Quantitative flow cytometry light scatter detector alignment

Abstract

To provide a method for determining alignment adjustment for a light scatter detector system of a flow cytometer.SOLUTION: A method of interest include: generating contrast data by a flow cytometer; determining a quantitative metric of alignment for a light scatter detector system based on the contrast data; and determining the alignment adjustment for the light scatter detector system based on a quantitative alignment metric. In some embodiments, the subject method further includes adjusting the light scatter detector system based at least in part on the alignment adjustment by performing, e.g., a hardware or software alignment adjustment. The subject method may be implemented automatically via a computer. A system, a non-transitory computer-readable storage medium, and a kit for carrying out the subject methods are also provided.SELECTED DRAWING: Figure 1A

Description

[Background technology]

[0001] Characterization of analytes in biological fluids has become an important part of biological research, medical diagnosis, and the assessment 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 can play a role in determining treatment protocols for patients with various disease states.

[0002] Flow cytometry is a technique used to characterize and often sort particles of interest, such as cells in a blood sample. A flow cytometer typically includes a sample reservoir for receiving a fluid sample, such as a blood sample, and a sheath reservoir that contains a sheath fluid. The flow cytometer directs the sheath fluid toward the flow cell while transporting particles (including cells) in the fluid sample as a particle stream toward the flow cell.

[0003] To characterize the components of a flow stream, the flow stream is illuminated with light. Variations in materials within the flow stream, such as the form or presence of fluorescent labels, can cause variations in the observed light, allowing for characterization and separation. Separation of particles of interest can be achieved by adding sorting or collection capabilities to the flow cytometer. For example, particles in the separated stream that are detected as having one or more desired properties may be individually isolated from the sample stream by mechanical or electrical removal.

[0004] To characterize particles in a flow stream, light must impinge on the flow stream and be collected. The light source for a flow cytometer can vary 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 the optical response from the illuminated particles is collected and quantified. For example, particles in fluid suspension may be exposed to excitation light as they pass through an interrogation region, and the particles' light scattering and fluorescence properties may be measured. Particles or their components are typically labeled with fluorescent dyes for ease of detection. Multiple different particles or components may be detected simultaneously by using spectrally distinct fluorescent dyes to label different particles or components. In some implementations, the flow cytometer includes multiple detectors, one for each scattering parameter to be measured and one or more for each distinct dye to be detected. The acquired data includes the signals measured by each light scattering detector and fluorescence detector.

[0005] A flow cytometer may further include a means for recording the measured data and analyzing the 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 for one particle and each column corresponding to each measured parameter. The use of a standard file format, such as the "FCS" file format, for storing data from a flow cytometer facilitates analysis of the data using separate programs and / or machines. Using current analysis methods, the data is typically displayed as a one-dimensional histogram or a two-dimensional (2D) plot for ease of visualization, although other methods may be used to visualize the data.

[0006] Data obtained from the analysis of cells (or other particles) by flow cytometry is often multidimensional, with each cell corresponding to a point in a multidimensional space defined by the measured parameters. Populations of cells or particles can be identified as clusters of points in the data space. Identification of clusters, and therefore populations, can be performed manually by drawing gates around the displayed populations in one or more two-dimensional plots, called "scatter plots" or "dot plots," of the data. Alternatively, population clusters can be identified, and gates defining the limits of the populations can be determined automatically. Examples of automated gating methods are described in, for example, U.S. Patent Nos. 4,845,653, 5,627,040, 5,739,000, 5,795,727, 5,962,238, 6,014,904, and 6,944,338, and U.S. Patent Publication No. 2012 / 0245889, each of which is incorporated herein by reference. Gating is used to make sense of the large amount of data that can be generated from a sample.

[0007] Parameters measured using a flow cytometer typically include forward scatter (FSC), which is light at the excitation wavelength scattered by particles at a narrow angle along a roughly forward direction; side scatter (SSC), which is excitation light scattered by particles in a direction orthogonal to the excitation laser; and light emitted from fluorescent molecules in one or more detectors that measure signals across a specific range of spectral wavelengths. Various cell types can be distinguished by their light-scattering characteristics and fluorescence emissions resulting from labeling various cellular proteins or other components with fluorochrome-conjugated antibodies or other fluorescent probes. To ensure a relatively high signal-to-noise ratio, both the FSC and SSC detectors must be aligned to achieve optimal light collection from interrogated particles in the flow cytometer's sample stream. Scatter detectors (i.e., FSC and SSC detectors) are typically manually aligned by a field service engineer, who adjusts the various optical components associated with a given detector to maximize the signal generated by the detector for a set of relatively large (e.g., >3 micron) calibration beads. This is known as detector "peaking." Summary of the Invention

[0008] The inventors have recognized that the process of aligning a flow cytometer light scatter detector system can be improved. In particular, it has been recognized that detector alignment by peaking can be time-consuming and disruptive, as well as relatively inconsistent due to, for example, inherent reliance on the knowledge and skill of a given field service engineer to manually adjust the detector system. This results in reduced accuracy and makes it difficult to compare light scatter data obtained from different instruments, or even the same instrument after alignment by different field service engineers. Therefore, a process for deriving quantitative metrics of light scatter collection alignment is desirable. In particular, an automated process is needed to generate quantitative metrics of light scatter detector system alignment and subsequently automatically adjust the light scatter detector system (e.g., to optimize light collection for each detector in the system) based on the quantitative metrics. Furthermore, quantitative alignment metrics may be generated after such automatic adjustment of the light scatter detector system has occurred, for example, to further align the detector system or to aid in the comparison of data generated by different instruments and systems. Embodiments of the present disclosure meet these needs and desires.

