configurations and when there are large differences between samples. Previous techniques for determining detector gain can be found, for example, in Maecker HT and Trotter J (2006) Cytometry A 69:1037-1042, which is incorporated herein in its entirety by reference.

[0008] The inventors have recognized that conventional approaches to setting gain, while effective in some cases, are often time-consuming and burdensome to the flow cytometry practitioner. In particular, the inventors have determined that a significant challenge in determining optimal gain is that the gain is sample-dependent, since the optimal gain depends on the optical background of the sample fluid, which may vary depending on the dyes in the sample and the particular staining / cleaning protocol employed. Thus, methods and systems for determining gain that take sample-specific information into account and reduce fluorescent dye spread are desirable. Embodiments of the present invention fulfill this need. [Means for solving the problem]

[0009] Aspects of the invention include methods for determining an ideal gain for a detector in an optical detection system of a flow cytometer. The methods of interest include illuminating a flow stream (e.g., containing a buffer, water, particles, or combinations thereof) with light from a light source, incrementally increasing the gain of the detector such that the detector collects light from the flow stream at each of a plurality of successively increasing gains, obtaining a baseline noise level from the detector at each of the plurality of successively increasing gains, calculating a limit of detection (LoD) for each of the plurality of successively increasing gains, and evaluating the calculated LoDs to determine an ideal gain. The gain may be calculated for any convenient detector or set of detectors. Detectors of interest include, for example, avalanche photodiodes (APDs), photomultiplier tubes (PMTs), photodiodes (PDs), and silicon photomultiplier tubes (SiPMs). The LoDs described herein are calculated based on the gain and the baseline noise level. For example, in some cases, the LoD calculation includes generating a ratio between the gain and the baseline noise level. In some cases, the LoD calculation further includes taking the inverse of the ratio between the gain and the baseline noise level. In an embodiment, when evaluating the calculated LoD, a LoD curve is generated that includes the calculated LoD for each of a plurality of successively increasing gains, e.g., the LoD curve is evaluated for the presence of an inflection point. In a variant, when evaluating the calculated LoD, an inflection point of the LoD curve and a gain within the plurality of successively increasing gains that is associated with the LoD at the inflection point are identified. The method may further determine that the gain within the plurality of successively increasing gains that is associated with the LoD at the inflection point is an ideal gain.

[0010] In some cases, the methods of interest evaluate flow cytometer data associated with a plurality of different particle populations to determine an ideal gain. In such cases, the plurality of particle populations includes a first particle population that is negative with respect to a particular parameter and a second particle population that is positive with respect to the same parameter. In some embodiments, the methods may obtain a first signal magnitude and a second signal magnitude for each of the first particle population and the second particle population at each of a plurality of successively increasing gains. For example, in some embodiments, the first signal magnitude is estimated based on a baseline noise level obtained by the detector at each of the plurality of successively increasing gains. In further cases, the method estimates the second signal magnitude based on each of the plurality of successively increasing gains. Variations of the subject methods further include obtaining the first and / or second signal magnitudes from the detector. In some cases, the methods calculate a difference between the second signal magnitude and the first signal magnitude obtained at each of the plurality of successively increasing gains. The method may further include generating a linearity measure to assess how the difference between the magnitude of the second signal and the magnitude of the first signal increases with increasing gain of the detector, and identifying a point of non-linearity where the difference between the magnitude of the second signal and the magnitude of the first signal does not increase linearly with increasing gain of the detector. The method may then determine an ideal gain to be a gain lower than the gain associated with the point of non-linearity. After determining the ideal gain, embodiments of the method may terminate increasing the gain in steps.

[0011] In some cases, the method further includes setting an event rate by selecting a sensitivity at which the trigger sensor observes the presence of a particle and generates a trigger signal. In such a case, the method may set a gain for the trigger sensor. The trigger sensor may be selected from, for example, a forward scatter sensor and an axial light loss (ALL) channel sensor. Embodiments of the method further include calculating a trigger window based on the trigger signal and obtaining a baseline noise level at a time outside the trigger window. The trigger window of interest provides a time at which a particle is expected to pass through the detection zone of the detector.

[0012] Aspects of the invention further include systems (e.g., flow cytometers). Systems of interest include a flow cell configured to carry a flow stream (e.g., containing buffer, water, particles, or combinations thereof), a light source for illuminating the flow stream at an interrogation point, a detector configured to collect light from the flow stream, and a processor operatively connected to the detector. The processor of interest is configured to perform the subject methods to incrementally increase a gain of the detector such that the detector collects light from the flow stream at each of a plurality of successively increasing gains, obtain a baseline noise level from the detector at each of the plurality of successively increasing gains, calculate a LoD for each of the plurality of successively increasing gains, and evaluate the calculated LoD to determine an ideal gain.

[0013] Aspects of the invention further include a non-transitory computer readable storage medium having stored thereon instructions for determining an ideal gain for a detector in an optical detection system of a flow cytometer, the instructions including incrementally increasing a gain for the detector such that the detector collects light from particles in a flow stream (e.g., including buffer, water, particles, or combinations thereof) at each of a plurality of successively increasing gains, obtaining a baseline noise level from the detector at each of the plurality of successively increasing gains, calculating a LoD for each of the plurality of successively increasing gains, and evaluating the calculated LoDs to determine the ideal gain. [Brief description of the drawings]

[0014] The invention may be best understood from the following detailed description when read in conjunction with the accompanying drawing figures, in which:

[0015] [Figure 1] 1 is a flowchart illustrating a workflow for determining ideal gains according to an embodiment. [Figure 2A] 1 is a graph showing the change in measured sensitivity versus detector gain for an avalanche photodiode; [Figure 2B] 1 is a graph showing the change in measured sensitivity versus voltage of a photomultiplier tube detector. [Figure 2C] 1 is a plot showing the change in measured sensitivity versus detector gain for an avalanche photodiode at various levels of optical background. [Diagram 3] FIG. 1 is a functional block diagram illustrating a flow cytometry system according to an embodiment. [Figure 4] FIG. 1 illustrates a control system according to an embodiment. [Figure 5A] FIG. 1 is a schematic diagram illustrating a particle sorting system according to an embodiment. [Figure 5B] FIG. 1 is a schematic diagram illustrating a particle sorting system according to an embodiment. [Figure 6] FIG. 1 is a block diagram illustrating a computing system according to an embodiment. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0016] A method is provided for determining an ideal gain for a detector in an optical detection system of a flow cytometer. The method of interest includes illuminating a flow stream with light from a light source, incrementally increasing the gain of the detector such that the detector collects light from the flow stream at each of a plurality of successively increasing gains, obtaining a baseline noise level from the detector at each of the plurality of successively increasing gains, calculating a limit of detection (LoD) for each of the plurality of successively increasing gains, and evaluating the calculated LoDs to determine the ideal gain. Systems and computer readable storage media for carrying out the invention are further provided.

[0017] Before the present invention is described in more detail, it should be understood that the invention is not limited to the particular embodiments described, as such may, of course, vary. The scope of the present invention will be limited only by the appended claims, and it should be further understood that the terminology used herein is for the purpose of describing particular embodiments only, and is not intended to be limiting.

[0018] When a range of values ​​is given, it is understood that each intervening value between the upper and lower limits of that range, to one-tenth of the unit of the lower limit unless the context clearly indicates otherwise, and any other stated or intervening value in that stated range, is encompassed within the invention. The upper and lower limits of these smaller ranges may be independently included in the smaller ranges and are further encompassed within the invention, subject to any specifically excluded limit in the stated range. Where the stated range includes one or both of the limits, ranges excluding either or both of those included limits are also encompassed within the invention.

[0019] In this specification, a range is provided with the term "about" before the numerical values. The term "about" is used herein to literally support the exact number that it precedes, as well as a number that is close to or approximately the number that it precedes. When determining whether a number is close to or approximately a specifically stated number, the unstated number that is close or approximately may be a number that, in the context in which the specifically stated number is presented, provides a substantial equivalent to the specifically stated number.

[0020] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. Although any methods and materials similar or equivalent to those described herein can also be used in the practice or testing of the present invention, representative and illustrative methods and materials are described.

[0021] All publications and patents cited herein are incorporated by reference as if each individual publication or patent was specifically and individually indicated to be incorporated by reference, and are incorporated by reference herein to disclose and describe the methods and / or materials in connection with which the publications are cited. The citation of any publication is for its disclosure prior to the filing date and should not be construed as an admission that the present invention is not entitled to antedate such publication by virtue of prior invention. Further, the dates of publication provided may be different from the actual publication dates which may need to be independently confirmed.

[0022] It should be noted that, as used in this specification and the appended claims, the singular forms "a," "an," and "the" include plural referents unless the context clearly dictates otherwise. It should be further noted that the claims may be drafted to exclude any optional element. As such, this statement is intended to serve as a prelude to the use of exclusive terminology, such as "solely," "only," or the use of a "negative" limitation in relation to the recitation of claim elements.

[0023] As will be apparent to one of ordinary skill in the art upon reading this disclosure, each of the individual embodiments described and illustrated herein comprises separate components and features which may be readily separated from, or combined with, any of the features of the other multiple embodiments without departing from the scope or spirit of the invention. Any recited method may be carried out in the order of events recited or in any other order which is logically possible.

[0024] Although the systems and methods have been described or will be described for grammatical fluidity with functional descriptions, it should be clearly understood that the claims, unless expressly recited under 35 U.S.C. ...

[0025] How to determine the ideal gain of a detector As discussed above, aspects of the invention include a method for determining an ideal gain for a detector in an optical detection system of a flow cytometer. The method of interest includes illuminating particles in a flow stream with light from a light source, incrementally increasing a gain of the detector such that the detector collects light from the flow stream at each of a plurality of successively increasing gains, obtaining a baseline noise level from the detector at each of the plurality of successively increasing gains, calculating a limit of detection (LoD) for each of the plurality of successively increasing gains, and evaluating the calculated LoDs to determine the ideal gain.

[0026] "Ideal Gain" refers to a gain that optimizes the signal-to-noise ratio (SNR) of a given detector. The ideal target gain is determined using the relative magnitudes of gain-dependent and gain-independent noise. "Gain-dependent" noise means noise that has a magnitude proportional to the magnitude of the gain. An example of gain-dependent noise is optical background noise. "Gain-independent" noise means noise that does not change with the magnitude of the gain. In general, the gain should be set such that the gain-independent noise is negligible compared to the magnitude of the gain-dependent noise. Beyond this point, the SNR does not improve because the noise increases with gain at least as rapidly as the signal. Thus, in an embodiment, the ideal gain can be determined by tracking how the SNR varies with gain and maximizing the SNR (e.g., by a robust peak-finding algorithm). To this end, aspects of the method obtain or provide estimates of the signal magnitude and noise magnitude. Since the signal is proportional to the gain, the gain itself can be used to represent the signal magnitude. Therefore, in a variant of the invention, the gain is used instead of the signal magnitude. Additionally, in embodiments of the method, baseline noise is used instead of the noise of the darkest population of flow cytometer data. In some embodiments, the subject method increases the signal-to-noise ratio of the optical detection system, for example, increases the signal-to-noise ratio of the optical detection system by 5% or more, for example, 10% or more, for example, 25% or more, for example, 50% or more, for example, 75% or more, for example, 90% or more, for example, 99% or more, compared to a suitable control. In some cases, the subject method increases the signal-to-noise ratio by 2-fold or more, for example, 3-fold or more, for example, 4-fold or more, for example, 5-fold or more, for example, 10-fold or more, compared to a suitable control. In some embodiments, the method of the present disclosure is sufficient to expand the range of detection and quantification of intensity by 2-fold or more, for example, 3-fold or more, for example, 5-fold or more, for example, 10-fold or more, for example, 25-fold or more, for example, 50-fold or more, for example, 100-fold or more, compared to a suitable control.

[0027] In the present invention, we determine an ideal gain that optimizes data quality in raw space (i.e., detector space) with a number of dimensions equal to the number of detectors in the instrument, but there is also a strong correlation between the SNR of the detector measurements and the spread of fluorophore abundance in a "correction space" or "unmixing space" with a number of dimensions equal to the number of fluorochromes in the sample. Correction or unmixing data is generated by mathematical processing of fluorescence correction (for conventional cytometers) or spectral unmixing (for full spectrum cytometers). Methods of spectral mixing include, for example, weighted least squares (WLS)-based spectral unmixing and ordinary least squares (OLS)-based spectral unmixing, as described, for example, in US Patent Application Publication No. 2020 / 0302606, the disclosure of which is incorporated herein by reference. In particular, in WLS-based spectral unmixing, minimizing the detector SNR minimizes the spread of fluorophores. When using the OLS algorithm for unmixing, the heteroscedasticity of the detector measurements violates the OLS requirement that the measurements be homoscedastic, thus preventing a direct proportional relationship between the detector SNR and the fluorophore spread. However, it is generally true that the SNR of the upstream measurements should be within a suitable range to ensure the quality of the downstream data. Thus, implementing embodiments of the present method will reduce and / or minimize the fluorophore spread.

[0028] In some cases, the methods of interest are sample specific. In other words, a set of ideal gains is determined for a given particle sample. The ideal gains may then be associated with that particle sample, for example in the form of a tube target value (TTV). The TTVs are associated with the voltage of each detector, and thus with the brightness of the positive population for each fluorescence parameter. In other words, the ideal gains may be applied to the detectors of the instrument such that when relevant samples having TTVs generated as described herein are analyzed in the flow stream of the instrument from which those TTVs were obtained, the SNR is improved and / or fluorophore spreading is reduced.

[0029] As described above, the method of interest involves irradiating particles in a flow stream with light from a light source. By "particle" is meant any particulate matter that may be carried in the flow stream. Particles of interest include, but are not limited to, cells, beads, polypeptides, polynucleotides, combinations thereof, and the like. Particles of interest may have any suitable size, and in some embodiments, are in the range of less than 1 μm to 20 μm in diameter. As used herein, "flow stream" is referred to in the conventional sense to refer to the flow of sheath fluid in which the particles are carried through the flow cell. In some embodiments, the particles are carried in the core stream, i.e., the portion of the flow stream in which the particles are carried in a single file. The diameter of the core stream may be adjusted in proportion to the pressure applied to the particles as they are injected into the sheath fluid flow. The flow rate of the sheath fluid remains constant. In this manner, the particles are injected into the sheath fluid and hydrodynamically focused such that a laminar flow is created to cause the particles to travel along the same axis at approximately the same speed. The flow stream may include a liquid sample injected from a sample tube. In some embodiments, the flow stream includes a buffer. In some aspects, the flow stream comprises water. In some embodiments, the flow stream may comprise a narrow, rapidly flowing liquid stream arranged such that linearly separated particles carried within the stream are in-line and separated from one another. In alternative embodiments, the flow stream does not comprise particles and comprises only a sheath fluid (e.g., buffer, water).

[0030] In some cases, the method conveys particles through a flow cell. "Flow cell" is used herein in a conventional sense to refer to a component that includes a flow path having a liquid flow stream for conveying particles within a sheath fluid. In embodiments, flow cells of interest include cuvettes. Cuvettes of interest include containers with passageways therethrough. The flow stream may include a liquid sample injected from a sample tube. Flow cells of interest include a flow path accessible to light. In some cases, the flow cell includes a transparent material (e.g., quartz) that allows the passage of light. Any convenient flow cell that conveys a fluid sample to a sample interrogation region may be used as the flow cell described herein, and in some embodiments, the flow cell is a cylindrical flow cell, a frustoconical flow cell, or a flow cell that includes a proximal cylindrical portion defining a longitudinal axis and a distal frustoconical portion terminating in a flat surface having an orifice perpendicular to the longitudinal axis.

[0031] In carrying out the methods of certain embodiments, a sample (e.g., in a flow stream of a flow cytometer) is illuminated with light from a light source. Any convenient light source may be used. In some cases, the methods illuminate the flow cell using a laser. In some embodiments, the methods illuminate the flow cell using multiple light sources (e.g., lasers). In some embodiments, the laser may be any convenient laser, such as a continuous wave laser. For example, the laser may be a diode laser, such as an ultraviolet diode laser, a visible diode laser, and a near infrared diode laser. In other embodiments, the laser may be a helium neon (HeNe) laser. In some cases, the laser is a gas laser, such as a helium neon laser, an argon laser, a krypton laser, a xenon laser, a nitrogen laser, a CO2 laser, a CO laser, an argon fluorine (ArF) excimer laser, a krypton fluorine (KrF) excimer laser, a xenon chlorine (XeCl) excimer laser, or a xenon fluorine (XeF) excimer laser, or a combination thereof. In other cases, lasers for carrying out the subject methods include dye lasers, such as stilbene lasers, coumarin lasers, or rhodamine lasers. In still other cases, lasers of interest include metal vapor lasers, such as helium-cadmium (HeCd) lasers, helium-mercury (HeHg) lasers, helium-selenium (HeSe) lasers, helium-silver (HeAg) lasers, strontium lasers, neon-copper (NeCu) lasers, copper lasers, or gold lasers, and combinations thereof. In still other cases, lasers for carrying out the subject methods include solid-state lasers, such as ruby ​​lasers, Nd:YAG lasers, NdCrYAG lasers, Er:YAG lasers, Nd:YLF lasers, Nd:YVO4 lasers, Nd:YCa4O(BO3)3 lasers, Nd:YCOB lasers, titanium sapphire lasers, thulium YAG lasers, ytterbium YAG lasers, Yb2O3 lasers, or cerium-doped lasers, and combinations thereof.