[0009] Aspects of the present disclosure include methods for determining an alignment adjustment of a light scatter detector system of a flow cytometer. The subject methods include generating control data by a flow cytometer, determining a quantitative metric of the alignment of the light scatter detector system based on the control data, and determining an alignment adjustment of the light scatter detector system based on the quantitative alignment metric. In some embodiments, determining the quantitative alignment metric includes calculating a collection angle based on the control data. In these cases, the collection angle may be calculated relative to an interrogation point of the flow cytometer. In some embodiments, the collection angle is calculated using a light scatter model, such as the Mie light scatter model. In some embodiments, the light scatter detector system includes a side scatter detector, a forward scatter detector, or both.

[0010] In certain embodiments, generating the control data includes illuminating beads with a flow cytometer and measuring data signals generated by a light scattering detector system. In some embodiments, the control data is generated for a plurality of beads, the plurality of beads including a first bead and a second bead larger than the first bead. In some embodiments, the plurality of beads has a diameter between 50 nm and 3000 nm, e.g., a diameter between 100 nm and 1200 nm. In some embodiments, the plurality of beads includes polystyrene. In some embodiments, the plurality of beads includes fluorescent beads.

[0011] In certain embodiments, the method further includes providing alignment adjustments to a user. In some embodiments, the alignment adjustments include software alignment adjustments. For example, the software alignment adjustments may include collection angle calibration values, trigger thresholds, trigger channel options, detector setting options, pulse processing options, or any combination thereof. In some embodiments, the alignment adjustments include hardware alignment adjustments. In these examples, the hardware alignment adjustments may include aperture adjustment distances, aperture adjustment angles, detector adjustment distances, detector adjustment angles, or any combination thereof.

[0012] In certain embodiments, the method further includes adjusting the light scatter detector system based at least in part on the alignment adjustment. In some embodiments, adjusting the light scatter detector system includes performing a software alignment adjustment. In these examples, the software alignment adjustment may include adjusting a collection angle calibration value, a trigger threshold, a trigger channel option, a detector setting option, a pulse processing option, or any combination thereof. In some embodiments, adjusting the light scatter detector system includes performing a hardware alignment adjustment. In these cases, the hardware alignment adjustment may include adjusting the position and / or orientation of an optical alignment component of the flow cytometer. For example, the hardware alignment adjustment may include adjusting the position and / or orientation of an aperture and / or a filter of the flow cytometer. In some embodiments, the hardware alignment adjustment may include adjusting the position and / or orientation of a light scatter detector of the light scatter detector system.

[0013] Aspects of the present disclosure also include systems for implementing methods for determining alignment adjustments for a light scatter detector system of a flow cytometer, e.g., as described above and herein. Systems of interest include a light scatter detector system configured to generate data signals from light received from an interrogation point of the flow cytometer, and a processor, the processor including a memory operatively coupled to the processor and having instructions stored in the memory that, when executed by the processor, cause the processor to generate control data with the flow cytometer, determine a quantitative metric for the alignment of the light scatter detector system based on the control data, and determine an alignment adjustment for the light scatter detector system based on the quantitative alignment metric. Aspects of the present disclosure further include a non-transitory computer-readable storage medium having stored thereon instructions for determining alignment adjustments for the light scatter detector system of a flow cytometer, and a kit including the non-transitory computer-readable storage medium and / or a set of submicron standard beads for determining alignment adjustments, e.g., as described above and herein.

[0014] The present disclosure can be best understood from the following detailed description when read in conjunction with the accompanying drawings, which include the following figures: [Brief explanation of the drawings]

[0015] [Figure 1A] 1 is a flow diagram for implementing a method for determining alignment adjustments for a light scatter detector system of a flow cytometer, according to certain embodiments. [Figure 1B] 1 is a flow diagram for implementing a method for determining alignment adjustments for a light scatter detector system of a flow cytometer, according to certain embodiments. [Figure 2] FIG. 1 is a diagram of a method for determining alignment adjustments for a light scatter detector system of a flow cytometer according to one embodiment of the present disclosure. [Figure 3]10A-10C illustrate several methods for adjusting a light scatter detector system of a flow cytometer based on determined alignment adjustments, according to one embodiment of the present disclosure. [Figure 4] FIG. 1 is a functional block diagram of an exemplary flow cytometer control system used to implement certain embodiments of the alignment adjustment determination method of the present disclosure. [Figure 5] FIG. 1 is a block diagram of a computing system for use in certain embodiments of the alignment adjustment determination method of the present disclosure. [Figure 6] FIG. 1 is a schematic diagram of an exemplary flow cytometer system for use in certain embodiments of the alignment adjustment determination method of the present disclosure. [Figure 7] FIG. 1 is a schematic diagram of an exemplary flow cytometer system for use in certain embodiments of the alignment adjustment determination method of the present disclosure. [Figure 8] FIG. 1 is a functional block diagram of a flow cytometer system for use in certain embodiments of the alignment adjustment determination method of the present disclosure. [Figure 9] FIG. 1 is a diagram of an exemplary flow cytometer system for use in certain embodiments of the alignment adjustment determination method of the present disclosure. [Figure 10A] FIG. 1 is a diagram of an exemplary sorting flow cytometer and data processing technique for fluorescent imaging using radio frequency tagged emissions for use in certain embodiments of the alignment adjustment determination method of the present disclosure. [Figure 10B] FIG. 1 is a diagram of an exemplary sorting flow cytometer and data processing technique for fluorescent imaging using radio frequency tagged emissions for use in certain embodiments of the alignment adjustment determination method of the present disclosure. DETAILED DESCRIPTION OF THE INVENTION

[0016] The present disclosure provides methods for determining an alignment adjustment of a light scatter detector system of a flow cytometer. The subject methods include generating control data with a flow cytometer, determining a quantitative metric of the alignment of the light scatter detector system based on the control data, and determining an alignment adjustment of the light scatter detector system based on the quantitative alignment metric. In some embodiments, the subject methods further include adjusting the light scatter detector system based at least in part on the alignment adjustment, for example, by performing a hardware or software alignment adjustment. The subject methods may also be implemented automatically via a computer. Systems, non-transitory computer-readable storage media, and kits for performing the subject methods are also provided.

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

[0018] When a range of values ​​is presented, unless the context clearly dictates otherwise, it is understood that each intervening value, to the tenth of the unit of the lower limit, between the upper and lower limits of that range, and any other stated or intervening value in that stated range, is encompassed within the disclosure. The upper and lower limits of these smaller ranges may independently be included in the smaller ranges, and are also encompassed within the disclosure, 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 included in the disclosure.

[0019] Certain ranges are described herein by numerical values ​​preceded by the term "about." The term "about" is used herein to literally support the exact number it precedes, as well as a number that is near or approximately the number preceded by the term. In determining whether a number is near or approximately a specifically stated number, a number not stated to be near or approximately may be a number that, in the context in which it is presented, represents the substantial equivalent of 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 disclosure belongs. Although any methods and materials similar or equivalent to those described herein can also be used in the practice or testing of this disclosure, representative exemplary methods and materials are now described.

[0021] All publications and patents cited herein are incorporated by reference to disclose and describe the methods and / or materials for which the publications are cited, as if each individual publication or patent was specifically and individually indicated to be incorporated by reference. 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 disclosure is not entitled to antedate such publication by virtue of prior disclosure. 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. Accordingly, this statement is intended to serve as a predicate for use of exclusive terminology, such as "solely," "only," and the like, in connection with the recitation of claim elements or the use of a "negative" limitation.

[0023] As will be apparent to those skilled in the art upon reading this disclosure, each of the individual embodiments described and illustrated herein has discrete components and features that may be readily separated from or combined with the features of any of the other several embodiments without departing from the scope or spirit of the disclosure. Any recited method can be carried out in the order of events recited or in any other order that is logically possible.

[0024] While the systems and methods are described for grammatical fluidity with functional descriptions, it is to be clearly understood that the claims should not be construed as necessarily limited by "means" or "step" limitation constructions unless expressly formulated under 35 U.S.C. § 112, but rather should be given the full scope of meaning and equivalents of the definitions provided by the claims under the doctrine of equivalents, and that if a claim is expressly formulated under 35 U.S.C. § 112, then the full statutory equivalents under 35 U.S.C. § 112 should be given.

[0025] How to determine alignment adjustments As summarized above, methods are provided for determining an alignment adjustment of a light scatter detector system of a flow cytometer. Aspects of the method include generating control data by a flow cytometer, determining a quantitative metric for the alignment of the light scatter detector system based on the control data, and determining an alignment adjustment of the light scatter detector system based on the quantitative alignment metric. In some embodiments, the subject methods further include adjusting the light scatter detector system based at least in part on the alignment adjustment, e.g., by implementing a hardware or software alignment adjustment. The subject methods may be computer-implemented, e.g., because the subject methods are particularly suited to automated implementation via a computer. For example, the subject methods for adjusting a light scatter detector system of a flow cytometer may be implemented automatically via a computer, e.g., through electronic control of one or more of the adjustable alignment components (e.g., collection aperture and / or lens) described herein.

[0026] In some embodiments, determining the quantitative alignment metric includes calculating a collection angle based on the control data. Collection angle refers to, for example, the solid angle of scattered light transmitted to a given light scatter detector by the light collection components (e.g., collection lens and / or collection aperture) of a given light scatter detector. In some embodiments, the collection angle is calculated relative to an interrogation point of the flow cytometer. In other words, a measure of the amount of the field of view of the interrogation point captured by a given light scatter detector may be calculated. In some embodiments, the collection angle is calculated using a light scatter model, such as the Mie light scatter model. In some embodiments, the light scatter detector system includes a side scatter detector, a forward scatter detector, or both.