[0032] In some embodiments, the method uses a continuous wave light source to illuminate the particles in the flow stream, e.g., the light source provides an uninterrupted light flux and maintains illumination of the particles in the flow stream with little or no undesired changes in light intensity. In some embodiments, the continuous light source provides non-pulsed or non-stroboscopic illumination. In some embodiments, the continuous light source provides a substantially constant luminous intensity. For example, the method may illuminate the particles in the flow stream using a continuous light source that provides a luminous intensity during a time interval of illumination that varies by 10% or less, such as 9% or less, such as 8% or less, such as 7% or less, such as 6% or less, such as 5% or less, such as 4% or less, such as 3% or less, such as 2% or less, such as 1% or less, such as 0.5% or less, such as 0.1% or less, such as 0.01% or less, such as 0.001% or less, such as 0.0001% or less, such as 0.00001% or less, such as 0.000001% or less. The intensity of the light output may be measured by any convenient protocol, including, but not limited to, scanning slit profilers, charge coupled devices (CCDs, e.g., intensified charge coupled devices (ICCDs)), position sensors, power sensors (e.g., thermopile power sensors), optical power sensors, energy meters, digital laser photometers, laser diode detectors, among other types of photodetectors.

[0033] In other embodiments, the method uses a pulsed light source to illuminate particles propagating in the flow stream, e.g., light is emitted at predetermined time intervals, each time interval having a predetermined illumination duration (i.e., pulse width). In an embodiment, the method uses a pulsed light source to illuminate particles in each interrogation region of the flow stream with periodic flashes of light. The pulsed light source illuminates particles in each interrogation region of the flow stream with periodic flashes of light. For example, the frequency of each light pulse may be 0.0001 kHz or more, e.g., 0.0005 kHz or more, e.g., 0.001 kHz or more, e.g., 0.005 kHz or more, e.g., 0.01 kHz or more, e.g., 0.05 kHz or more, e.g., 0.1 kHz or more, e.g., 0.5 kHz or more, e.g., 1 kHz or more, e.g., 2.5 kHz or more, e.g., 5 kHz or more, e.g., 10 kHz or more, e.g., 25 kHz or more, e.g., 50 kHz or more, e.g., 100 kHz or more. In some cases, the frequency of the pulsed irradiation by the light source is in the range of 0.00001 kHz to 1000 kHz, such as 0.00005 kHz to 900 kHz, for example 0.0001 kHz to 800 kHz, for example 0.0005 kHz to 700 kHz, for example 0.001 kHz to 600 kHz, for example 0.005 kHz to 500 kHz, for example 0.01 kHz to 400 kHz, for example 0.05 kHz to 300 kHz, for example 0.1 kHz to 200 kHz, for example 1 kHz to 100 kHz. The duration of light illumination of each light pulse (i.e. pulse width) may vary and may be 0.000001 milliseconds or more, such as 0.000005 milliseconds or more, for example 0.00001 milliseconds or more, such as 0.00005 milliseconds or more, for example 0.0001 milliseconds or more, such as 0.0005 milliseconds or more, for example 0.001 milliseconds or more, such as 0.005 milliseconds or more, for example 0.01 milliseconds or more, such as 0.05 milliseconds or more, for example 0.1 milliseconds or more, such as 0.5 milliseconds or more, for example 1 millisecond or more, such as 2 milliseconds or more, for example 3 milliseconds or more, such as 4 milliseconds or more, for example 5 milliseconds or more, such as 10 milliseconds or more, for example 25 milliseconds or more, such as 50 milliseconds or more, for example 100 milliseconds or more, such as 500 milliseconds or more.For example, the duration of light irradiation may be within a range of 0.000001 milliseconds to 1000 milliseconds, for example, 0.000005 milliseconds to 950 milliseconds, for example, 0.00001 milliseconds to 900 milliseconds, for example, 0.00005 milliseconds to 850 milliseconds, for example, 0.0001 milliseconds to 800 milliseconds, for example, 0.0005 milliseconds to 750 milliseconds, for example, 0.001 milliseconds to 700 milliseconds, for example, 0.005 milliseconds to 650 milliseconds, for example, 0.01 milliseconds to 600 milliseconds, for example, 0.05 milliseconds to 550 milliseconds, for example, 0.1 milliseconds to 500 milliseconds, for example, 0.5 milliseconds to 450 milliseconds, for example, 1 millisecond to 400 milliseconds, for example, 5 milliseconds to 350 milliseconds, for example, 10 milliseconds to 300 milliseconds.

[0034] In some embodiments, the light source outputs a particular wavelength, e.g., between 200 nm and 1500 nm, e.g., between 250 nm and 1250 nm, e.g., between 300 nm and 1000 nm, e.g., between 350 nm and 900 nm, e.g., between 400 nm and 800 nm. In some embodiments, the continuous wave light source emits light having a wavelength of 365 nm, 385 nm, 405 nm, 460 nm, 490 nm, 525 nm, 550 nm, 580 nm, 635 nm, 660 nm, 740 nm, 770 nm, or 850 nm.

[0035] The flow stream may be illuminated by the light source from any suitable distance, for example from a distance of 0.001 mm or more, such as 0.005 mm or more, for example 0.01 mm or more, such as 0.05 mm or more, for example 0.1 mm or more, such as 0.5 mm or more, for example 1 mm or more, such as 5 mm or more, for example 10 mm or more, such as 25 mm or more, for example from a distance of 100 mm or more. In addition, illumination of the flow stream may be at any suitable angle, for example from an angle in the range of 10° to 90°, for example from 15° to 85°, for example from 20° to 80°, for example from 25° to 75°, for example from 30° to 60°, for example at an angle of 90°.

[0036] After illumination by a light source, the particles emit particle-modulated light. By "particle-modulated light" is meant light emitted by particles in a flow stream after the particles are illuminated with light from a light source. In some cases, the particle-modulated light is fluorescent light. Fluorescence may be emitted, for example, by particles having fluorescent dyes after the fluorescent dyes are illuminated with excitation wavelength light. In other cases, the particle-modulated light is side-scattered light. As described herein, side-scattered light refers to light that is refracted and reflected off the surface and internal structure of a particle. In still other cases, the particle-modulated light includes both fluorescent light and side-scattered light. In further embodiments, the particle-modulated light includes forward-scattered light (i.e., light that travels through or around the particle primarily in a forward direction).

[0037] The disclosed methods further include detecting light using a detector. A detector for implementing the subject methods may be any convenient photodetector, including, but not limited to, light sensors or photodetectors, such as active pixel sensors (APS), quad photodiodes, image sensors, charge-coupled devices (CCD), intensified charge-coupled devices (ICCD), light-emitting diodes, photon counters, bolometers, pyroelectric detectors, photoresistors, photocells, photodiodes (PD), photomultiplier tubes (PMT), phototransistors, quantum dot photoconductors or avalanche photodiodes (APD), silicon photomultiplier tubes (SiPM), and combinations thereof, among other photodetectors. In one embodiment, the photodetector is a photomultiplier tube, e.g., a 0.01 cm 2 ~10cm 2 , e.g. 0.05 cm 2 ~9cm 2 , e.g. 0.1 cm 2 ~8cm 2 , e.g. 0.5 cm 2 ~7cm 2 , e.g. 1 cm 2 ~5cm 2 In another embodiment, the photodetector is an avalanche photodiode, e.g., having an active detection surface area of ​​0.01 cm. 2 ~10cm 2, e.g. 0.05 cm 2 ~9cm 2 , e.g. 0.1 cm 2 ~8cm 2 , e.g. 0.5 cm 2 ~7cm 2 , e.g. 1 cm 2 ~5cm 2 In some cases, the light is detected by an array of photodetectors, e.g., by a photodetector array having 2 or more photodetectors, e.g., 3 or more photodetectors, e.g., 5 or more photodetectors, e.g., 10 or more photodetectors, e.g., 25 or more photodetectors, e.g., 50 or more photodetectors, e.g., 75 or more photodetectors, e.g., 100 or more photodetectors, e.g., 500 or more photodetectors, e.g., a photodetector array having 1000 or more photodetectors. In some cases, light is detected by an array of avalanche photodiodes, e.g., by a photodetector array having 2 or more avalanche photodiodes, for example 3 or more avalanche photodiodes, for example 5 or more avalanche photodiodes, for example 10 or more avalanche photodiodes, for example 25 or more avalanche photodiodes, for example 50 or more avalanche photodiodes, for example 75 or more avalanche photodiodes, for example 100 or more avalanche photodiodes, for example 500 or more avalanche photodiodes, e.g., by a photodetector array having 1000 or more avalanche photodiodes.

[0038] In embodiments of the present disclosure, light may be measured by a detector at one or more wavelengths, such as 2 or more wavelengths, for example 5 or more different wavelengths, such as 10 or more different wavelengths, for example 25 or more different wavelengths, such as 50 or more different wavelengths, for example 100 or more different wavelengths, such as 200 or more different wavelengths, for example 300 or more different wavelengths, for example light from particles in the flow stream may be measured at 400 or more different wavelengths.

[0039] In embodiments, the light may be measured continuously or at discrete intervals. In some cases, the detector of interest is configured to measure the light continuously. In other cases, the detector of interest is configured to measure at discrete intervals, such as every 0.001 milliseconds, every 0.01 milliseconds, every 0.1 milliseconds, every 1 millisecond, every 10 milliseconds, every 100 milliseconds, such as every 1000 milliseconds, or other intervals.

[0040] The light from the light source may be measured one or more times during each of the separate time intervals, such as two or more times, such as three or more times, such as five or more times, such as ten or more times, in an embodiment the light from the light source is measured by the detector two or more times, and the data is optionally averaged.

[0041] When obtaining a data signal from the detector, in some embodiments, the signal amplitude is calculated over a period of time. Optionally, when calculating the signal amplitude, the median signal amplitude is calculated. Optionally, the method further compares the calculated signal amplitude to the light intensity of the light source. In other cases, the method calculates the mean value of the signal amplitude. Optionally, the method further calculates the standard deviation of the signal amplitude. In other cases, the method calculates the variance and coefficient of variation (e.g., CV=standard deviation / mean value) of the signal amplitude. Based on one or more of the calculated signal amplitude and the comparison of the calculated signal amplitude to the light intensity of the light source, a parameter of the detector is calculated. For example, the method may determine parameters such as a minimum detection threshold, a maximum detection threshold, a detector sensitivity (i.e., the ratio of detector output to detector input), a dynamic range of the detector (the range of the detector signal from the minimum detection threshold to the maximum detection threshold), a signal-to-noise ratio of the detector, or the number of photoelectrons per unit output.

[0042] In some cases, the method sets the event rate by selecting the sensitivity at which the trigger sensor observes the presence of a particle and generates a trigger signal. In other words, a more sensitive trigger sensor will observe more particles and thus a higher event rate, while a less sensitive trigger sensor will observe relatively fewer particles and thus a relatively lower event rate. A "trigger sensor" is a light detector (e.g., a light detector as described above) configured to detect the presence of a particle in the flow stream. The trigger sensor may be any suitable sensor in the light detection system. For example, in some cases, the trigger sensor is a forward scatter light sensor (e.g., a sensor positioned to detect light passing through the sample primarily in a forward direction). In further cases, the trigger sensor is an axial light loss (ALL) channel sensor (e.g., a sensor positioned to measure the total amount of light lost from the light source at 0 degrees when a particle passes through the light). Thus, a "trigger signal" is associated with the time at which a given particle is detected in the flow stream. An "event rate" is typically measured in particles per unit time (e.g., seconds). The sensitivity at which the trigger sensor observes the presence of particles and generates a trigger signal may be selected to produce any convenient event rate. Event rates of interest may be, for example, in the range of 1 particle / sec to 500,000 particles / sec, such as 25 particles / sec to 100,000 particles / sec, such as 50 particles / sec to 50,000 particles / sec, such as 100 particles / sec to 15,000 particles / sec. In select embodiments, the event rate is less than 50,000 particles / sec, such as less than 15,000 particles / sec. In some cases, selecting the sensitivity at which the trigger sensor observes the presence of particles and generates a trigger signal involves setting the gain of the trigger sensor. The gain of the trigger sensor may be set, for example, by a user practicing the subject method to achieve a certain event rate.

[0043] As discussed above, aspects of the invention further include incrementally increasing the gain of the detector such that the detector collects light from the flow stream at each of a plurality of successively increasing gains. By "increasing" the gain, it is meant operating the detector at a first gain, increasing the first gain by a fixed amount, then operating the detector at a second gain, increasing the second gain by a fixed amount, then operating the detector at a third gain, and so on. This process may be referred to as "sweeping" the gain of the detector. By "increasing" the gain successively, it is meant that each gain in the series of gains has a higher magnitude than the gain immediately preceding it in the series of gains. In other words, the gain does not decrease over time. In some cases, the voltage applied to the detector is increased as the gain is incrementally increased. Depending on the type of detector (e.g. photomultiplier tube, avalanche photodiode, etc.), the applied voltage may be increased by 0.001% or more, such as 0.005% or more, such as 0.01% or more, such as 0.05% or more, such as 0.1% or more, such as 0.5% or more, such as 1% or more, such as 2% or more, such as 3% or more, such as 4% or more, such as 5% or more, such as 10% or more, such as 15% or more, such as 25% or more, such as in increments of 50% or more. In some cases, the applied voltage is increased by a factor of 2 or more, such as a factor of 3 or more, such as a factor of 5 or more, such as a factor of 10 or more. In some embodiments, the voltage applied to each photodetector in the subject method is increased by 0.0001 mV or more, such as 0.0005 mV or more, such as 0.001 mV or more, such as 0.005 mV or more, such as 0.01 mV or more, such as 0.05 mV or more, such as 0.1 mV or more, such as 0.5 mV or more, such as 1 mV or more, such as 2 mV or more, such as 3 mV or more, such as 4 mV or more, such as 5 mV or more, such as 10 mV or more, such as 25 mV or more, such as 50 mV or more, such as 75 mV or more, such as 100 mV or more, such as 250 mV or more, such as 500 mV or more, such as 750 mV or more, such as 1000 mV or more, such as 2500 mV or more, such as 5000 mV or more, such as 10000 mV or more. Each increment of the multiple successively increasing gains may be the same or different.In some embodiments, each increment of the multiple successively increasing gains has the same magnitude (i.e., the gains increase by the same amount each time), while in other embodiments the gains may increase by increments of different magnitudes.

[0044] The method of interest further includes obtaining a baseline noise level from the detector at each of a plurality of successively increasing gains. The term "baseline noise" is used herein in its conventional sense to refer to a baseline electronic signal from the detector (e.g., an electronic signal resulting from the operating electronics of the detector or optical components of the optical detection system). In some cases, the baseline noise includes electronic signals present in the optical detection system, such as electronic signals generated by the light source or other electronic subcomponents of the optical detection system. In other embodiments, the baseline noise includes electronic signals resulting from vibration or thermal effects from components of the system. In yet other embodiments, the baseline noise includes optical signals, such as light from an illumination source of the system (e.g., one or more lasers present in a flow cytometer). In some cases, the baseline noise results from a combination of zero-average electronic thermal noise (i.e., electrical background) and optical shot noise (i.e., optical background) resulting from, for example, ambient light and / or elastically scattered light. According to an embodiment of the present disclosure, the contribution to the background noise of each individual detector of the optical detection system is determined by obtaining a real-time sample-specific measurement of the baseline noise, for example, determining the contribution from time-varying parameters including, but not limited to, drift of the laser focus, drift of the laser alignment, time-dependent changes in the flow rate and flow profile of the flow stream, and increase in electronic noise due to thermal drift of detector components such as the transimpedance amplifier. In some cases, the baseline noise is related to the characteristics of the sample fluid (e.g., the amount of dye in the sample). The baseline noise may be calculated via any convenient protocol. For example, the baseline noise may be defined as the mean square error of the detector signal in the absence of particle-based signals or "events". In some embodiments, when obtaining the baseline noise, the moving mean square error of the generated data signal is calculated to determine the baseline noise of the optical detector. An exemplary protocol may be found in U.S. Patent Application No. 17 / 403105, the entire disclosure of which is incorporated herein by reference.

[0045] As described above, in some embodiments of the method, the event rate is set by selecting the sensitivity at which the trigger sensor observes the presence of particles and generates a trigger signal. In some cases, such embodiments may further calculate a trigger window based on the trigger signal. "Trigger window" refers to the time when a particle is expected to pass through a detection zone of a detector (e.g., a laser). "Detection zone" refers to the area of ​​the flow cell where the detector collects light. In a variation of the method, after calculating the trigger window, a baseline noise level is obtained at a time outside the trigger window. In other words, in embodiments of the method, if the baseline noise is related to a signal unrelated to particles, a baseline noise is obtained from the detector at a time when particles are not being evaluated by the detector (i.e., outside the trigger window). In some cases, the baseline noise is obtained from a field programmable gate array (FPGA) having a measurement block. In such cases, the FPGA continuously monitors the baseline noise outside the trigger window.