[0027] In certain embodiments, generating the control data includes illuminating beads in a flow cytometer and measuring a data signal generated by a light scattering detector system. In these cases, the data signal may be generated from light scattered by the illuminated beads, e.g., at the interrogation point of the flow cytometer. In some embodiments, the control data is generated for a plurality of beads, including a first bead and a second bead larger than the first bead. In some embodiments, the beads used to generate the control data include beads of three or more different sizes, e.g., four or more different sizes, six or more different sizes, or ten or more different sizes. In some embodiments, the control beads include beads of six different sizes. The control beads (i.e., the beads illuminated, e.g., at the interrogation point of the flow cytometer to generate the control data) may have a diameter between 50 nm and 3000 nm. In some embodiments, the control beads have a diameter of 50 nm to 2000 nm, or 50 nm to 1500 nm, or 50 nm to 1200 nm, or 100 nm to 3000 nm, or 150 nm to 3000 nm, or 200 nm to 3000 nm, or 100 nm to 1500 nm, or 100 nm to 1200 nm. In some embodiments, the control beads include six different sized beads with diameters of 100 nm to 1200 nm. In some embodiments, the control beads all have the same refractive index. In other embodiments, the control beads include beads with different refractive indices, for example, beads with two or more different refractive indices. In some embodiments, the control beads include polystyrene. For example, the control beads may include six different sized polystyrene beads with diameters of 100 nm to 1200 nm. In some embodiments, the control beads include fluorescent beads. For example, the control beads may include six different sizes of polystyrene beads with diameters ranging from 100 nm to 1200 nm and one type of fluorescent bead (i.e., the control beads may include seven different types of beads).

[0028] In some embodiments, a quantitative metric (and, e.g., alignment adjustment) is determined for the light scattering detector (i.e., light scattering detector system) that generated the data signal from the control beads. In some cases, the light scattering detector system includes multiple light scattering detectors, and the control data includes measurement data signals generated by each of the scatter detectors for each control bead. In some embodiments, a quantitative metric of alignment is determined for each light scattering detector that generated the control data from the beads. In some cases, a quantitative metric of alignment is determined for a light scattering detector from control data generated by a different light scattering detector of the system. For example, a quantitative alignment metric may be determined for a first light scattering detector from control data generated by a second (i.e., different) light scattering detector of the system that shares one or more of the same light collection components (e.g., the same collection lens and / or collection aperture, etc.) with the first light scattering detector. In some cases, a quantitative alignment metric is determined for a first light scattering detector from control data generated by the first light scattering detector and control data generated by a second scatter detector that receives scattered light at a different angle. For example, a quantitative alignment metric may be determined for a side scatter (SSC) detector from control data generated by the side scatter detector and control data generated by a forward scatter (FSC) detector.

[0029] As described above, determining the quantitative alignment metric may include calculating a collection angle based on the control data using a Mie light scattering model. In some embodiments, the quantitative alignment metric (e.g., collection angle) is calculated using the method described by Welsh et al. ("FCM PASSThe quantitative alignment metric is calculated using techniques disclosed in "Software Aids Extracellular Vesicle Light Scatter Standardization," Cytometry A. 2020;97(6):569-581. In some embodiments, the quantitative alignment metric is determined by comparing measurements of the generated data signals of the control data with predicted measurements generated using a Mie light scattering model. In some cases, the quantitative alignment metric is determined by comparing the collection angle calculated from the control data (e.g., using a Mie light scattering model) with an ideal or desired collection angle. In some cases, the quantitative alignment metric is determined by calculating the ratio of measurements generated by a first scatter detector (e.g., an SSC detector) to measurements generated by a second scatter detector (e.g., an FSC detector) and comparing the ratio to a predicted ratio generated using a Mie light scattering model.

[0030] In some embodiments, the alignment adjustment of the light scatter detector is determined from a single quantitative alignment metric. In other examples, the alignment adjustment of the light scatter detector is generated from two or more different quantitative alignment metrics. In some embodiments, determining the alignment adjustment includes determining a first quantitative alignment metric for a first scatter detector, determining a second quantitative alignment metric for a second scatter detector, and determining an alignment adjustment for the first detector and / or the second detector based on the first quantitative alignment metric and the second quantitative alignment metric. In some cases, the first detector is an SSC detector and the second detector is an FSC detector. In some cases, both the first detector and the second detector are SSC detectors or FSC detectors, and both detectors share one or more of the same light collection components (e.g., the same collection lens and / or collection aperture, etc.).

[0031] In some embodiments, both the light scattering detector and the fluorescence detector share one or more of the same light collection components, such as, for example, the same light collection aperture. In other words, the light scattering detector receives scattered light through the aperture, and the fluorescence detector receives fluorescent light through the aperture. In these embodiments, adjusting the alignment may include moving the aperture to optimize the light scattering detector alignment and the fluorescence detector alignment. In some embodiments, the light that passes through the aperture is filtered before being received by the light scattering detector. In some embodiments, the light scattering detector and the fluorescence detector have separate optical collection paths (i.e., the scattered light may be collected separately from the fluorescent light).