[0046] The disclosed method further calculates a limit of detection (LoD) for each of a plurality of successively increasing gains. As described herein, the LoD refers to the smallest measurable particle-modulated light signal that can be observed with sufficient confidence or statistical significance. In some cases, the LoD represents the smallest measurable particle-modulated light signal that corresponds to one standard deviation of the noise. The LoD of interest is calculated based on the gain and a baseline noise level (e.g., obtained as described above). For example, in some cases, a ratio of the gain to the baseline noise level is generated when calculating the LoD. Since the particle-modulated light signal is proportional to the gain, it is possible to use the gain itself to represent the magnitude of the signal. In addition, the baseline noise is a surrogate for the noise of the dimmest population of particles. This is strictly true when autofluorescence is low and marker expression is zero, and is also true enough for the purposes of the subject method even when these conditions are not met. Since the gain and baseline noise level are surrogates for signal and noise, respectively, a ratio of the gain to the baseline noise level is generated instead of the signal-to-noise ratio (SNR) of a given detector. Therefore, LoD and SNR can be considered as the same mathematical construct within the framework of the present invention. In some cases, the LoD is calculated by taking the inverse of the ratio between the gain and the baseline noise level.

[0047] In one variation, when evaluating the calculated LoD, a LoD curve is generated that includes the calculated LoD for each of a plurality of successively increasing gains. In other words, the calculated LoD at each gain is plotted as a function of gain. Optionally, after calculating each individual LoD, the LoD is added as a data point on the LoD curve. In an embodiment of the method, the LoD curve is further evaluated for the presence of an inflection point (i.e., a point where the concavity of the curve changes). If the LoD curve includes an inflection point, the method may identify the inflection point of the LoD curve and a gain within the plurality of successively increasing gains that is associated with the LoD at the inflection point. Optionally, the method determines that the gain within the plurality of successively increasing gains that is associated with the LoD at the inflection point is an ideal gain.

[0048] In further embodiments, the method evaluates flow cytometer data associated with multiple distinct particle populations to determine the ideal gain. As used herein, a "population" or "subpopulation" of an analyte, such as cells or other particles, generally refers to a group of analytes having characteristics (e.g., optical, impedance, or temporal characteristics) with respect to one or more measured fluorescence parameters such that the measured parameter data form a cluster in the data space. Thus, the populations are recognized as clusters in the data. Each data cluster is generally interpreted as corresponding to a population of a particular type of cell or analyte, although conversely, clusters corresponding to noise or background are typically observed. Clusters may be defined, for example, to subsets of dimensions with respect to a subset of measured fluorescence parameters (i.e., fluorochromes), which correspond to populations that differ only in a subset of measured parameters or features extracted from the sample measurements. In some cases, the multiple particle populations include a first particle population that is negative for a particular parameter and a second particle population that is positive for the same parameter. A particle population may be described as "positive" or "negative" based on whether the characteristic is observed with respect to a given characteristic or parameter.

[0049] In an embodiment of the method for evaluating flow cytometer data associated with a plurality of different particle populations to determine an ideal gain, the method may obtain a first signal magnitude and a second signal magnitude for each of the first and second particle populations at each of a plurality of successively increasing gains. The first signal magnitude and the second signal magnitude may be obtained from the sample by the detector, or may be substituted using other values ​​(e.g., baseline noise and / or gain, as desired). For example, in a variation of the method, the first signal magnitude is estimated based on a baseline noise level obtained by the detector at each of the plurality of successively increasing gains. Similarly, the method may estimate the second signal magnitude based on each of the plurality of successively increasing gains. In other cases, the method obtains the first and / or second signal magnitudes from the detector.

[0050] In some cases, the method generates a linearity measure (sometimes referred to as a "linearity range") to assess how the difference between the magnitude of the second signal and the magnitude of the first signal increases with increasing gain of the detector. Detector linearity is described, for example, in Bagwell et al. Cytometry: The Journal of the International Society for Analytical Cytology. 10:689-694 (1989), which is incorporated herein by reference in its entirety. The method according to these embodiments takes the difference between the magnitude of the first signal and the magnitude of the second signal acquired at each gain. In addition, a variation of the method identifies a point of non-linearity where the difference between the magnitude of the second signal and the magnitude of the first signal does not increase linearly with increasing gain of the detector. For example, if r2 is the magnitude of the second signal and r1 is the magnitude of the first signal, the difference between the magnitude of the second signal and the magnitude of the first signal at a particular iteration within a successively increasing gain i is (r2-r1). i In this example, the difference between the magnitude of the second signal and the magnitude of the first signal calculated for a first gain in the successively increasing gains is (r2-r1)1, the difference between the magnitude of the second signal and the magnitude of the first signal calculated for a second gain in the successively increasing gains is (r2-r1)2, and so on. n If r2-r1 deviates from the linear scale (i.e., the difference does not increase linearly with respect to the preceding iteration), then (r2-r1) n may be considered a point of non-linearity. Once a point of non-linearity is identified, a method according to an embodiment may determine the ideal gain to be a gain lower than the gain associated with the point of non-linearity. In some cases, the method determines the ideal gain to be a gain associated with the difference between the magnitude of the first signal and the magnitude of the second signal that is immediately lower than the gain associated with the point of non-linearity within a plurality of successively increasing gains. In the above example, (r2-r1) n Assuming that is the point of nonlinearity, (r2-r1) n-1may be determined to be the ideal gain. However, in an alternative variation, another gain lower than the gain associated with the point of non-linearity, e.g. (r2-r1) n-2 ,(r2-r1) n-3 etc. may be determined to be the ideal gain.

[0051] In some embodiments of the method, the ideal gain is both determined by evaluating the LoD curve for the presence of an inflection point, and the flow cytometer data associated with multiple different particle populations is evaluated. If the method includes a combination of protocols for determining the ideal gain, each protocol may be used in any suitable order. In some cases, the method evaluates the flow cytometer data associated with multiple different particle populations (at each iteration of increasing gain). For example, if a gain results in a point of non-linearity, the previous gain that brings the brightest population into the linear range may be selected as the ideal gain. If the same gain does not result in a point of non-linearity, the LoD curve may be analyzed for the presence of an inflection point. If an inflection point is detected, the gain may be determined to be the ideal gain. If the method does not detect an inflection point, the gain may be increased and the above steps may be repeated.

[0052] In some cases, in method embodiments, the method is performed for each detector in the optical detection system. The optical detection system may include any convenient number of detectors or detector arrays. For example, the number of detectors may be in the range of 1 to 100, such as 1 to 50, such as 1 to 25, such as 2 to 10. When ideal gains are determined for multiple detectors, the ideal gains may be determined simultaneously or at different times. In some cases, ideal gains associated with multiple different detectors are determined simultaneously. In other cases, ideal gains associated with multiple different detectors are determined at one or more different times (e.g., sequentially). In some cases, the method of interest terminates the incremental increase in gain after determining the ideal gain. In other words, after determining the ideal gain for a given detector by any of the methods described above, gain sweeps are no longer required and terminate.

[0053] FIG. 1 is a flow chart illustrating a workflow for determining an ideal gain according to an embodiment. In the embodiment of FIG. 1, the method begins in step 101 by loading a particle sample for analysis into a flow cytometer. In step 102, the event rate is set by selecting the sensitivity (e.g., by setting the detection threshold and gain) at which a trigger sensor (e.g., in the forward scatter channel or the light loss channel) observes the presence of a particle and generates a trigger signal. In FIG. 1, the gain for each fluorescence photodetector in the light detection system is determined simultaneously. Therefore, in step 103, the gain is increased for all of the fluorescence channels. In step 104, the LoD is calculated for the gain generated in step 103. In step 105, the signals collected for the particle population at the gain generated in step 103 are analyzed to determine whether the brightest population is outside the linear range (i.e., a point of non-linearity). If the brightest population is outside the linear range, the previous gain is determined to be the ideal gain in step 106. If the brightest population is not outside the linear range, the method proceeds to step 107 where it is determined whether the LoD calculated in step 104 reaches an inflection point. If an inflection point exists, the gain of step 103 is determined to be the ideal gain. If an inflection point does not exist, the method returns to step 103 where the gain is increased again.

[0054] As discussed above, the detector(s) that may be used in the subject method include, among others, photomultiplier tubes (PMTs) and / or avalanche photodiodes (APDs). When the detector(s) are PMTs, the excess noise is not dependent on gain. Therefore, the SNR will plateau when the gain dependent noise dominates, with the noise increasing with gain at the same rate as the signal. As a result, there may be an optimal gain range for the PMT. When a PMT is employed, the gain at the lower end of the optimal gain range to maximize the dynamic range is selected as the ideal gain. When the detector(s) are APDs, the noise is dependent on gain according to a power law relationship. Thus, the noise increases with gain faster than the signal. Thus, the LoD curve (i.e., the SNR curve) is convex with respect to the APD, and there is an optimal gain at which the SNR is maximized. As a result, when an APD is employed, the method determines that the gain at which the SNR is maximized is the ideal gain.

[0055] As described above, embodiments of the method use baseline noise instead of the noise of the dimmest population. In some cases, this approximation results in a higher gain than the true optimal gain. However, for PMT-based systems, such an approximation still results in optimal fluorophore spread. For APD-based systems, the fluorophore spread may be reduced. However, in such cases, this reduction may result in an overestimation of the optimal gain, and such an overestimation will have less impact on the LoD than an underestimation. For example, Figures 2A and 2B show the change in sensitivity measurements with detector gain or voltage for APD (Figure 2A) and PMT (Figure 2B). As shown in the LoD curve in Figure 2A, gain passing through a minimum will reduce the LoD. However, the optimum is shallow, and an overestimation of the optimal gain will have less impact on the LoD than an underestimation. As shown in Figure 2B, voltages higher than the inflection voltage will produce the same CV. FIG. 2B is taken from Maecker HT and Trotter J (2006) Cytometry A 69:1037-1042. FIG. 2C shows several exemplary LoD curves showing the change in LoD versus gain of APD at various levels of optical background. As shown in FIG. 2C, the optimal gain depends on the level of optical background present. In other words, the appropriate gain depends in part on the characteristics of the sample. The sample-specific method of the present invention allows for the determination of the ideal gain suitable for the optical background associated with each sample.

[0056] In some cases, the sample to be analyzed is a particle sample. In other words, the sample contains a plurality of particles (e.g., cells, beads, polynucleotides, proteins, etc.). In some cases, the sample to be analyzed in the present method is a biological sample. The term "biological sample" is used in the conventional sense to refer to a whole organism, a plant, a fungus, or a subset of tissues, cells, or components of an animal, where the subset of tissues, cells, or components of an animal may be found in blood, mucus, lymph, synovial fluid, cerebrospinal fluid, saliva, bronchoalveolar lavage fluid, amniotic fluid, amniotic cord blood, urine, vaginal fluid, and semen, as the case may be. Thus, "biological sample" refers to both a naturally occurring organism or a subset of its tissues, and homogenates, lysates, or extracts prepared from an organism or a subset of its tissues, including, but not limited to, plasma, serum, spinal fluid, lymph, skin sections, respiratory tract, gastrointestinal tract, cardiovascular, genitourinary tract, tears, saliva, milk, blood cells, tumors, and organs. The biological sample may be tissue from any type of organism, including both healthy and diseased tissue (e.g., cancerous, malignant, necrotic, etc.). In certain embodiments, the biological sample is a liquid sample, such as blood or a derivative thereof, such as plasma, tears, urine, semen, etc., and in some cases, the sample is a blood sample, including whole blood, such as blood obtained from a venipuncture or finger prick (which may or may not be combined with any reagents, such as preservatives, anticoagulants, etc., prior to assay).

[0057] In some embodiments, the sample source is a "mammal" or "mammalian," which terms are used broadly to describe organisms belonging to the class Mammalia, including the orders Carnivora (e.g., dogs and cats), Rodentia (e.g., mice, guinea pigs, and rats), and Primates (e.g., humans, chimpanzees, and monkeys). In some cases, the subject is a human. The method may be applied to samples obtained from human subjects of both genders and at any stage of development (i.e., neonate, infant, juvenile, adolescent, adult), and in some embodiments, the human subject is a juvenile, adolescent, or adult. While the present invention may be applied to samples from human subjects, it should be understood that the method may also be performed on samples from other animal subjects (i.e., "non-human subjects"), including, but not limited to, birds, mice, rats, dogs, cats, livestock, and horses.

[0058] Cells of interest may be subject to characterization according to various parameters, such as phenotypic characteristics identified by attaching specific fluorescent labels to the cells of interest. In some embodiments, the system is configured to deflect analysis droplets determined to contain target cells. A variety of cells may be characterized using the subject methods. Target cells of interest include, but are not limited to, stem cells, T cells, dendritic cells, B cells, granulocytes, leukemia cells, lymphoma cells, viral cells (e.g., HIV cells), NK cells, macrophages, monocytes, fibroblasts, epithelial cells, endothelial cells, and red blood cells. Target cells of interest include cells bearing convenient cell surface markers or antigens that may be taken up or labeled by convenient affinity agents or conjugates thereof. For example, the target cell may comprise cell surface antigens such as CD11b, CD123, CD14, CD15, CD16, CD19, CD193, CD2, CD25, CD27, CD3, CD335, CD36, CD4, CD43, CD45RO, CD56, CD61, CD7, CD8, CD34, CD1c, CD23, CD304, CD235a, T cell receptor alpha / beta, T cell receptor gamma / delta, CD253, CD95, CD20, CD105, CD117, CD120b, Notch4, Lgr5 (N-terminus), SSEA-3, TRA-1-60 antigen, disialoganglioside GD2, and CD71. In some embodiments, the target cells are selected from HIV-containing cells, Treg cells, antigen-specific T cell populations, tumor cells, or hematopoietic progenitor cells (CD34+) from whole blood, bone marrow, or umbilical cord blood.

[0059] The featured methods may further use the particles in research, clinical trials, or therapy. In some embodiments, the subject methods obtain individual cells prepared from a target fluid or tissue biological sample. For example, the subject methods obtain cells from a fluid or tissue sample used as a research or diagnostic specimen for diseases such as cancer. Similarly, the subject methods obtain cells from a fluid or tissue sample used for therapy. Cell therapy protocols are protocols in which viable cellular material, including, for example, cells and tissue, may be prepared and introduced into a subject as a therapeutic treatment. Conditions that may be treated by administration of flow cytometrically sorted samples include, but are not limited to, blood disorders, immune system disorders, organ damage, and the like.

[0060] A typical cell therapy protocol may include the steps of sample collection, cell isolation, genetic modification, culture, in vitro expansion, cell harvesting, sample volume reduction, sample washing, biopreservation, storage, and introduction of cells into a subject. The protocol may begin by collecting viable cells and tissue from a tissue source of the subject to generate a cell and / or tissue sample. The sample may be collected by any suitable procedure, including, for example, administering a cell mobilizing agent to the subject, drawing blood from the subject, removing bone marrow from the subject, etc. After the sample is collected, cell enrichment may be performed by multiple methods, including, for example, centrifugation-based methods, filter-based methods, elutriation, magnetic separation, fluorescence-activated cell sorting (FACS), etc. In some cases, the enriched cells may be genetically modified by any convenient method, for example, nuclease-mediated gene editing. The genetically modified cells may be cultured, activated, and expanded in vitro. In some cases, the cells are preserved, for example, cryopreserved, and stored for future use. When in use, the cells may be thawed and then administered to the patient, for example, the cells may be infused into the patient.

[0061] System for classifying flow cytometer data - Patents.com Aspects of the invention further include systems. Systems of interest include a flow cell configured to carry a flow stream, a light source for illuminating the flow stream at an interrogation point, a detector configured to collect light from the flow stream, and a processor operatively connected to the detector. The processor of interest is configured to incrementally increase a gain of the detector such that the detector collects light from the flow stream at each of a plurality of successively increasing gains, obtain a baseline noise level from the detector at each of the plurality of successively increasing gains, calculate a limit of detection (LoD) for each of the plurality of successively increasing gains, and evaluate the calculated LoD to determine an ideal gain. The systems described herein may be any particle analyzer configured to analyze particles in a flow stream. In some cases, the system includes a flow cytometer. In such cases, the flow cytometer is a multicolor flow cytometer. In other cases, the flow cytometer is a spectral flow cytometer.

[0062] In some cases, the subject processor operates with programmable logic, which may be implemented in hardware, software, firmware, or any combination thereof, for example, to determine an ideal gain. For example, when the programmable logic is implemented in software, the determination of the ideal gain may be at least partially accomplished by a computer readable data storage medium having program code including instructions configured, when executed, to incrementally increase a gain of the detector such that the detector collects light from the flow stream at each of a plurality of successively increasing gains, obtain a baseline noise level from the detector at each of the plurality of successively increasing gains, calculate a LoD for each of the plurality of successively increasing gains, and evaluate the calculated LoD to determine an ideal gain. For example, the program code may include instructions for generating a ratio between the gain and a baseline noise level, taking the inverse of the ratio between the gain and the baseline noise level, generating a LoD curve including the calculated LoD for each of the plurality of successively increasing gains, and evaluating the LoD curve for the presence of an inflection point. In an embodiment, the processor is configured to identify a gain within the plurality of successively increasing gains that is associated with the LoD at the inflection point. Additionally, the program code may include instructions for evaluating flow cytometer data associated with a plurality of different particle populations, for example a first particle population negative with respect to a particular parameter and a second particle population positive with respect to the same parameter, to determine an ideal gain. The processor may be further configured to obtain a first signal magnitude and a second signal magnitude for each of the first particle population and the second particle population, respectively, at each of a plurality of successively increasing gains, calculate a difference between the second signal magnitude and the first signal magnitude obtained at each of the plurality of successively increasing gains, generate a linearity measure to assess how the difference between the second signal magnitude and the first signal magnitude increases with increasing detector gain, and identify a point of non-linearity where the difference between the second signal magnitude and the first signal magnitude does not increase linearly with increasing detector gain.The processor may, in some cases, determine that a gain that is lower than the gain associated with the point of non-linearity is the ideal gain.

[0063] The programmable logic of interest may be implemented in any of a variety of devices, such as a specially programmed event processing computer, a wireless communication device, an integrated circuit device, etc. In some embodiments, the programmable logic may be executed by a specially programmed processor, which may include one or more processors, such as one or more digital signal processors (DSPs), configurable microprocessors, application specific integrated circuits (ASICs), field programmable gate arrays (FPGAs), or other equivalent integrated or discrete logic circuits. Combinations of computing devices, such as a combination of a DSP and a microprocessor, multiple microprocessors, one or more microprocessors in combination with a DSP core, or any other such configuration in at least partial data connectivity, may implement one or more of the features described herein.

[0064] In some cases, the system further comprises a display configured to output the ideal gain of the flow as determined by the processor. In some cases, the display outputs the ideal gain in the form of a TTV. A user may then view the flow cytometer data evaluated by the processor. Displays of interest may include, but are not limited to, monitors, tablet computers, smartphones, or other electronic devices configured to provide a graphical interface.

[0065] As described above, systems of interest include a flow cell. The term "flow cell" is used in its conventional sense to refer to a component, such as a cuvette, that includes a flow path having a liquid flow stream for carrying particles within a sheath fluid. A cuvette of interest includes a container with a passageway therethrough. The flow stream may include a liquid sample injected from a sample tube. A flow cell of interest includes a flow path accessible to light. In some cases, the flow cell includes a transparent material (e.g., quartz) that allows the passage of light. In some embodiments, the flow cell is a stream-in-air flow cell, where optical interrogation of particles occurs in free space. In some cases, the flow stream is configured to be illuminated with light from one or more light sources at an interrogation point. As described herein, "interrogation point" refers to an area in the flow stream where particles are illuminated by light from a light source, for example, for analysis. The size of the interrogation point may vary as desired. For example, if 0 μm represents the axial center of the light emitted by the light-related light source, the interrogation zone may be in the range of -100 μm to 100 μm, such as -50 μm to 50 μm, such as -25 μm to 40 μm, such as -15 μm to 30 μm. The flow stream in which the flow path is configured may comprise a liquid sample injected from a sample tube. In an embodiment, the flow stream may comprise a narrow, rapidly flowing liquid stream arranged such that linearly separated particles carried therein are in-line and separated from one another. After illuminating the particles in the flow cell, the particle-modulated light may be observed.

[0066] Any convenient flow cell that delivers the fluid sample to the sample interrogation region may be used, and in some embodiments the flow cell is a cylindrical flow cell, a frusto-conical flow cell, or a flow cell that includes a proximal cylindrical portion defining a longitudinal axis and a distal frusto-conical portion terminating in a flat surface having an orifice perpendicular to the longitudinal axis.

[0067] In some embodiments, the sample flow stream is emitted from an orifice at the distal end of the flow cell. Depending on the desired characteristics of the flow stream, the orifice of the flow cell may have any suitable shape, including but not limited to rectilinear cross-sectional shapes, e.g., square, rectangular, trapezoidal, triangular, hexagonal, curvilinear cross-sectional shapes, e.g., circular, oval, and irregular shapes, e.g., a parabolic bottom joined to a planar top. In some embodiments, the flow cell of interest has a circular orifice. The size of the nozzle orifice may vary, and in some embodiments may be in the range of 1 μm to 10,000 μm, e.g., 25 μm to 7,500 μm, e.g., 50 μm to 5,000 μm, e.g., 75 μm to 1,000 μm, e.g., 100 μm to 750 μm, e.g., 150 μm to 500 μm. In some embodiments, the nozzle orifice is 100 μm.

[0068] In some embodiments, the flow cell has a sample injection port configured to deliver a sample to the flow cell. The sample injection port may be an orifice in the wall of the internal chamber or a tube in the proximal end of the internal chamber. When the sample injection port is an orifice in the wall of the internal chamber, the orifice of the sample injection port may have any suitable shape, and cross-sectional shapes of interest include, but are not limited to, rectilinear cross-sectional shapes, e.g., square, rectangular, trapezoidal, triangular, hexagonal, curvilinear cross-sectional shapes, e.g., circular, oval, and irregular shapes, e.g., a parabolic bottom joined to a planar top. In some embodiments, the sample injection port has a circular orifice. The size of the orifice of the sample injection port may vary depending on the shape, and in some cases may have an opening within the range of 0.1 mm to 5.0 mm, for example, 0.2 mm to 3.0 mm, for example, 0.5 mm to 2.5 mm, for example, 0.75 mm to 2.25 mm, for example, 1 mm to 2 mm, for example, 1.25 mm to 1.75 mm, for example, an opening of 1.5 mm.

[0069] In some cases, the sample injection port is a tube provided at the proximal end of the internal chamber of the flow cell. For example, the sample injection port may be a tube that is aligned such that the orifice of the sample injection port is aligned with the orifice of the flow cell. When the sample injection port is a tube that is aligned with the orifice of the flow cell, the cross-sectional shape of the sample injection tube may be any suitable shape, cross-sectional shapes of interest include, but are not limited to, rectilinear cross-sectional shapes, e.g., square, rectangular, trapezoidal, triangular, hexagonal, curvilinear cross-sectional shapes, e.g., circular, oval, and irregular shapes, e.g., a parabolic bottom joined to a planar top. The orifice of the tube may vary depending on the shape, and in some cases may have an opening in the range of 0.1 mm to 5.0 mm, e.g., 0.2 mm to 3.0 mm, e.g., 0.5 mm to 2.5 mm, e.g., 0.75 mm to 2.25 mm, e.g., 1 mm to 2 mm, e.g., 1.25 mm to 1.75 mm, e.g., an opening of 1.5 mm. The shape of the tip of the sample injection port may be the same as or different from the cross-sectional shape of the sample injection tube. For example, the orifice of the sample injection port may have a bevel angle in the range of 1 to 10 degrees, for example, 2 to 9 degrees, for example, 3 to 8 degrees, for example, 4 to 7 degrees, for example, a bevel angle of 5 degrees.

[0070] In some embodiments, the flow cell further comprises a sheath fluid injection port configured to supply sheath fluid to the flow cell. In embodiments, the sheath fluid injection system is configured to supply a flow of sheath fluid, e.g., together with the sample, to the internal chamber of the flow cell to generate a laminated flow stream of sheath fluid surrounding the flow stream of the sample. The velocity of the sheath fluid delivered to the chamber of the flow cell may be between 25 μL / sec and 2500 μL / sec, e.g., between 50 μL / sec and 1000 μL / sec, e.g., between 75 μL / sec or more and 750 μL / sec, depending on the desired characteristics of the flow stream.

[0071] In some embodiments, the sheath fluid injection port is an orifice in the wall of the internal chamber. The orifice of the sheath fluid injection port may be of any suitable shape, with cross-sectional shapes of interest including, but not limited to, rectilinear cross-sectional shapes, such as square, rectangular, trapezoidal, triangular, hexagonal, curvilinear cross-sectional shapes, such as circular, oval, and irregular shapes, such as a parabolic bottom joined to a planar top. The size of the orifice of the sample injection port may vary depending on the shape, and may in some cases have an opening in the range of 0.1 mm to 5.0 mm, such as 0.2 mm to 3.0 mm, such as 0.5 mm to 2.5 mm, such as 0.75 mm to 2.25 mm, such as 1 mm to 2 mm, such as 1.25 mm to 1.75 mm, such as a 1.5 mm opening.

[0072] In some embodiments, the system further comprises a pump in fluid communication with the flow cell for propagating the flow stream through the flow cell. Any convenient fluid pumping protocol may be used to control the flow of the flow stream through the flow cell. In some cases, the system comprises a peristaltic pump, e.g., a peristaltic pump having a pulse damper. The pump of the subject system is configured to convey fluid through the flow cell at a suitable rate for multiphoton counting of light from the sample in the flow stream. For example, the system may comprise a pump configured to flow the sample through the flow cell at a rate within a range of 1 nL / min to 500 nL / min, e.g., 1 nL / min to 250 nL / min, e.g., 1 nL / min to 100 nL / min, e.g., 2 nL / min to 90 nL / min, e.g., 3 nL / min to 80 nL / min, e.g., 4 nL / min to 70 nL / min, e.g., 5 nL / min to 60 nL / min, e.g., 10 nL / min to 50 nL / min. In one embodiment, the flow rate of the flow stream is between 5 nL / min and 6 nL / min.

[0073] Aspects of the subject system further include a light source for illuminating the flow stream at the interrogation point. Any convenient light source, such as a laser, may be used. In embodiments, the laser may be any convenient laser, such as a continuous wave laser. For example, the laser may be a diode laser, such as an ultraviolet diode laser, a visible diode laser, and a near infrared diode laser. In other embodiments, the laser may be a helium neon (HeNe) laser. In some cases, the laser is a gas laser, such as a helium neon laser, an argon laser, a krypton laser, a xenon laser, a nitrogen laser, a CO2 laser, a CO2 laser, an argon fluorine (ArF) excimer laser, a krypton fluorine (KrF) excimer laser, a xenon chlorine (XeCl) excimer laser, or a xenon fluorine (XeF) excimer laser, or combinations thereof. In other cases, the flow cytometer of interest includes a dye laser, such as a stilbene laser, a coumarin laser, or a rhodamine laser. In still other cases, the lasers of interest include metal vapor lasers, such as helium-cadmium (HeCd), helium-mercury (HeHg), helium-selenium (HeSe), helium-silver (HeAg), strontium, neon-copper (NeCu), copper, or gold lasers, and combinations thereof. In still other cases, flow cytometers of interest include solid-state lasers, such as ruby, Nd:YAG, NdCrYAG, Er:YAG, Nd:YLF, Nd:YVO4, Nd:YCa4O(BO3)3, Nd:YCOB, titanium sapphire, thulium YAG, ytterbium YAG, Yb2O3, or cerium-doped lasers, and combinations thereof.

[0074] The laser light source according to an embodiment may further include one or more optical adjustment components. In an embodiment, the optical adjustment components are disposed between the light source and the flow cell and may include any device capable of changing the spatial width of the illumination or other characteristics of the illumination from the light source, such as the illumination direction, wavelength, beam width, beam intensity, and focus. The optical adjustment protocol may include any convenient device that adjusts one or more characteristics of the light source, including, but not limited to, lenses, mirrors, filters, optical fibers, wavelength separators, pinholes, slits, collimation protocols, and combinations thereof. In an embodiment, the flow cytometer of interest includes one or more focusing lenses. The focusing lens may be, in one example, a reduction lens. In yet another embodiment, the flow cytometer of interest includes optical fibers.

[0075] If the optical adjustment component is configured to move, it may be configured to move continuously or at discrete intervals, for example in increments of 0.01 μm or more, such as 0.05 μm or more, for example 0.1 μm or more, such as 0.5 μm or more, for example 1 μm or more, such as 10 μm or more, for example 100 μm or more, such as 500 μm or more, for example 1 mm or more, such as 5 mm or more, for example 10 mm or more, such as 25 mm or more.

[0076] Any movement protocol may be used to move the optical adjustment component structure, for example coupled to a movable support stage or directly coupled to a motor-driven translation stage, a lead screw translation assembly, a geared translation device, for example using stepper motors, servo motors, brushless electric motors, brushed DC motors, microstep drive motors, and high resolution stepper motors, among other motor types.

[0077] The light source may be positioned at any suitable distance from the flow cell, for example the light source and the flow cell are separated by 0.005 mm or more, such as 0.01 mm or more, for example 0.05 mm or more, such as 0.1 mm or more, for example 0.5 mm or more, such as 1 mm or more, for example 5 mm or more, such as 10 mm or more, for example 25 mm or more, such as 100 mm or more. In addition, the light source may be positioned at any suitable angle relative to the flow cell, for example at an angle in the range of 10 degrees to 90 degrees, for example 15 degrees to 85 degrees, such as 20 degrees to 80 degrees, for example 25 degrees to 75 degrees, for example 30 degrees to 60 degrees, for example at an angle of 90 degrees.

[0078] In some embodiments, the system includes a plurality of light sources. In some cases, the plurality of light sources includes a plurality of lasers, e.g., two or more lasers, e.g., three or more lasers, e.g., four or more lasers, e.g., five or more lasers, e.g., ten or more lasers, e.g., fifteen or more lasers, configured to provide laser light for separately irradiating the flow stream. Depending on the desired wavelength of light for irradiating the flow stream, each laser may have a different specific wavelength within the range of 200 nm to 1500 nm, e.g., 250 nm to 1250 nm, e.g., 300 nm to 1000 nm, e.g., 350 nm to 900 nm, e.g., 400 nm to 800 nm. In some embodiments, the lasers of interest may include one or more of a 405 nm laser, a 488 nm laser, a 561 nm laser, and a 635 nm laser.

[0079] Systems of interest may include one or more detectors for detecting particle modulated light intensity data. In some embodiments, the one or more particle modulated light detectors include one or more forward scattered light detectors configured to detect forward scattered light. For example, particle analyzers of interest may include one forward scattered light detector or multiple forward scattered light detectors, e.g., two or more, e.g., three or more, e.g., four or more, e.g., five or more forward scattered light detectors. In some embodiments, the particle analyzer includes one forward scattered light detector. In other embodiments, the particle analyzer includes two forward scattered light detectors.

[0080] Any convenient detector for detecting collected light may be used in the forward scattered light detectors described herein. Detectors of interest may include, but are not limited to, light sensors or photodetectors, such as active pixel sensors (APS), avalanche photodiodes, image sensors, charge-coupled devices (CCD), intensified charge-coupled devices (ICCD), light-emitting diodes, photon counters, bolometers, pyroelectric detectors, photoresistors, photocells, photodiodes, photomultiplier tubes (PMT), phototransistors, quantum dot photoconductors or quantum dot photodiodes, and combinations thereof, among other detectors. In some embodiments, the collected light is measured with a charge-coupled device (CCD), a semiconductor charge-coupled device (CCD), an active pixel sensor (APS), a complementary metal-oxide semiconductor (CMOS) image sensor, or an N-type metal-oxide semiconductor (NMOS) image sensor. In some embodiments, the detector is a photomultiplier tube, e.g., a 0.01 cm 2 ~10cm 2 , e.g. 0.05 cm 2 ~9 cm 2 , e.g. 0.1 cm 2 ~8 cm 2 , e.g. 0.5 cm 2 ~7 cm 2 , e.g. 1 cm 2 ~5 cm 2 The photomultiplier tube has an active detection surface area of ​​each region within the range of .

[0081] In embodiments, the forward scattered light detector is configured to measure light continuously or at discrete intervals. In some cases, the detector of interest is configured to measure the collected light continuously. In other cases, the detector of interest is configured to measure at discrete intervals, such as every 0.001 milliseconds, every 0.01 milliseconds, every 0.1 milliseconds, every 1 millisecond, every 10 milliseconds, every 100 milliseconds, such as every 1000 milliseconds, or other intervals.

[0082] In some cases, the system includes one or more side scattered light detectors for detecting side scattered wavelengths of light (i.e., light that is refracted and reflected off the surface and internal structure of the particle). In some embodiments, the particle analyzer includes one side scattered light detector. In other embodiments, the particle analyzer includes multiple side scattered light detectors, such as 2 or more, such as 3 or more, such as 4 or more, such as 5 or more side scattered light detectors.

[0083] Any convenient detector for detecting collected light may be used for the side scatter light detectors described herein. Detectors of interest may include, but are not limited to, light sensors or photodetectors, such as active pixel sensors (APS), avalanche photodiodes, image sensors, charge-coupled devices (CCD), intensified charge-coupled devices (ICCD), light-emitting diodes, photon counters, bolometers, pyroelectric detectors, photoresistors, photocells, photodiodes, photomultiplier tubes (PMT), phototransistors, quantum dot photoconductors or quantum dot photodiodes, and combinations thereof, among other detectors. In some embodiments, the collected light is measured with a charge-coupled device (CCD), a semiconductor charge-coupled device (CCD), an active pixel sensor (APS), a complementary metal-oxide semiconductor (CMOS) image sensor, or an N-type metal-oxide semiconductor (NMOS) image sensor. In some embodiments, the detector is a photomultiplier tube, e.g., a 0.01 cm 2 ~10cm 2 , e.g. 0.05 cm 2 ~9 cm 2 , e.g. 0.1 cm 2 ~8 cm 2 , e.g. 0.5 cm 2 ~7 cm 2 , e.g. 1 cm 2 ~5 cm 2 The photomultiplier tube has an active detection surface area of ​​each region within the range of .