[0032] In some embodiments, multiple light scatter detectors for wavelengths of light share one or more of the same light collection components, such as the same light collection aperture. In some cases, the multiple scatter detectors include scatter detectors of varying sensitivity. For example, a light collection component (i.e., a collection path for scattered light) may transmit light to multiple light scatter detectors, including a first light scatter detector and a second light scatter detector with a higher sensitivity than the first light scatter detector. In these embodiments, a quantitative alignment metric and / or alignment adjustment may be generated for the higher sensitivity (or, e.g., most sensitive) scatter detector of the multiple scatter detectors that share the same light collection component. A lower sensitivity scatter detector (i.e., multiple scatter detectors that share the same light collection component) may then be calibrated or adjusted based on the quantitative alignment metric and / or alignment adjustment generated by the higher sensitivity (or, e.g., most sensitive) scatter detector of the multiple scatter detectors. In this manner, a quantitative alignment metric (e.g., collection angle) may be determined for a relatively lower sensitivity light scatter detector for which such a metric cannot normally be calculated. In some embodiments, at least one FSC detector in the FSC light collection path (i.e., receiving light from one or more light collection components forming the optical path of the FSC light) has a sensitivity limit of 500 nm or less, e.g., 400 nm or less, or 300 nm or less. In some embodiments, at least one SSC detector in the SSC light collection path (i.e., receiving light from one or more light collection components forming the optical path of the SSC light) has a sensitivity limit of 200 nm or less, e.g., 100 nm or less, or 50 nm or less.

[0033] In certain embodiments, the determined alignment adjustments for the light scattering detector system (e.g., alignment adjustments determined for the detectors of the light scattering detector system as described above and herein) are manually performed by a user (e.g., a field service engineer). In these examples, the method (e.g., when implemented via a computer) may further include providing the alignment adjustments to the user. In some embodiments, the alignment adjustments provided to the user include software alignment adjustments. For example, the software alignment adjustments provided to the user may include collection angle calibration values, trigger thresholds, trigger channel options, detector setting options, pulse processing options, or any combination thereof. In some embodiments, the alignment adjustments provided to the user include hardware alignment adjustments. In these examples, the hardware alignment adjustments may include aperture adjustment distance, aperture adjustment angle, detector adjustment distance, detector adjustment angle, or any combination thereof.

[0034] In certain embodiments, the method further includes adjusting the light scatter detector system based at least in part on the determined alignment adjustment. In some embodiments, adjusting the light scatter detector system includes performing a software alignment adjustment. In these examples, the software alignment adjustment may include adjusting a collection angle calibration value, a trigger threshold, a trigger channel option, a detector setting option, a pulse processing option, or any combination thereof. In some embodiments, adjusting the light scatter detector system includes performing a hardware alignment adjustment. In these cases, the hardware alignment adjustment may include adjusting the position and / or orientation of an optical alignment component of the flow cytometer. For example, the hardware alignment adjustment may include adjusting the position and / or orientation of an aperture and / or a filter of the flow cytometer. In some embodiments, the hardware alignment adjustment includes adjusting the position and / or orientation of a light scatter detector of the light scatter detector system. In some embodiments, the adjustment is performed automatically, for example, via a computer.

[0035] In some embodiments, a feedback loop including one or more of the steps described above and herein (i.e., generating control data, determining a quantitative alignment metric, determining alignment adjustments, and adjusting the light scatter detector system) is implemented, e.g., via a computer, to optimize the alignment and calibration of one or more scatter detectors of the light scatter detector system. In some embodiments, the feedback loop is implemented continuously. In some cases, the feedback loop is implemented until a desired quantitative alignment metric is reached. For example, the aperture of one or more SSC detectors may be adjusted (e.g., via multiple separate adjustments) until a collection angle within a predetermined collection angle value threshold (e.g., as described above) is calculated for the SSC detector from the control beads.

[0036] In some embodiments, the methods described above and herein are used to reduce variation across different flow cytometers. In some embodiments, the determined quantitative alignment metric is used to compare data generated by different flow cytometers. For example, the latest quantitative alignment metric calculated for a given scatter detector may be associated with sample data generated by the detector and used to normalize the data, e.g., when comparing it with data generated by a detector of a different flow cytometer. In some embodiments, after alignment adjustments are performed (e.g., as described above and herein), the scatter detector of the light scatter detector system is used to identify extracellular vesicles or specific cell populations in a biological sample. In some embodiments, the aligned detector is used to derive the diameter and / or refractive index of small particles in the sample. In some embodiments, the aligned detector is used to sort particles in the sample.

[0037] FIG. 1A is a flow diagram for implementing a method for determining alignment adjustments for a light scatter detector system of a flow cytometer according to certain embodiments of the present disclosure. In step 101, control data is generated by the flow cytometer. The control data may be generated by irradiating a set of control beads (e.g., including six differently sized polystyrene beads with diameters ranging from 100 nm to 1200 nm and one type of fluorescent bead) with the flow cytometer and measuring data signals generated by the light scatter detector system. In some cases, at least one detector per collection path (e.g., at least one FSC detector and at least one SSC detector) generates measured data signals for the control data. In step 102, a quantitative metric of alignment is determined for the light scatter detector system based on the control data. In some cases, the quantitative metric is determined for each alignment of the light scatter detector system that may require adjustment (e.g., for each collection path of the system or for each scatter detector). The quantitative alignment metric may be determined by calculating the collection angle using the Mie light scatter model. In step 103, an alignment adjustment for the light scattering detector system is determined based on the at least one determined quantitative alignment metric. The alignment adjustment may be a software alignment adjustment or a hardware alignment adjustment.