[0084] In embodiments, the subject systems further comprise a fluorescence detector configured to detect light at one or more fluorescence wavelengths, hi other embodiments, the particle analyzer comprises a plurality of fluorescence detectors, e.g., 2 or more, e.g., 3 or more, e.g., 4 or more, 5 or more, 10 or more, 15 or more, e.g., 20 or more fluorescence detectors.

[0085] Any convenient detector for detecting collected light may be used in the fluorescence photodetectors described herein. Detectors of interest may include, but are not limited to, light sensors or photodetectors, such as active pixel sensors (APS), avalanche photodiodes, image sensors, charge-coupled devices (CCD), intensified charge-coupled devices (ICCD), light-emitting diodes, photon counters, bolometers, pyroelectric detectors, photoresistors, photocells, photodiodes, photomultiplier tubes (PMT), phototransistors, quantum dot photoconductors or quantum dot photodiodes, and combinations thereof, among other detectors. In some embodiments, the collected light is measured with a charge-coupled device (CCD), a semiconductor charge-coupled device (CCD), an active pixel sensor (APS), a complementary metal-oxide semiconductor (CMOS) image sensor, or an N-type metal-oxide semiconductor (NMOS) image sensor. In some embodiments, the detector is a photomultiplier tube, e.g., a 0.01 cm 2 ~10 cm 2 , e.g. 0.05 cm 2 ~9 cm 2 , e.g. 0.1 cm 2 ~8 cm 2 , e.g. 0.5 cm 2 ~7 cm 2 , e.g. 1 cm 2 ~5 cm 2 The photomultiplier tube has an active detection surface area of ​​each region within the range of .

[0086] When a particle analyzer of interest has multiple fluorescence detectors, each of the fluorescence detectors may be identical, or the collection of fluorescence detectors may be a combination of different types of detectors. For example, when a particle analyzer of interest has two fluorescence detectors, in some embodiments, the first fluorescence detector is a CCD type device and the second fluorescence detector (or image sensor) is a CMOS type device. In other embodiments, both the first and second fluorescence detectors are CCD type devices. In yet other embodiments, both the first and second fluorescence detectors are CMOS type devices. In yet other embodiments, the first fluorescence detector is a CCD type device and the second fluorescence detector is a photomultiplier tube (PMT). In yet other embodiments, the first fluorescence detector is a CMOS type device and the second fluorescence detector is a photomultiplier tube. In yet other embodiments, both the first and second fluorescence detectors are photomultiplier tubes.

[0087] In embodiments of the present disclosure, the fluorescent light detector of interest is configured to measure collected light at one or more wavelengths, e.g., two or more wavelengths, e.g., five or more different wavelengths, e.g., ten or more different wavelengths, e.g., twenty-five or more different wavelengths, e.g., fifty or more different wavelengths, e.g., one or more than one hundred different wavelengths, e.g., two or more than one hundred different wavelengths, e.g., two or more than one hundred different wavelengths, e.g., three or more than one hundred different wavelengths, e.g., four ...

[0088] In some embodiments, the fluorescent light detector of interest is configured to measure light collected over a range of wavelengths (e.g., 200 nm to 1000 nm). In certain embodiments, the detector of interest is configured to collect a spectrum of light over a range of wavelengths. For example, a particle analyzer may have one or more detectors configured to collect a spectrum of light over one or more of the wavelength ranges of 200 nm to 1000 nm. In yet other embodiments, the detector of interest is configured to measure light emitted from a sample in the flow stream at one or more particular wavelengths. For example, the particle analyzer may have one or more detectors configured to measure light at one or more of: 450 nm, 518 nm, 519 nm, 561 nm, 578 nm, 605 nm, 607 nm, 625 nm, 650 nm, 660 nm, 667 nm, 670 nm, 668 nm, 695 nm, 710 nm, 723 nm, 780 nm, 785 nm, 647 nm, 617 nm, and any combination thereof. In some embodiments, the one or more detectors may be configured to pair with a particular fluorophore, such as a fluorophore used with a sample in a fluorescence assay.

[0089] In some embodiments, one or more of the particle modulation photodetectors comprises one or more detector arrays, e.g., an array of photodiodes. In these embodiments, each photodetector array may comprise 4 or more detectors, e.g., 10 or more detectors, e.g., 25 or more detectors, e.g., 50 or more detectors, e.g., 100 or more detectors, e.g., 250 or more detectors, e.g., 500 or more detectors, e.g., 750 or more detectors, e.g., 1000 or more detectors. For example, a detector may be a photodiode array having 4 or more photodiodes, e.g., 10 or more photodiodes, e.g., 25 or more photodiodes, e.g., 50 or more photodiodes, e.g., 100 or more photodiodes, e.g., 250 or more photodiodes, e.g., 500 or more photodiodes, e.g., 750 or more photodiodes, e.g., 1000 or more photodiodes.

[0090] The detectors may be arranged in any geometric configuration as desired, with configurations of interest including, but not limited to, square, rectangular, trapezoidal, triangular, hexagonal, heptagonal, octagonal, nonagonal, decagonal, dodecagonal, circular, elliptical, and irregular pattern configurations. The detectors of the detector array may be oriented at angles (with respect to the XZ plane) in the range of 10° to 180°, such as 15° to 170°, such as 20° to 160°, such as 25° to 150°, such as 30° to 120°, such as 45° to 90°, relative to the other detectors. The detector array may have any suitable shape, including rectilinear shapes, such as square, rectangular, trapezoidal, triangular, hexagonal, curvilinear shapes, such as circular, elliptical, and irregular shapes, such as a parabolic base joined to a planar top. In an embodiment, the detector array has a rectangular active surface.

[0091] In some embodiments, the particle analyzer comprises one or more wavelength separators disposed between the flow cell and the one or more particle modulation light detectors. The term "wavelength separator" is used herein in its conventional sense to refer to an optical component configured to separate light collected from a sample into predetermined spectral regions. In some embodiments, the particle analyzer comprises one wavelength separator. In other embodiments, the particle analyzer comprises multiple wavelength separators, e.g., 2 or more wavelength separators, e.g., 3 or more, e.g., 4 or more, e.g., 5 or more, e.g., 6 or more, e.g., 7 or more, e.g., 8 or more, e.g., 9 or more, e.g., 10 or more, e.g., 15 or more, e.g., 25 or more, e.g., 50 or more, e.g., 75 or more, e.g., 100 or more wavelength separators. In some embodiments, the wavelength separator is configured to separate light collected from a sample into predetermined spectral regions by passing light having a predetermined spectral region and reflecting light in one or more remaining spectral regions. In other embodiments, the wavelength separator is configured to separate light collected from a sample into predetermined spectral regions by passing light having a predetermined spectral region and absorbing light in one or more remaining spectral regions. In yet other embodiments, the wavelength separator is configured to spatially diffract light collected from the sample into a predetermined spectral region. Each wavelength separator may be any convenient light separation protocol, such as one or more dichroic mirrors, bandpass filters, diffraction gratings, beam splitters, or prisms. In some embodiments, the wavelength separator is a prism. In other embodiments, the wavelength separator is a diffraction grating. In certain embodiments, the wavelength separator of the subject light detection system is a dichroic mirror.

[0092] In some cases, one or more detectors of the system may be considered to be trigger sensors (i.e., sensors that observe the presence of a particle and generate a trigger signal). In some embodiments, the trigger sensor is a forward scattered light detector (e.g., as described above). In other cases, the trigger sensor is an axial light loss (ALL) channel sensor. In such cases, the processor may be configured to calculate a trigger window based on the trigger signal, giving the time when a particle is expected to pass through the detection zone of the detector, and to obtain a baseline noise level at times outside the trigger window.

[0093] Suitable flow cytometry systems include those described in Ormerod (ed.), Flow Cytometry: A Practical Approach, Oxford Univ. Press (1997);Jaroszeski et al. (eds.), Flow Cytometry Protocols, Methods in Molecular Biology No. 91, Humana Press (1997);Practical Flow Cytometry, 3rd ed., Wiley-Liss (1995);Virgo, et al. (2012) Ann Clin Biochem. Jan;49(pt 1):17-28;Linden, et. al., Semin Throm Hemost. 2004 Oct;30(5):502-11;Alison, et al. J Pathol, 2010 Dec; 222(4):335-344; and Herbig, et al. (2007) Crit Rev Ther Drug Carrier Syst. 24(3):203-255.In some cases, flow cytometry systems of interest include BD Biosciences FACSCanto™ flow cytometers, BD Biosciences FACSCanto™ II flow cytometers, BD Accuri™ flow cytometers, BD Accuri™ C6 Plus flow cytometers, BD Biosciences FACSCelesta™ flow cytometers, BD Biosciences FACSLyric™ flow cytometers, BD Biosciences FACSVerse™ flow cytometers, BD Biosciences FACSymphony™ flow cytometers, BD Biosciences LSRFortessa™ flow cytometers, BD Biosciences LSRFortessa™ X-20 flow cytometers, BD Biosciences FACSPresto™ flow cytometers, BD Biosciences FACSVia™ flow cytometers, and BD Biosciences FACSCalibur™ cell sorters, BD Biosciences FACSCount™ cell sorters, BD Biosciences FACSLyric™ cell sorters, BD These include BD Biosciences Via™ cell sorters, BD Biosciences Influx™ cell sorters, BD Biosciences Jazz™ cell sorters, BD Biosciences Aria™ cell sorters, BD Biosciences FACSAria™ II cell sorters, BD Biosciences FACSAria™ III cell sorters, BD Biosciences FACSAria™ Fusion cell sorters, BD Biosciences FACSMelody™ cell sorters, and BD Biosciences FACSymphony™ S6 cell sorters.

[0094] In some embodiments, the subject system is a flow cytometry system, e.g., as described in U.S. Pat. Nos. 10,663,476, 10,620,111, 10,613,017, 10,605,713, 10,585,031, 10,578,542, 10,578,469, 10,481,074, 10,302,545, 10,145,793, 10,113,967, 10,006,852, 9,952,076, 9,933,341, 9,726,527, 9,453,789, 9,200,334, 9,000,491, 9,100,620, 9,200,492, 9,300,820, 9,400,440, 9,500,460, 9,600,480, 9,700,480, 9,800,480, 9,900,480, 9,100,480, 9,200,480, 9,300,480, 9,400,480, 9,500,480, 9,600,480, 9,700,480, 9,800,480, 9,900,480, 9,100,480, 9,100,480, 9,200,480, 9,300,480, 9,400,480, 9,500,480, 9,1 97640, U.S. Pat. No. 9095494, U.S. Pat. No. 9092034, U.S. Pat. No. 8975595, U.S. Pat. No. 8753573, U.S. Pat. No. 8233146, U.S. Pat. No. 8140300, U.S. Pat. No. 7544326, U.S. Pat. No. 7201875, U.S. Pat. No. 7129505, U.S. Pat. No. 6821740, U.S. Pat. No. 6813017, U.S. Pat. No. 6809804, U.S. Pat. No. 6372506, U.S. Pat. No. 5700692, U.S. Pat. No. 5643796, U.S. Pat. No. 5627040, U.S. Pat. No. 5620842, U.S. Pat. No. 5602039, U.S. Pat. No. 4987086, and U.S. Pat. No. 4498766. In some cases, the flow cytometry system of the present invention is a cluster wavelength division (CWD) system. CWD systems are described, for example, in U.S. Patent Application Publication No. 2021 / 0247293, the disclosure of which is incorporated herein by reference in its entirety.

[0095] In some cases, the flow cytometry system of the present invention may be implemented using the techniques disclosed in Diebold, et al. Nature Photonics Vol. 7(10); 806-810 (2013), the disclosures of which are incorporated herein by reference, as well as U.S. Pat. Nos. 9,423,353, 9,784,661, 9,983,132, 10,006,852, 10,078,045, 10,036,699, 10,222,316, 10,288,546, 10,324,019, 10,408,758, 10,451,538, 10,620,111, 10,820,121, 10,840,132, 10,820,141, 10,840,152, 10,840,162, 10,840,171, 10,840,185, 10,840,191, 10,840,192, 10,840,162, 10,840,173, 10,840,191, 10,840,162, 10,840,173, 10,840,185, 10,840,192, 10,840,16 ... The present invention has been adapted to image particles in a flow stream by Fluorescence Imaging using Radio Frequency Tag Emission (FIRE), as described in U.S. Patent Application Publication No. 2019 / 0376895, U.S. Patent Application Publication No. 2019 / 0376894, U.S. Patent Application Publication No. 2019 / 0376895, U.S. Patent Application Publication No. 2019 / 0376894, U.S. Patent Application Publication No. 2019 / 0376895, U.S. Patent Application Publication No. 2019 / 0376894, and U.S. Patent Application Publication No. 2019 / 0376894.

[0096] 3 illustrates a system 300 for flow cytometry according to an exemplary embodiment of the invention. System 300 includes a flow cytometer 310, a controller / processor 390, and a memory 395. Flow cytometer 310 includes one or more excitation lasers 315a-315c, a focusing lens 320, a flow chamber 325, a forward scatter detector 330, a side scatter detector 335, a fluorescence collection lens 340, one or more beam splitters 345a-345g, one or more bandpass filters 350a-350e, one or more longpass (LP) filters 355a-355b, and one or more fluorescence detectors 360a-360f.

[0097] The pump lasers 315a-315c emit light in the form of laser beams. The wavelengths of the laser beams emitted from the pump lasers 315a-315c are 488 nm, 633 nm, and 325 nm, respectively, in the exemplary system of FIG. 3. The laser beams are first directed through one or more of the beam splitters 345a and 345b. The beam splitter 345a transmits the 488 nm light and reflects the 633 nm light. The beam splitter 345b transmits the UV light (light having a wavelength in the range of 10-400 nm) and reflects the 488 nm and 633 nm lights.

[0098] The laser beam is then directed to a focusing lens 320, which focuses the laser beam onto the portion of the fluid stream in which the sample particles reside in a flow chamber 325. The flow chamber is the part of the fluid system that directs particles in the stream, usually one at a time, into the focused laser beam for investigation. The flow chamber can comprise a flow cell in a benchtop flow cytometer or a nozzle tip in a stream-in-air cytometer.

[0099] Light from the laser beam(s) interacts with particles in the sample by diffraction, refraction, reflection, scattering and absorption, and is re-emitted at a variety of different wavelengths depending on the particle's properties, such as the particle's size, internal structure, and the presence of one or more fluorescent molecules attached to or naturally present on or in the particle. The fluorescent radiation, as well as the diffracted, refracted, reflected and scattered light, may be sent through one or more of beam splitters 345c-345g, bandpass filters 350a-350e, longpass filters 355a-355b, and fluorescence collection lens 340 to one or more of forward scatter detector 330, side scatter detector 335, and one or more fluorescence detectors 360a-360f.

[0100] Fluorescence collection lens 340 collects light emitted by particle-laser beam interactions and directs the light toward one or more beam splitters and filters. Bandpass filters, such as bandpass filters 350a-350e, allow a narrow range of wavelengths to pass through the bandpass filter. For example, bandpass filter 350a is a 510 / 20 filter. The first number represents the center of the spectral band. The second number represents the range of the spectral band. Thus, a 510 / 20 filter extends 10 nm on either side of the center of the spectral band, from 500 nm to 520 nm. Shortpass filters transmit light with wavelengths equal to or less than a specified wavelength. Longpass filters, such as longpass filters 355a-355b, transmit light with wavelengths equal to or greater than a specified wavelength of light. For example, longpass filter 355b, a 670 nm longpass filter, transmits light above 670 nm. Filters are often selected to optimize the specificity of the detector for a particular fluorochrome. The filters may be configured so that the spectral band of light transmitted to the detector is close to the emission peak of the fluorescent dye.

[0101] The forward scatter detector 330 is positioned slightly off-axis from the direct beam through the flow cell and is configured to detect diffracted light, i.e., excitation light traveling primarily in a forward direction through or around the particle. The intensity of light detected by the forward scatter detector depends on the overall size of the particle. The forward scatter detector may include a photodiode. The side scatter detector 335 is configured to detect refracted and reflected light at the surface and internal structure of the particle, which tends to increase as the complexity of the particle's structure increases. Fluorescent emission from fluorescent molecules bound to the particle may be detected by one or more of the fluorescence detectors 360a-360f. The side scatter detector 335 and the fluorescence detector may include photomultiplier tubes. The signals detected by the forward scatter detector 330, the side scatter detector 335 and the fluorescence detector may be converted to electronic signals (voltage) by the detectors. This data may provide information about the sample.

[0102] Those skilled in the art will recognize that flow cytometers according to embodiments of the present invention are not limited to the flow cytometer shown in Figure 3, but may include any flow cytometer known in the art. For example, a flow cytometer may have any number of lasers, beam splitters, filters, and detectors of various wavelengths and in a variety of different configurations.

[0103] During operation, the operation of the flow cytometer is controlled by the controller / processor 390, and measurement data from the detectors may be stored in memory 395 and processed by the controller / processor 390. Although not explicitly shown, the controller / processor 390 is coupled to the detectors to receive output signals from the detectors, and may further be coupled to electrical and electromechanical components of the flow cytometer 310 to control lasers, fluid flow parameters, and the like. Input / output (I / O) functionality 397 may also be provided in the system. The memory 395, controller / processor 390, and I / O functionality 397 may be provided entirely as an integral part of the flow cytometer 310. In such an embodiment, a display may also form part of the I / O functionality 397 to present experimental data to a user of the flow cytometer 310. Alternatively, some or all of the memory 395 and the controller / processor 390 and I / O functionality may be part of one or more external devices, such as a general purpose computer. In some embodiments, some or all of the memory 395 and controller / processor 390 may be in wireless or wired communication with the flow cytometer 310. The controller / processor 390 in conjunction with the memory 395 and I / O functionality 397 may be configured to perform a variety of functions associated with the preparation and analysis of flow cytometer experiments.

[0104] The system illustrated in FIG. 3 includes six different detectors that detect fluorescence in six different wavelength bands (which may be referred to herein as "filter windows" for a given detector) as defined by the configuration of filters and / or splitters in the beam path from the flow cell 325 to each detector. Different fluorescent molecules used in a flow cytometer experiment emit light in their own unique wavelength bands. The particular fluorescent labels used in the experiment and the associated fluorescent emission bands of the fluorescent labels may be selected to approximately match the filter windows of the detectors. The I / O functionality 397 may be configured to receive data regarding a flow cytometer experiment having a panel of fluorescent labels and multiple cell populations having multiple markers, each cell population having a subset of multiple markers. The I / O functionality 397 may be further configured to receive biological data assigning one or more markers to one or more cell populations, marker concentration data, emission spectrum data, data assigning labels to one or more markers, and cytometer configuration data. Flow cytometer experiment data, such as label spectral characteristics and flow cytometer configuration data, may be further stored in the memory 395. The controller / processor 390 may be configured to evaluate one or more assignments of labels to markers.

[0105] In some embodiments, the subject system is a particle sorting system configured to sort particles using an enclosed particle sorting module, such as described in U.S. Patent Application Publication No. 2017 / 0299493, filed March 28, 2017, the disclosure of which is incorporated herein by reference. In an embodiment, particles (e.g., cells) of a sample are sorted using a sorting determination module having a plurality of sorting determination units, such as described in U.S. Patent Application Publication No. 2020 / 0256781, filed December 23, 2019, the disclosure of which is incorporated herein by reference. In some embodiments, a system for sorting components of a sample includes a particle sorting module having deflection plates, such as described in U.S. Patent Application Publication No. 2017 / 0299493, filed March 28, 2017, the disclosure of which is incorporated herein by reference.

[0106] 4 is a functional block diagram of an example of a system for analyzing and displaying biological events having a processor 400. The processor 400 may be configured to perform various processes for controlling the graphical display of biological events.

[0107] A flow cytometer or sorting system 402 may be configured to acquire bio-event data. For example, a flow cytometer may generate flow cytometry event data (e.g., particle-modulated light data). The flow cytometer 402 may be configured to provide the bio-event data to the processor 400. A data communication channel may be provided between the flow cytometer 402 and the processor 400. The bio-event data may be provided to the processor 400 via the data communication channel.

[0108] The processor 400 may be configured to receive bio-event data from the flow cytometer 402. The bio-event data received from the flow cytometer 402 may include flow cytometry event data. The processor 400 is configured to evaluate the data received from the flow cytometer 402, for example, as described above. The processor 400 may be configured to perform the subject method by incrementally increasing a gain of a detector (or detectors) such that the detector collects light from the flow stream at each of a plurality of successively increasing gains, obtaining a baseline noise level from the detector at each of the plurality of successively increasing gains, calculating a LoD for each of the plurality of successively increasing gains, and evaluating the calculated LoD to determine an ideal gain.

[0109] The processor 400 may be configured to cause the display device 406 to display a graphical display including the bio-event data. For example, the processor 400 may provide the display device 406 with the calculated ideal gains for each of the detectors in the system (e.g., the fluorescent light detectors 360a-360e). These ideal gains may be output, for example, in the form of tube target values ​​(TTVs). The processor 400 may be further configured to render a region of interest as a gate around the population of bio-event data displayed by the display device 406, for example, overlaid on the first plot. In some embodiments, the gate may be a logical combination of one or more illustrated regions of interest plotted on a histogram or bivariate plot of one parameter. In some embodiments, the display may be used to display particle parameters or saturated detector data.

[0110] The processor 400 may further be configured to display the bioevent data on the display device 406 within the gate differently than other events within the bioevent data outside the gate. For example, the processor 400 may be configured to render the color of the bioevent data included within the gate differently than the color of the bioevent data outside the gate. The display device 406 may be implemented as a monitor, tablet computer, smartphone, or other electronic device configured to provide a graphical interface.

[0111] The processor 400 may be configured to receive a gate selection signal identifying a gate from a first input device. For example, the first input device may be implemented as a mouse 410. The mouse 410 may transmit a gate selection signal identifying a gate to be displayed on or manipulated via the display device 406 (e.g., by clicking on or within the desired gate when the cursor is on the desired gate) to the processor 400. In some implementations, the first device may be implemented as a keyboard 408 or other means for providing input signals to the processor 400, such as a touch screen, a pen for input, a photodetector, or a voice recognition system. Some input devices may include multiple input functions. In such implementations, each input function may be considered an input device. For example, as shown in FIG. 4, the mouse 410 may include a right mouse button and a left mouse button, and the right mouse button and the left mouse button may each generate a trigger event.

[0112] A trigger event can cause the processor 400 to change how the data is displayed, what portions of the data are actually displayed on the display device 406, and / or provide input for further processing, such as selection of a population of interest for particle sorting.

[0113] In some embodiments, the processor 400 may be configured to detect when a gate selection is initiated by the mouse 410. The processor 400 may further be configured to automatically modify the visualization of the plot to facilitate gating. This modification may be based on a particular distribution of the bio-event data received by the processor 400. In some embodiments, the processor 400 extends the first gate such that a second gate is generated (e.g., as described above).

[0114] The processor 400 may be connected to a storage device 404. The storage device 404 may be configured to receive and store bio-event data from the processor 400. The storage device 404 may be further configured to receive and store flow cytometry event data from the processor 400. The storage device 404 may be further configured to enable retrieval of bio-event data, such as flow cytometry event data, by the processor 400.

[0115] The display device 406 may be configured to receive display data from the processor 400. The display data may include plots of the biological event data and gates outlining sections of the plots. The display device 406 may be further configured to modify the information displayed in response to input received from the processor 400 in conjunction with input from the flow cytometer 402, the storage device 404, the keyboard 408, and / or the mouse 410.

[0116] In some embodiments, the processor 400 can generate a user interface for receiving exemplary events for screening. For example, the user interface can include a mechanism for receiving exemplary events or exemplary images. The exemplary events or images, or exemplary gates, can be provided prior to collection of event data for a sample, or based on an initial set of events for a portion of a sample.

[0117] FIG. 5A is a schematic diagram illustrating a particle sorting system 500 (e.g., flow cytometer 402) according to one embodiment presented herein. In some embodiments, the particle sorting system 500 is a cell sorting system. As shown in FIG. 5A, a droplet forming transducer 502 (e.g., a piezoelectric oscillator) is coupled to a fluid conduit 501, which may be coupled to, include, or be a nozzle 503. Within the fluid conduit 501, a sheath fluid 504 hydrodynamically focuses a sample fluid 506 containing particles 509 into a moving fluid column 508 (e.g., a stream). Within the moving fluid column 508, the particles 509 (e.g., cells) are aligned in a single file across a monitoring region 511 (e.g., where a laser stream intersects) and are illuminated by an illumination source 512 (e.g., a laser). Vibration of the droplet forming transducer 502 causes the moving fluid column 508 to break up into a number of droplets 510 , some of which contain particles 509 .

[0118] In operation, a detection station 514 (e.g., an event detector) identifies when a particle of interest (or cell of interest) crosses the monitoring region 511. The detection station 514 feeds a timing circuit 528, which in turn feeds a flash charge circuit 530. At a droplet break-off point, signaled by a timed droplet delay (Δt), a flash charge can be applied to the moving fluid column 508 such that the droplet of interest carries a charge. The droplet of interest can contain one or more particles or cells to be sorted. The charged droplets can then be sorted by activating a deflection plate (not shown) to deflect the charged droplets into a receptacle, such as a collection tube or a multi-well or microwell sample plate, where a well or microwell can be specifically associated with the droplet of interest. As shown in FIG. 5A, the droplets can be collected in a drain receptacle 538.

[0119] The detection system 516 (e.g., a droplet boundary detector) serves to automatically determine the phase of the droplet drive signal when a particle of interest passes through the monitoring region 511. An exemplary droplet boundary detector is described in U.S. Pat. No. 7,679,039, the entire contents of which are incorporated herein by reference. The detection system 516 enables the instrument to accurately calculate the position of each detected particle in the droplet. The detection system 516 may provide an amplitude signal 520 and / or a phase signal 518, which are then provided (via an amplifier 522) to an amplitude control circuit 526 and / or a frequency control circuit 524. The amplitude control circuit 526 and / or the frequency control circuit 524 then control the droplet forming transducer 502. The amplitude control circuit 526 and / or the frequency control circuit 524 may be provided within the control system.

[0120] In some embodiments, the sorting electronics (e.g., detection system 516, detection station 514, and processor 540) may be coupled to a memory configured to store detected events and sorting decisions based on the detected events. The sorting decisions may be included in the event data for the particles. In some embodiments, detection system 516 and detection station 514 may be implemented as a single detection unit or may be communicatively coupled such that event measurements may be collected by either detection system 516 or detection station 514 and provided to a non-collection element.

[0121] FIG. 5B is a schematic diagram showing a particle sorting system according to one embodiment presented herein. The particle sorting system 500 shown in FIG. 5B includes deflection plates 552 and 554. An electric charge can be applied via a stream charging wire in the barb, thus generating a stream of droplets 510 containing the particles 509 for analysis. The particles can be illuminated with one or more light sources (e.g., lasers) to generate light scattering and fluorescence information. The information about the particles is analyzed, such as by sorting electronics (not shown in FIG. 5B) or other detection systems. Deflection plates 552 and 554 can be independently controlled to attract or repel the charged droplets and direct them toward a desired collection vessel (e.g., one of 572, 574, 576, or 578). 5B, deflector 552 and deflector 554 can be controlled to direct particles along a first path 562 toward a container 574 or along a second path 568 toward a container 578. If the particle is not of interest (e.g., does not exhibit scattering or illumination information within a specified sorting range), the deflector may allow the particle to continue along flow path 564. Such uncharged droplets may be channeled into a waste container, such as via an aspirator 570.

[0122] Sorting electronics can be included to initiate measurement collection, receive fluorescent signals for the particles, and determine how to adjust the deflection plates to sort the particles. Exemplary implementations of the embodiment shown in Figure 5B include the BD FACSAria™ line of flow cytometers marketed by Becton, Dickinson and Company (Franklin Lakes, NJ).

[0123] Computer-readable storage medium Aspects of the present disclosure further include a non-transitory computer-readable storage medium having instructions for carrying out the subject methods. The computer-readable storage medium may be employed in one or more computers for fully automating or partially automating a system for carrying out the methods described herein. In certain embodiments, instructions for the methods described herein may be encoded in a computer-readable medium in the form of a "program," and the term "computer-readable medium" as used herein refers to any non-transitory storage medium involved in providing instructions and data to a computer for execution and processing. Examples of suitable non-transitory storage media include magnetic disks, hard disks, optical disks, magneto-optical disks, CD-ROMs, CD-Rs, magnetic tapes, non-volatile memory cards, ROMs, DVD-ROMs, Blu-ray® disks, solid-state disks, flash drives, and network-attached storage (NAS), regardless of whether such devices are internal or external to the computer. A file containing information may be "stored" on a computer-readable medium, where "storing" means recording information such that the information can be accessed and retrieved at a later date by a computer. The computer-implemented methods described herein may be performed using programs that may be written in one or more of any number of computer programming languages, including, for example, Java, Python, Visual Basic, and C++, as well as many others.

[0124] In some embodiments, a computer readable storage medium of interest includes a computer program stored thereon, the computer program including instructions having an algorithm, when loaded into a computer, for incrementally increasing a gain of a detector such that the detector collects light from particles in a flow stream at each of a plurality of successively increasing gains, obtaining a baseline noise level from the detector at each of the plurality of successively increasing gains, calculating a limit of detection (LoD) for each of the plurality of successively increasing gains, and evaluating the calculated LoDs to determine an ideal gain. The instructions of interest are configured to calculate each LoD based on the gain and the baseline noise level.

[0125] Computer Control System Aspects of the present disclosure further include a computer control system, the computer control system comprising one or more computers for full or partial automation. In some embodiments, the system comprises a computer having a non-transitory computer readable storage medium having a computer program stored thereon, the computer program comprising instructions, when loaded into the computer, for incrementally increasing a gain of the detector such that the detector collects light from particles in the flow stream at each of a plurality of successively increasing gains, obtaining a baseline noise level from the detector at each of the plurality of successively increasing gains, calculating a limit of detection (LoD) for each of the plurality of successively increasing gains, and evaluating the calculated LoDs to determine an ideal gain. The instructions of interest are configured to calculate each LoD based on the gain and the baseline noise level. The instructions of interest are configured to calculate each LoD based on the gain and the baseline noise level.

[0126] The system may include a display and an operator input device. The operator input device may be, for example, a keyboard, a mouse, etc. The processing module has a processor that can access a memory in which instructions for performing the steps of the subject method are stored. The processing module may include an operating system, a graphical user interface (GUI) controller, a system memory, a memory storage device, an input / output controller, a cache memory, a data backup unit, and many other devices. The processor may be a commercially available processor or one of other processors that are available or become available. The processor executes an operating system, which interfaces with firmware and hardware in a well-known manner to facilitate the processor coordinating and executing the functions of various computer programs, which may be written in various programming languages, such as Java, Perl, C++, Python, other high-level or low-level languages, and combinations thereof, as is known in the art. The operating system generally cooperates with the processor to coordinate and execute the functions of the other elements of the computer. The operating system further provides scheduling, input / output control, file and data management, memory management, and communication control and related services, all according to known techniques. In some embodiments, the processor includes analog electronics that provide feedback control, such as negative feedback control.

[0127] The system memory may be any of a variety of known or future memory storage devices. Examples include any commonly available random access memory (RAM), magnetic media such as resident hard disks or tapes, optical media such as read-write compact disks, flash memory devices or other memory storage devices. The memory storage devices may be any of a variety of known or future devices including compact disk drives, tape drives, or diskette drives. Such types of memory storage devices typically read from and / or write to a program storage medium (not shown) such as a compact disk. Any of these program storage media, or other program storage media now in use or that may be developed in the future, may be considered a computer program product. As will be appreciated, these program storage media typically store computer software programs and / or data. Computer software programs, also referred to as computer control logic, are typically stored in the system memory and / or in program storage devices used in conjunction with the memory storage devices.

[0128] In some embodiments, a computer program product is described that includes a computer usable medium having stored thereon control logic (a computer software program including program code). The control logic, when executed by a processor, a computer, causes the processor to perform the functions described herein. In other embodiments, some functions are implemented primarily in hardware, for example using hardware state machines. The implementation of hardware state machines to perform the functions described herein will be apparent to one of ordinary skill in the relevant art.

[0129] The memory may be any suitable device from which the processor can store and retrieve data, such as a magnetic device, an optical device, or a solid-state storage device (including a magnetic or optical disk or a tape or a RAM or any other suitable device, fixed or portable). The processor may include a general-purpose digital microprocessor suitably programmed from a computer-readable medium storing the necessary program code. The program may be provided remotely to the processor via a communication channel, or may be pre-recorded in a computer program product such as a memory, or in other portable or fixed computer-readable storage media using either a device connected to the memory. For example, a magnetic or optical disk may store the program and may be read by a disk writer / reader. The system of the present invention further comprises a program, for example in the form of a computer program product, an algorithm for use in implementing the method as described above. The program of the present invention may be recorded in a computer-readable medium, for example any medium that can be directly read and accessed by a computer. Such media include, but are not limited to, magnetic storage media, such as magnetic disks, hard disk storage media, and magnetic tape; optical storage media, such as CD-ROM; electrical storage media, such as RAM and ROM; portable flash drives; and hybrids of these categories, such as magnetic / optical storage media.

[0130] The processor may also access a communication channel to communicate with a user at a remote location, meaning that the user does not have direct contact with the system but relays input information to the input manager from an external device, such as a computer connected to a wide area network ("WAN"), a telephone network, a satellite network, or any other suitable communication channel, including a mobile phone (i.e., a smartphone).