[0038] FIG. 1B is a flow diagram for implementing a method for determining an alignment adjustment of a light scatter detector system of a flow cytometer according to certain embodiments of the present disclosure. FIG. 1B includes the same elements as FIG. 1A but adds step 104 of adjusting the light scatter detector system based at least in part on the alignment adjustment and performing one or more of steps 101-104 again (arrow 105). Adjusting the light scatter detector system (step 104) may include performing a software alignment adjustment and / or a hardware alignment adjustment. In some embodiments, after the light scatter detector system is adjusted in step 104, additional control data is generated to determine another quantitative alignment metric. In some cases, the new quantitative alignment metric is not within a predetermined alignment metric value threshold, and steps 103 and 104 may be performed again using the new quantitative alignment metric. In other cases, the new quantitative alignment metric is within a predetermined alignment metric value threshold. In these instances, the novel quantitative alignment metrics may be stored, for example, to normalize data subsequently obtained from biological samples using the aligned light scattering detector system.

[0039] Perform alignment adjustment As mentioned above, the methods of the present disclosure may further include adjusting the light scattering detector system based at least in part on the determined alignment adjustment (e.g., as described above and herein). In some embodiments, the adjustment is performed manually by a user. In other embodiments, the adjustment is performed automatically via a computer.

[0040] In some embodiments, adjusting the light scatter detector system includes performing a software alignment adjustment. In these examples, the software alignment adjustment may include adjusting a collection angle calibration value, a trigger threshold, a trigger channel option, a detector setting option, a pulse processing option, or any combination thereof. In some embodiments, the software alignment adjustment includes adjusting a collection angle calibration value. For example, the detector's collection angle may be determined to calibrate the detector, as the detector's collection angle determines the amount or intensity of scattered light received by the detector. In some embodiments, the software alignment adjustment includes adjusting a trigger threshold. In these embodiments, the trigger threshold may be that of a flow cytometer gate used for sorting. As used herein, a "gate" generally refers to a classifier boundary (e.g., including a threshold) that identifies a subset of data of interest. In other words, a gate is a numerical or graphical boundary that can be used to define the characteristics of particles to include for further analysis. In flow cytometry, a gate may combine a group of events or data points of particular interest. The boundaries (i.e., thresholds) of the flow cytometry gate may be defined by a vertex or set of coordinates in the data space of the dataset (e.g., the data space of a portion of the flow cytometry data). In some embodiments, the software alignment adjustment includes adjusting a trigger channel option, e.g., the channel of the flow cytometer used to trigger a sorting decision.

[0041] In some embodiments, adjusting the light scatter detector system includes performing a hardware alignment adjustment. In these examples, the hardware alignment adjustment may include adjusting the position and / or orientation of an optical adjustment component of the flow cytometer. "Optical adjustment" means that light is modified or adjusted as it propagates through a component. For example, an optical adjustment component may collimate a light beam, change the profile of a light beam, change the focus of a light beam, change the direction of light beam propagation, etc. An optical adjustment component may be any convenient device or structure that provides the desired modification or adjustment and may include, but is not limited to, a lens, a mirror, a beam splitter, a collimating lens, an aperture, a pinhole, a slit, a grating, an optical refractor, and any combination thereof. An optical adjustment component may be a component in the light path of a given scatter detector, such as a light collection component used to collect light for the scatter detector. For example, the hardware alignment adjustment may include adjusting the position and / or orientation of an aperture and / or a filter used to collect light for the FSC or SSC detector of the light scatter detector system. In some embodiments, the hardware alignment adjustment comprises adjusting the position and / or orientation of a light scatter detector of a light scatter detector system, hi some embodiments, the hardware alignment adjustment comprises adjusting the settings of an optical alignment component, such as, for example, the size of an aperture used to collect light of one or more scatter detectors.

[0042] In some embodiments, the position and / or orientation of the light scattering detector and / or optical adjustment components are adjusted using a configurable or adjustable stage, such as, for example, an electronically adjustable (e.g., via electric motors) x-stage, y-stage, and / or z-stage. In some embodiments, each collection path (e.g., the FSC path and the SSC path) of the light scattering detector system is separate, and each separate path is mounted on an electronically adjustable xyz stage. For example, the FSC and SSC detector light paths may be separate from the fluorescence collection, and each path may be mounted on an electronically adjustable stage.