[0131] In some embodiments, a system according to the present disclosure may be configured to include a communication interface. In some embodiments, the communication interface includes a receiver and / or a transmitter for communicating with a network and / or another device. The communication interface may be configured for wired or wireless communication, including but not limited to radio frequency (RF) communication, such as radio frequency identification (RFID), ZigBee communication protocol, Wi-Fi, infrared, wireless universal serial bus (USB), ultra-wideband (UWB), Bluetooth® communication protocol, and cellular communication, such as code division multiple access (CDMA) or Global System for Mobile Communications (GSM).

[0132] In one embodiment, the communication interface is configured to include one or more communication ports, e.g., physical ports or interfaces, such as a USB port, a USB-C port, an RS-232 port, or any other suitable electrical connection port, to enable data communication between the subject system and other external devices, such as computer terminals (e.g., in a clinic or hospital environment) configured for similar complementary data communication.

[0133] In one embodiment, the communications interface is configured for infrared communications, Bluetooth® communications, or any other suitable wireless communications protocol, allowing the subject system to communicate with other devices, such as computer terminals and / or networks, communication-enabled mobile phones, personal digital assistants, or any other communications devices that a user may use in conjunction therewith.

[0134] In one embodiment, the communication interface is configured to provide a connection for data transfer utilizing Internet Protocol (IP) via a cellular network, Short Message Service (SMS), a wireless connection to a personal computer (PC) on a local area network (LAN) connected to the Internet, or a Wi-Fi connection to the Internet at a Wi-Fi hotspot.

[0135] In one embodiment, the subject system is configured to communicate wirelessly with the server device via a communication interface using common standards such as 802.11, Bluetooth RF protocol, or IrDA infrared protocol. The server device may be another portable device, such as a smart phone, a personal digital assistant (PDA), or a notebook computer; or a larger device, such as a desktop computer, an appliance, etc. In some embodiments, the server device has a display, such as a liquid crystal display (LCD), and an input device, such as a button, a keyboard, a mouse, or a touch screen.

[0136] In some embodiments, the communications interface is configured to automatically or semi-automatically communicate data stored in the subject system, e.g., any data storage unit, with a network or server device using one or more of the communications protocols and / or mechanisms described above.

[0137] The output controller may include a controller for any of a variety of known display devices for presenting information to a user, whether human or machine, local or remote. Where one of the display devices provides visual information, this information may generally be logically and / or physically organized as an array of pixels. A graphical user interface (GUI) controller may include any of a variety of known or future software programs for providing a graphical input / output interface between the system and the user, and for processing user input. The functional elements of the computer may communicate with each other via a system bus. Some of these communications may be accomplished using a network or other type of remote communication in alternative embodiments. The output manager may further provide information generated by the processing module to a user at a remote location, for example, via the Internet, telephone, or satellite network, according to known techniques. Presentation of data by the output manager may be performed according to a variety of known techniques. As some examples, the data may include SQL, HTML, or XML documents, emails, or other files, or other forms of data. The data may include Internet URL addresses so that the user may retrieve additional SQL, HTML, XML, or other documents or data from remote sources. The platform or platforms present in the subject system are typically a class of computers commonly referred to as servers, but may be any type of computer platform now known or later developed. However, the platforms may also be mainframe computers, workstations, or other computer types. The platforms may be connected via any type of cabling, now known or later, or other communication systems, including wireless systems, whether networked or not. The platforms may be co-located or physically separated.Various operating systems may be used on any of the computer platforms, depending in some cases on the type and / or configuration of the computer platform selected. Suitable operating systems include Windows NT, Windows XP, Windows 7, Windows 8, Windows 10, iOS, macOS, Linux, Ubuntu, Fedora, OS / 400, i5 / OS, IBM i, Android™, SGI IRIX, Oracle Solaris, and the like.

[0138] FIG. 6 illustrates a general configuration of an exemplary computing device 600 according to an embodiment. The general configuration of the computing device 600 illustrated in FIG. 6 includes an arrangement of computer hardware and software components. However, not all of these general conventional elements need to be illustrated to provide a useful disclosure. As illustrated, the computing device 600 includes a processing unit 610, a network interface 620, a computer-readable medium drive 630, an input / output device interface 640, a display 650, and an input device 660, all of which may communicate with each other via a communication bus. The network interface 620 may provide connectivity to one or more networks or computing systems. Thus, the processing unit 610 may receive information and instructions from other computing systems or services via the network. The processing unit 610 may further communicate with a memory 670 and may further provide output information for an optional display 650 via the input / output device interface 640. For example, analysis software (e.g., data analysis software or programs, such as FlowJo®), stored as executable instructions in non-transitory memory of the analysis system, can display flow cytometry event data to a user. Input / output device interface 640 may further accept input from any input device 660, such as a keyboard, mouse, digital pen, microphone, touch screen, gesture recognition system, voice recognition system, game pad, accelerometer, gyroscope, or other input device.

[0139] Memory 670 may include computer program instructions (grouped in some embodiments as modules or components) that processing unit 610 executes to implement one or more embodiments. Memory 670 typically includes RAM, ROM, and / or other persistent, secondary, or non-transitory computer-readable media. Memory 670 may store an operating system 672 that provides computer program instructions for use by processing unit 610 in the general management and operation of computing device 600. Data may be stored in data storage device 690. Memory 670 may further include computer program instructions and other information for implementing aspects of the present disclosure.

[0140] usefulness The subject methods, systems, and computer systems find use in a variety of applications where it is desirable to calibrate or optimize optical detectors, such as particle analyzers. The invention may be used where it is desirable to determine the ideal gain of a detector and / or reduce fluorophore spread. The subject methods and systems find further use in optical detectors used to analyze and sort particle components in samples in fluid media, such as biological samples. The present disclosure finds further use in flow cytometry, where it is desirable to provide a flow cytometer with improved cell sorting accuracy, improved particle collection, reduced energy consumption, particle charging efficiency, more accurate particle charging, and improved particle deflection during cell sorting. In embodiments, the present disclosure reduces the need for user input or manual adjustments during sample analysis using a flow cytometer. In certain embodiments, the subject methods and systems provide fully automated protocols, such that adjustments to the flow cytometer during use require little, if any, human input.

[0141] The embodiments of the present invention are further used in applications where cells prepared from biological samples may be desired for use in research, clinical trials, or therapy. In some embodiments, the subject methods and devices may facilitate obtaining individual cells prepared from a target fluid or tissue biological sample. For example, the subject methods and systems may facilitate obtaining cells from a fluid or tissue sample used as a research or diagnostic specimen for a disease such as cancer. Similarly, the subject methods and systems may facilitate obtaining cells from a fluid or tissue sample used for therapy. The disclosed methods and devices allow for the separation and collection of cells from biological samples (e.g., organs, tissues, tissue slices, fluids) with high efficiency and low cost compared to conventional flow cytometry systems.

[0142] kit Aspects of the present disclosure further include kits, the kits having storage media, such as magneto-optical disks, CD-ROMs, CD-Rs, magnetic tapes, non-volatile memory cards, ROMs, DVD-ROMs, Blu-ray® disks, solid state disks, and network attached storage (NAS). Any of these program storage media, or other program storage media now in use or that may be developed in the future, may be included in the subject kits. In embodiments, the program storage media includes instructions for incrementally increasing a gain of a detector such that the detector collects light from particles in the flow stream at each of a plurality of successively increasing gains, obtaining a baseline noise level from the detector at each of the plurality of successively increasing gains, calculating a limit of detection (LoD) for each of the plurality of successively increasing gains, and evaluating the calculated LoDs to determine an ideal gain. In embodiments, the instructions included in the computer readable media provided in the subject kits, or portions thereof, may be implemented as a software component of software for analyzing data. In these embodiments, the computer control system according to the present disclosure may function as a software "plug-in" to an existing software package.

[0143] In addition to the above components, the subject kits may further include (in some embodiments) instructions for use, for example, for installing a plug-in into an existing software package. These instructions may be present in the subject kits in a variety of forms, one or more of which may be present in the kit. One form in which these instructions may be provided is information printed on a suitable medium or substrate, such as one or more pieces of paper on which the information is printed, the kit packaging, a package insert, etc. Yet another form in which these instructions may be present is a computer readable medium on which the information is recorded, such as a diskette, a compact disc (CD), a portable flash drive, etc. Yet another form in which these instructions may be present is a website address that may be used via the internet to access the information at a remote location.

[0144] Regardless of the scope of the appended claims, the present disclosure is further defined by the following caveats.

[0145] Appendix 1. A method for determining an ideal gain of a detector in an optical detection system of a flow cytometer, comprising: A light source is applied to the flow stream; increasing the gain of the detector in steps such that the detector collects light from the flow stream at each of a plurality of successively increasing gains; obtaining a baseline noise level from the detector at each of a plurality of successively increasing gains; calculating a limit of detection (LoD) for each of a plurality of successively increasing gains based on the gain and a baseline noise level; A method to evaluate the calculated LoD and determine the ideal gain.

[0146] Addendum 2. The method of Addendum 1, wherein the LoD calculation generates a ratio between gain and baseline noise level.

[0147] Appendix 3. The method of appendix 2, in which the LoD is calculated by taking the inverse of the ratio between gain and baseline noise level.

[0148] Appendix 4. The method of any one of appendices 1 to 3, wherein when evaluating the calculated LoD, a LoD curve is generated that includes a calculated LoD for each of a plurality of successively increasing gains.

[0149] Clause 5. The method of clause 4, wherein when evaluating the calculated LoD, the LoD curve is evaluated for the presence of an inflection point.

[0150] Appendix 6. When evaluating the calculated LoD, Inflection points of the LoD curve, and Gain in multiple successively increasing gains, related to the LoD at the inflection point The method of claim 5, wherein the

[0151] Clause 7. The method of clause 6, determining that a gain within a plurality of successively increasing gains that is related to the LoD at an inflection point is an ideal gain.

[0152] Appendix 8. The method of any one of appendices 1 to 7, wherein the flow stream comprises a buffer.

[0153] Addendum 9. The method of any one of Addendums 1 to 8, wherein the flow stream comprises water.

[0154] Clause 10. The method of any one of clauses 1 to 9, wherein the flow stream comprises particles.

[0155] Clause 11. The method of clause 10, wherein flow cytometer data associated with a plurality of different particle populations is evaluated to determine an ideal gain.

[0156] Clause 12. The method of clause 11, wherein the plurality of particle populations includes a first particle population that is negative for a particular parameter and a second particle population that is positive for the same parameter.

[0157] Clause 13. The method of clause 12, further comprising obtaining a first signal magnitude and a second signal magnitude for each of the first and second particle populations, respectively, at each of a plurality of successively increasing gains.

[0158] Clause 14. The method of clause 13, further comprising estimating the magnitude of the first signal based on a baseline noise level obtained by the detector at each of a plurality of successively increasing gains.

[0159] Addendum 15. The method of Addendum 13 or 14, further comprising estimating the magnitude of the second signal based on each of a plurality of successively increasing gains.

[0160] Addendum 16. The method of any one of Addendums 13 to 14, further comprising obtaining a magnitude of a second signal from the detector.

[0161] Addendum 17. The method of any one of Addendums 13 to 16, further comprising calculating a difference between the magnitude of the second signal and the magnitude of the first signal acquired at each of a plurality of successively increasing gains.

[0162] Clause 18. The method of clause 17, generating a linearity measure for assessing how the difference between the magnitude of the second signal and the magnitude of the first signal increases with increasing detector gain.

[0163] Clause 19. The method of clause 18, further comprising identifying a point of non-linearity where the difference between the magnitude of the second signal and the magnitude of the first signal does not increase linearly with increasing detector gain.

[0164] Clause 20. The method of clause 19, wherein a gain lower than the gain associated with the point of nonlinearity is determined to be the ideal gain.

[0165] Addendum 21. The method of any one of Addendums 1 to 20, wherein the stepwise increase in gain is terminated after determining the ideal gain.

[0166] Addendum 22. The method of any one of Addendums 10 to 21, wherein the event occurrence rate is set by selecting the sensitivity at which the trigger sensor observes the presence of a particle and generates a trigger signal.

[0167] Addendum 23. The method of Addendum 22, further comprising setting the gain of the trigger sensor.

[0168] Addendum 24. The method of Addendum 22 or 23, wherein the trigger sensor is a forward scattered light sensor.

[0169] Clause 25. The method of clause 22 or 23, wherein the trigger sensor is an axial light loss (ALL) channel sensor.

[0170] Addendum 26. The method of any one of Addendums 22 to 25, further comprising calculating a trigger window based on the trigger signal, the trigger window providing the time during which a particle is expected to pass through a detection zone of the detector.

[0171] Addendum 27. The method of Addendum 26, further comprising obtaining a baseline noise level at a time outside the trigger window.

[0172] Addendum 28. The method of any one of Addendums 1 to 27, wherein the detector is a photomultiplier tube (PMT).

[0173] Addendum 29. The method of any one of Addendums 1 to 27, wherein the detector is an avalanche photodiode (APD).

[0174] Addendum 30. The method of any one of Addendums 1 to 27, wherein the detector is a photodiode (PD).

[0175] Addendum 31. The method of any one of Addendums 1 to 27, wherein the detector is a silicon photomultiplier (SiPM).

[0176] Addendum 32. The method of any one of Addendums 1 to 31, determining ideal gains for multiple detectors.

[0177] Addendum 33. A flow cell configured to carry a flow stream; a light source for illuminating the flow stream at the interrogation point; a detector configured to collect light from the flow stream; a processor operably connected to the detector; Equipped with The processor increasing the gain of the detector in steps such that the detector collects light from the flow stream at each of a plurality of successively increasing gains; obtaining a baseline noise level from the detector at each of a plurality of successively increasing gains; calculating a limit of detection (LoD) for each of a plurality of successively increasing gains based on the gain and a baseline noise level; Evaluate the calculated LoD to determine the ideal gain The system is configured as follows:

[0178] Addendum 34. The system of Addendum 33, wherein when calculating the LoD, a ratio between the gain and the baseline noise level is generated.

[0179] Addendum 35. The system of Addendum 34, wherein when calculating the LoD, the inverse of the ratio between the gain and the baseline noise level is taken.

[0180] Addendum 36. The system of any one of Addendums 33 to 35, wherein when evaluating the calculated LoD, a LoD curve is generated that includes a calculated LoD for each of a plurality of successively increasing gains.

[0181] Addendum 37. The system of Addendum 36, wherein when evaluating the calculated LoD, the LoD curve is evaluated for the presence of an inflection point.

[0182] Appendix 38. When evaluating a calculated LoD, Inflection points of the LoD curve, and Gain in multiple successively increasing gains, related to the LoD at the inflection point 38. The system of claim 37,

[0183] Addendum 39. The system of any one of Addendums 33 to 38, wherein the flow cell is configured to carry particles within the flow stream.

[0184] Addendum 40. The system of Addendum 39, wherein the processor is configured to evaluate flow cytometer data associated with a plurality of different particle populations to determine an ideal gain.

[0185] Clause 41. The system of clause 40, wherein the plurality of particle populations includes a first particle population negative for a particular parameter and a second particle population positive for the same parameter.

[0186] Clause 42. The system of clause 41, wherein the processor is configured to obtain a first signal magnitude and a second signal magnitude for each of the first particle population and the second particle population, respectively, at each of a plurality of successively increasing gains.

[0187] Addendum 43. The system of Addendum 42, wherein the processor is configured to estimate a magnitude of the first signal based on a baseline noise level obtained by the detector at each of a plurality of successively increasing gains.

[0188] Addendum 44. The system of any one of Addendum 42 to 43, wherein the processor is configured to estimate a magnitude of the second signal based on each of a plurality of successively increasing gains.

[0189] Addendum 45. The system of any one of Addendums 42 and 43, wherein the processor is configured to obtain a magnitude of the second signal from the detector.

[0190] Addendum 46. The system of any one of Addendums 42 to 45, wherein the processor is configured to calculate a difference between the magnitude of the second signal and the magnitude of the first signal acquired at each of a plurality of successively increasing gains.

[0191] Addendum 47. The system of Addendum 46, wherein the processor is configured to generate a linearity measure to assess how the difference between the magnitude of the second signal and the magnitude of the first signal increases with increasing detector gain.

[0192] Addendum 48. The system of Addendum 47, wherein the processor is configured to identify a point of nonlinearity where the difference between the magnitude of the second signal and the magnitude of the first signal does not increase linearly with increasing detector gain.

[0193] Clause 49. The system of clause 48, wherein the processor is configured to determine an ideal gain that is lower than a gain associated with a point of nonlinearity.

[0194] Addendum 50. The system of any one of Addendums 33-49, wherein the processor is configured to terminate incrementally increasing the gain after determining the ideal gain.

[0195] Addendum 51. A system described in any one of Addendums 39 to 50, further comprising a trigger sensor configured to observe the presence of a particle in the flow cell and generate a trigger signal.

[0196] Addendum 52. The system of Addendum 51, wherein the trigger sensor is a forward scattered light sensor.

[0197] Clause 53. The system of clause 51, wherein the trigger sensor is an axial light loss (ALL) channel sensor.

[0198] Addendum 54. A system according to any one of Addendums 51 to 53, wherein the processor is configured to set the event occurrence rate by selecting the sensitivity at which the trigger sensor observes the presence of particles and generates a trigger signal.