[0043] FIG. 2 illustrates a method for determining alignment adjustments for a light scatter detector system of a flow cytometer according to one embodiment of the present disclosure. In FIG. 2, a nanoparticle bead set is introduced into a flow cytometer system (e.g., including a light scatter detection system) to generate control data. Software analysis is then performed on the control data, where the software analysis includes one or more of automatic gating, Mie modeling, collection angle derivation, collection angle fit determination, calibration factor determination, etc. The calibration factors determined via the software analysis may be used to calibrate data scaling, reduce intra-platform variability, and / or determine quantitative metrics of alignment. The software analysis may also be used to determine hardware adjustments, including, but not limited to, adjustments to trigger thresholds, trigger channel options, detector settings, pulse processing options, aperture alignment, or any combination thereof. The hardware adjustments may be performed or implemented manually or automatically, for example, via one or more of the electronically adjustable components described above or herein. In some cases, the hardware adjustments are performed to achieve optimal alignment of the light scatter detection system.

[0044] FIG. 3 illustrates several methods for adjusting a light scatter detector system of a flow cytometer based on a determined alignment adjustment, according to one embodiment of the present disclosure. In some cases, both scattered light and fluorescent light are propagated through the same adjustable aperture, and the adjustable aperture is moved to optimize alignment with both the light scatter detector and the fluorescent detector. In other examples, only scattered light is propagated through the adjustable aperture, and the adjustable aperture is moved to optimize alignment with only the light scatter detector. In some embodiments, detector calibration is performed separately for each detector in the light scatter detector system. In other embodiments, the light collection component (i.e., the scattered light collection path) transmits light to multiple light scatter detectors, including, for example, a first light scatter detector and a second light scatter detector with higher sensitivity than the first light scatter detector. In these embodiments, detector calibration of the first light scatter detector may be performed based on data generated by the second light scatter detector.

[0045] Flow cytometry In certain embodiments, the method includes data acquisition, analysis, and recording, such as by a computer, in which multiple data channels record data from each detector for light scattering and fluorescence emitted by each particle in the sample as it passes through the sample interrogation region of the flow cytometer. In these embodiments, analysis may include classifying and counting particles so that each particle is represented as a set of digitized parameter values. The subject system may be configured to trigger on selected parameters to distinguish particles of interest from background and noise. "Triggering" refers to a preset threshold for detection of a parameter and may be used as a means for detecting particles passing through a light source. Detection of an event exceeding a threshold for the selected parameter triggers acquisition of light scattering and fluorescence data for the particle. Data is not acquired for particles or other components in the medium being assayed that cause a response below the threshold. The trigger parameter may be detection of forward scattered light caused by a particle passing through a light beam. The flow cytometer then detects and collects the light scattering and fluorescence data for the particle. The data recorded for each particle is analyzed in real time or, as desired, stored in a data storage and analysis means, such as a computer.

[0046] The subject methods may further include sorting particles in the sample via a sorting flow cytometer based on the classification. Stated differently, particles corresponding to flow cytometer data may be sorted into a series of collection vessels based on the classification status determined by the processes described herein. For example, a method embodiment may include sorting particles associated with a first set of flow cytometer data into a first collection vessel, sorting particles associated with a second set of flow cytometer data into a second collection vessel, and so on. In certain instances, sorted particles may be considered "borderline" cases that are not properly classified, potentially having a sufficient number of particles of interest such that discarding them is undesirable. Certain embodiments further include re-sorting particles to obtain a high yield of particles of interest.

[0047] Suitable collection vessels for collecting particles include, but are not limited to, test tubes, conical tubes, multi-compartment vessels such as microtiter plates (e.g., 96-well plates), centrifuge tubes, culture tubes, microtubes, caps, cuvettes, bottles, distortion-corrected polymer vessels and bags, among other types of vessels. Particles may be sorted into any convenient number of collection vessels, such as, for example, two or more collection vessels, three or more collection vessels, four or more collection vessels, five or more collection vessels, six or more collection vessels, seven or more collection vessels, etc.

[0048] In some cases, the sample analyzed in the present method is a biological sample. The term "biological sample" is used in its conventional sense and refers to a whole organism, whole plant, whole fungus, or a subset of animal tissues, cells, or components, which may be found in certain cases in blood, mucus, lymph, synovial fluid, cerebrospinal fluid, saliva, bronchoalveolar lavage fluid, amniotic fluid, amniotic cord blood, urine, vaginal fluid, and semen. Thus, a "biological sample" refers to both intact organisms or a subset of their tissues, as well as homogenates made from organisms or a subset of their tissues, including, but not limited to, lysates or extracts, such as plasma, serum, cerebrospinal fluid, lymph, sections of the skin, respiratory tract, gastrointestinal tract, cardiovascular tract, and genitourinary tract, tears, saliva, milk, blood cells, tumors, and organs. A biological sample may be any type of biological tissue, 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, e.g., plasma, tears, urine, semen, etc., and in some cases the sample is a blood sample, including whole blood, such as blood obtained from venipuncture or finger stick (which may or may not be combined with any reagents, such as preservatives, anticoagulants, etc., prior to assay).

[0049] In certain embodiments, the source of the sample is a "mammal" or "mammalian," a term 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 methods may be applied to samples obtained from human subjects of both genders and at any stage of development (i.e., newborn, infant, juvenile, adolescent, adult), and in certain embodiments, the human subject is a juvenile, adolescent, or adult. It should be understood that while the present disclosure may be applied to samples from human subjects, the methods may also be performed on samples from other animal subjects (i.e., "non-human subjects"), such as, but not limited to, birds, mice, rats, dogs, cats, livestock, and horses.