[0199] Addendum 55. A system described in any one of Addendums 51 to 54, wherein the processor is configured to calculate a trigger window based on the trigger signal, the trigger window providing a time during which a particle is expected to pass through a detection zone of the detector.

[0200] Clause 56. The system of clause 55, wherein the processor is configured to obtain a baseline noise level at a time outside the trigger window.

[0201] Addendum 57. The system of any one of Addendums 33 to 56, wherein the detector is a photomultiplier tube (PMT).

[0202] Addendum 58. The system of any one of Addendums 33 to 56, wherein the detector is an avalanche photodiode (APD).

[0203] Addendum 59. The system of any one of Addendums 33 to 56, wherein the detector is a photodiode (PD).

[0204] Addendum 60. The system of any one of Addendums 33 to 56, wherein the detector is a silicon photomultiplier (SiPM).

[0205] Addendum 61. The system of any one of Addendums 33 to 60, comprising a plurality of detectors.

[0206] Clause 62. The system of clause 61, wherein the processor is configured to determine an ideal gain for each of the plurality of detectors.

[0207] Addendum 63. A system according to any one of Addendums 33 to 62, comprising a flow cytometer.

[0208] Addendum 64. The system of Addendum 63, wherein the flow cytometer is a multi-color flow cytometer.

[0209] Addendum 65. The system of Addendum 63, wherein the flow cytometer is a spectral flow cytometer.

[0210] Addendum 66. The system of any one of Addendums 33 to 65, comprising a display for outputting the ideal gain.

[0211] Clause 67. Increasing the gain of the detector in steps such that the detector collects light from the illuminated flow stream at each of a plurality of successively increasing gains; obtaining a baseline noise level from the detector at each of a plurality of successively increasing gains; calculating a limit of detection (LoD) for each of a plurality of successively increasing gains based on the gain and a baseline noise level; Evaluate the calculated LoD to determine the ideal gain A non-transitory computer readable storage medium having stored thereon instructions for determining, by a method, an ideal gain for a detector in an optical detection system of a flow cytometer.

[0212] Addendum 68. The non-transitory computer-readable storage medium of Addendum 67, which generates a ratio between gain and baseline noise level when calculating the LoD.

[0213] Addendum 69. The non-transitory computer-readable storage medium of Addendum 68, wherein when calculating the LoD, the inverse of the ratio between the gain and the baseline noise level is taken.

[0214] Addendum 70. The non-transitory computer-readable storage medium of any one of Addendums 67-69, wherein when evaluating the calculated LoD, a LoD curve is generated that includes a calculated LoD for each of a plurality of successively increasing gains.

[0215] Clause 71. The non-transitory computer-readable storage medium of Clause 70, wherein when evaluating the calculated LoD, the LoD curve is evaluated for the presence of an inflection point.

[0216] Appendix 72. When evaluating a calculated LoD: Inflection points of the LoD curve, and Gain in multiple successively increasing gains, related to the LoD at the inflection point 72. The non-transitory computer-readable storage medium of claim 71,

[0217] Clause 73. The non-transitory computer-readable storage medium of Clause 72, wherein the method further comprises determining that a gain within the plurality of successively increasing gains that is associated with the LoD at an inflection point is an ideal gain.

[0218] Addendum 74. The non-transitory computer-readable storage medium of any one of Addendums 67-73, wherein the irradiated flow stream includes a buffer.

[0219] Addendum 75. The non-transitory computer-readable storage medium of any one of Addendums 67-74, wherein the irradiated flow stream comprises water.

[0220] Addendum 76. The non-transitory computer-readable storage medium of any one of Addendums 67-75, wherein the irradiated flow stream contains particles.

[0221] Clause 77. The non-transitory computer-readable storage medium of clause 76, wherein the method further comprises evaluating flow cytometer data associated with a plurality of different particle populations to determine an ideal gain.

[0222] Addendum 78. The non-transitory computer-readable storage medium of Addendum 77, wherein the plurality of particle populations includes a first particle population that is negative for a particular parameter and a second particle population that is positive for the same parameter.

[0223] Clause 79. The non-transitory computer-readable storage medium of clause 78, wherein the method further comprises obtaining a first signal magnitude and a second signal magnitude for each of the first particle population and the second particle population, respectively, at each of a plurality of successively increasing gains.

[0224] Clause 80. The non-transitory computer-readable storage medium of Clause 79, wherein the method estimates a magnitude of the first signal based on a baseline noise level obtained by the detector at each of a plurality of successively increasing gains.

[0225] Addendum 81. The non-transitory computer-readable storage medium of Addendum 79 or 80, wherein the method estimates a magnitude of the second signal based on each gain of a plurality of successively increasing gains.

[0226] Addendum 82. The non-transitory computer-readable storage medium of any one of Addendums 79 to 80, wherein the method includes obtaining a magnitude of a second signal from the detector.

[0227] Addendum 83. The non-transitory computer-readable storage medium of any one of Addendums 67 to 82, wherein the method further comprises calculating a difference between the magnitude of the second signal and the magnitude of the first signal obtained at each of a plurality of successively increasing gains.

[0228] 84. The non-transitory computer-readable storage medium of claim 83, wherein the method further comprises generating a linearity measure for assessing how the difference between the magnitude of the second signal and the magnitude of the first signal increases with increasing detector gain.

[0229] 85. The non-transitory computer-readable storage medium of claim 84, wherein the method further identifies a point of non-linearity where the difference between the magnitude of the second signal and the magnitude of the first signal does not increase linearly with increasing gain of the detector.

[0230] Clause 86. The non-transitory computer-readable storage medium of Clause 85, wherein the method determines a gain that is lower than a gain associated with a point of non-linearity to be an ideal gain.

[0231] Addendum 87. The non-transitory computer-readable storage medium of any one of Addendums 67 to 86, wherein the method further comprises terminating the incremental increase of the gain after determining the ideal gain.

[0232] Addendum 88. The non-transitory computer-readable storage medium of any one of Addendums 76 to 87, wherein the method sets the event occurrence rate by selecting the sensitivity at which the trigger sensor observes the presence of a particle and generates a trigger signal.

[0233] Clause 89. The non-transitory computer-readable storage medium of Clause 88, wherein the method further comprises setting a gain of the trigger sensor.

[0234] Addendum 90. The non-transitory computer-readable storage medium of Addendum 88 or 89, wherein the method further comprises calculating a trigger window based on the trigger signal, the trigger window providing a time when a particle is expected to pass through a detection zone of the detector.

[0235] Clause 91. The non-transitory computer-readable storage medium of Clause 90, wherein the method obtains a baseline noise level at a time outside the trigger window.

[0236] Addendum 92. The non-transitory computer-readable storage medium of any one of Addendums 67 to 91, for determining ideal gains for multiple detectors.

[0237] Addendum 93. A method for determining an ideal gain of a detector in an optical detection system, comprising: (a) a flow cell configured to carry particles in a flow stream; a light source for illuminating the flow stream at the interrogation point; a detector configured to collect light from the flow stream; a processor operatively connected to the detector, increasing the gain of the detector in steps such that the detector collects light from the flow stream at each of a plurality of successively increasing gains; obtaining a baseline noise level from the detector at each of a plurality of successively increasing gains; calculating a limit of detection (LoD) for each of a plurality of successively increasing gains based on the gain and a baseline noise level; Evaluate the calculated LoD to determine the ideal gain and a processor configured as introducing a particle sample into a system comprising: (b) receiving an ideal gain from the processor.

[0238] Addendum 94. The method of Addendum 93, wherein when calculating the LoD, a ratio between the gain and the baseline noise level is generated.

[0239] Addendum 95. The method of Addendum 94, wherein the LoD is calculated by taking the inverse of the ratio between the gain and the baseline noise level.

[0240] Addendum 96. The method of any one of Addendums 93 to 95, wherein when evaluating the calculated LoD, a LoD curve is generated that includes a calculated LoD for each of a plurality of successively increasing gains.

[0241] Addendum 97. The method of Addendum 96, wherein when evaluating the calculated LoD, the LoD curve is evaluated for the presence of an inflection point.

[0242] Appendix 98. When evaluating a calculated LoD: Inflection points of the LoD curve, and Gain in multiple successively increasing gains, related to the LoD at the inflection point 98. The method of claim 97, wherein the

[0243] Addendum 99. The method of any one of Addendums 93-98, wherein the processor is configured to evaluate flow cytometer data associated with a plurality of different particle populations to determine an ideal gain.

[0244] Clause 100. The method of clause 99, wherein the plurality of particle populations includes a first particle population that is negative for a particular parameter and a second particle population that is positive for the same parameter.

[0245] Addendum 101. The method of Addendum 100, wherein the processor is configured to obtain a first signal magnitude and a second signal magnitude for each of the first particle population and the second particle population, respectively, at each of a plurality of successively increasing gains.

[0246] Clause 102. The method of clause 101, wherein the processor is configured to estimate a magnitude of the first signal based on a baseline noise level obtained by the detector at each of a plurality of successively increasing gains.

[0247] Addendum 103. The method of any one of Addendum 101 to 102, wherein the processor is configured to estimate a magnitude of the second signal based on each of the plurality of successively increasing gains.

[0248] Addendum 104. The method of any one of Addendum 101 to 102, wherein the processor is configured to obtain a magnitude of the second signal from the detector.

[0249] Addendum 105. The method of any one of Addendums 101-104, wherein the processor is configured to calculate a difference between the magnitude of the second signal and the magnitude of the first signal obtained at each of a plurality of successively increasing gains.

[0250] Addendum 106. The method of Addendum 105, wherein the processor is configured to generate a linearity measure to assess how the difference between the magnitude of the second signal and the magnitude of the first signal increases with increasing detector gain.

[0251] Addendum 107. The method of Addendum 106, wherein the processor is configured to identify a point of nonlinearity where the difference between the magnitude of the second signal and the magnitude of the first signal does not increase linearly with increasing gain of the detector.

[0252] Clause 108. The method of clause 107, wherein the processor is configured to determine an ideal gain that is lower than the gain associated with the point of nonlinearity.

[0253] Addendum 109. The method of any one of Addendums 93-108, wherein the processor is configured to terminate incrementally increasing the gain after determining the ideal gain.

[0254] Addendum 110. The method of any one of Addendums 93 to 109, wherein the system further comprises a trigger sensor configured to observe the presence of a particle in the flow cell and generate a trigger signal.

[0255] Addendum 111. The method of Addendum 110, wherein the trigger sensor is a forward scattered light sensor.

[0256] Clause 112. The method of clause 110, wherein the trigger sensor is an axial light loss (ALL) channel sensor.

[0257] Addendum 113. The method of any one of Addendums 110-112, wherein the processor is configured to set the event occurrence rate by selecting a sensitivity at which the trigger sensor observes the presence of a particle and generates a trigger signal.

[0258] Addendum 114. The method of any one of Addendums 110 to 113, wherein the processor is configured to calculate a trigger window based on the trigger signal, the trigger window providing a time during which a particle is expected to pass through a detection zone of the detector.

[0259] Addendum 115. The method of Addendum 114, further comprising obtaining a baseline noise level at a time outside the trigger window.

[0260] Addendum 116. The method of any one of Addendums 93 to 115, wherein the detector is a photomultiplier tube (PMT).

[0261] Addendum 117. The method of any one of Addendums 93 to 115, wherein the detector is an avalanche photodiode (APD).

[0262] Addendum 118. The method of any one of Addendums 93 to 115, wherein the detector is a photodiode (PD).

[0263] Addendum 119. The method of any one of Addendums 93 to 115, wherein the detector is a silicon photomultiplier (SiPM).

[0264] Addendum 120. The method of any one of Addendums 93-119, wherein the system includes a plurality of detectors.

[0265] Clause 121. The method of clause 120, wherein the processor is configured to determine an ideal gain for each of the plurality of detectors.

[0266] Addendum 122. The method of any one of Addendums 93 to 121, wherein the system includes a flow cytometer.

[0267] Addendum 123. The method of Addendum 122, wherein the flow cytometer is a multi-color flow cytometer.

[0268] Addendum 124. The method of Addendum 122, wherein the flow cytometer is a spectral flow cytometer.

[0269] Addendum 125. The method of any one of Addendums 93-124, further comprising a display for outputting the ideal gain.

[0270] Although the foregoing invention has been described in some detail by way of illustration and example for ease of understanding, it will be readily apparent to those skilled in the art, in view of the teachings of the invention, that certain changes and modifications may be made thereto without departing from the spirit and scope of the appended claims.

[0271] Thus, the foregoing merely illustrates the nature of the invention. It is clear that those skilled in the art may devise various configurations that embody the nature of the invention and are within the spirit and scope of the invention, although not expressly described or shown herein. Furthermore, all examples and conditional language described herein are intended essentially to aid the reader in understanding the nature of the invention and the concepts given by the inventors to advance the art, and should not be construed as being limited to the examples and conditions specifically described as such. Furthermore, all descriptions herein that describe the nature, aspects, and embodiments of the invention, as well as specific examples of the invention, are intended to include both structural and functional equivalents of the invention. In addition, such equivalents are intended to include both currently known equivalents and equivalents developed in the future, i.e., all elements developed that perform the same function, regardless of structure. Furthermore, the descriptions disclosed herein are not intended to be publicly available, regardless of whether such disclosure is expressly set forth in the claims.

[0272] Therefore, it is not intended that the scope of the present invention be limited to the exemplary embodiments shown and described herein. Rather, the scope and spirit of the present invention is embodied in the appended claims. With respect to claims, 35 U.S.C. 112(f) or 35 U.S.C. 112(6) is expressly provided to be invoked with respect to a limitation in a claim only when the precise phrase "means for" or "step for" is recited at the beginning of such limitation in the claim, and if such precise phrase is not used in the limitation of the claim, 35 U.S.C. 112(f) or 35 U.S.C. 112(6) is not invoked.

[0273] CROSS-REFERENCE TO RELATED APPLICATIONS This application claims priority under 35 U.S.C. §119(e) of the filing date of U.S. Provisional Application No. 63 / 320,499, filed March 16, 2022, the disclosure of which is incorporated herein by reference in its entirety.

Claims

1. 1. A method for determining an ideal gain for a detector in an optical detection system of a flow cytometer, comprising: A light source is applied to the flow stream; increasing a gain of the detector in steps such that the detector collects light from the flow stream at each of a plurality of successively increasing gains; obtaining a baseline noise level from the detector at each of the plurality of successively increasing gains; calculating, for each of the plurality of successively increasing gains, a limit of detection (LoD) based on the gain and the baseline noise level; A method to evaluate the calculated LoD and determine the ideal gain.

2. The method of claim 1 , further comprising: generating a ratio of said gain to said baseline noise level when calculating LoD.

3. The method of claim 2 , wherein the LoD is calculated by taking the inverse of the ratio of the gain to the baseline noise level.

4. The method according to any one of claims 1 to 3, further comprising generating an LoD curve comprising a calculated LoD for each of said plurality of successively increasing gains when evaluating the calculated LoDs.

5. The method of claim 4 , wherein when evaluating the calculated LoD, the LoD curve is evaluated for the presence of an inflection point.

6. The method of claim 5 , further comprising identifying an inflection point of the LoD curve and a gain within a plurality of successively increasing gains that is associated with the LoD at the inflection point when evaluating the calculated LoD.

7. The method of claim 6 , further comprising determining a gain within a plurality of successively increasing gains associated with the LoD at the inflection point to be an ideal gain.

8. The method of any one of claims 1 to 7, wherein the flow stream comprises a buffer.

9. The method of any one of claims 1 to 8, wherein the flow stream comprises water.

10. The method of any one of claims 1 to 9, wherein the flow stream comprises particles.

11. The method according to any one of claims 1 to 10, wherein the stepwise increase of the gain is terminated after determining the ideal gain.

12. The method according to any one of claims 1 to 11, wherein the detector is a photomultiplier tube (PMT), an avalanche photodiode (APD), a photodiode (PD) or a silicon photomultiplier (SiPM).

13. The method of any one of claims 1 to 12, further comprising determining ideal gains for a plurality of detectors.

14. a flow cell configured to carry a flow stream; a light source for illuminating the flow stream at the interrogation point; a detector configured to collect light from the flow stream; a processor operatively connected to the detector, increasing a gain of the detector in steps such that the detector collects light from the flow stream at each of a plurality of successively increasing gains; obtaining a baseline noise level from the detector at each of a plurality of successively increasing gains; calculating, for each of a plurality of successively increasing gains, a limit of detection (LoD) based on said gains and said baseline noise level; Evaluate the calculated LoD to determine the ideal gain The processor configured to The system comprises:

15. 1. A method for determining an ideal gain for a detector in an optical detection system, comprising: (a) a flow cell configured to carry particles in a flow stream; a light source for illuminating the flow stream at the interrogation point; a detector configured to collect light from the flow stream; a processor operatively connected to the detector, increasing a gain of the detector in steps such that the detector collects light from the flow stream at each of a plurality of successively increasing gains; obtaining a baseline noise level from the detector at each of a plurality of successively increasing gains; calculating, for each of a plurality of successively increasing gains, a limit of detection (LoD) based on said gains and said baseline noise level; Evaluate the calculated LoD to determine the ideal gain The processor configured to introducing a particle sample into a system comprising: (b) receiving the ideal gains from the processor.

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