[0050] Cells of interest may be targeted for characterization according to various parameters, such as phenotypic characteristics identified through the attachment of specific fluorescent labels to the cells of interest. In some embodiments, the system is configured to deflect analyzed droplets determined to contain target cells. A variety of cells can 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 erythroid cells. Target cells of interest include cells with favorable parameters (cell surface markers or antigens) that can be captured or labeled by a favorable affinity factor or conjugate thereof. For example, target cells may comprise cell surface antigens such as, for example, 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+) obtained from whole blood, bone marrow, or umbilical cord blood.

[0051] In certain embodiments, sample data and / or control data (e.g., as described above) are obtained by performing a flow cytometry protocol. In performing such methods, sample or control beads (e.g., as described above) in a flow stream of a flow cytometer are illuminated with light from a light source. In some embodiments, the light source is a broadband light source, emitting light having a wide range of wavelengths, including those ranging from 50 nm or greater, e.g., 100 nm or greater, e.g., 150 nm or greater, e.g., 200 nm or greater, e.g., 250 nm or greater, e.g., 300 nm or greater, e.g., 350 nm or greater, e.g., 400 nm or greater, and 500 nm or greater. For example, any suitable broadband light source emits light having a wavelength between 200 nm and 1500 nm. Another example of a suitable broadband light source includes a light source that emits light having a wavelength between 400 nm and 1000 nm. Where the method includes irradiating with a broadband light source, the broadband light source protocol of interest may include, but is not limited to, a halogen lamp, a deuterium arc lamp, a xenon arc lamp, a stabilized fiber-coupled broadband light source, a broadband LED with a continuous spectrum, a superluminescent light emitting diode, a semiconductor light emitting diode, a broadband LED white light source, a multi-LED integrated white light source, or any combination thereof, among other broadband light sources.

[0052] In other embodiments, the methods of the present disclosure include irradiating with a narrowband light source that emits a specific wavelength or narrow range of wavelengths, for example, a light source that emits light in a narrow range of wavelengths, such as in the range of 50 nm or less, for example 40 nm or less, for example 30 nm or less, for example 25 nm or less, for example 20 nm or less, for example 15 nm or less, for example 10 nm or less, for example 5 nm or less, for example 2 nm or less, and with a light source that emits a specific wavelength of light (i.e., monochromatic light). When the method includes irradiating with a narrowband light source, the narrowband light source protocol of interest may include, but is not limited to, a narrow wavelength LED, a laser diode, or a broadband light source coupled to one or more optical bandpass filters, a diffraction grating, a monochromator, or any combination thereof.

[0053] In certain embodiments, the method includes irradiating the sample and / or control beads with one or more lasers. As noted above, the type and number of lasers will vary depending on the sample / beads and the desired light to be collected, and may be gas lasers such as a helium-neon laser, an argon laser, a krypton laser, a xenon laser, a nitrogen laser, a CO 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 combinations thereof. In other examples, the method includes irradiating the flowstream with a dye laser, such as a stilbene, coumarin, or rhodamine laser. In yet another example, the method includes irradiating the flowstream with a metal vapor laser, such as a helium-cadmium (HeCd) laser, a helium-mercury (HeHg) laser, a helium-selenium (HeSe) laser, a helium-silver (HeAg) laser, a strontium laser, a neon-copper (NeCu) laser, a copper laser, or a gold laser, and combinations thereof. In yet another example, the method includes irradiating the flowstream with a solid state laser, such as a ruby ​​laser, a Nd:YAG laser, a NdCrYAG laser, an Er:YAG laser, a Nd:YLF laser, a Nd:YVO4 laser, a Nd:YCa4O(BO3)3 laser, a Nd:YCOB laser, a titanium sapphire laser, a thulium YAG laser, a ytterbium YAG laser, a ytterbium 2O3 laser, or a cerium-doped laser, and combinations thereof.

[0054] The sample and / or control beads may be illuminated with one or more of the light sources described above, e.g., two or more light sources, e.g., three or more light sources, e.g., four or more light sources, e.g., five or more light sources, including ten or more light sources. The light sources may include any combination of light source types. For example, in some embodiments, the method includes illuminating the sample and / or control beads in the flow stream with an array of lasers, such as an array having one or more gas lasers, one or more dye lasers, and one or more solid-state lasers.

[0055] The sample and / or control beads may be illuminated with wavelengths ranging from 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, and e.g., 400 nm to 800 nm. For example, if the light source is a broadband light source, the sample and / or control beads may be illuminated with wavelengths ranging from 200 nm to 900 nm. In another example, if the light source includes multiple narrowband light sources, the sample and / or control beads may be illuminated with specific wavelengths ranging from 200 nm to 900 nm. For example, the light source may be multiple narrowband LEDs (1 nm to 25 nm), each independently emitting light having a wavelength ranging from 200 nm to 900 nm. In other embodiments, the narrowband light source includes one or more lasers (e.g., a laser array), and the sample and / or control beads are illuminated at specific wavelengths in the range of 200 nm to 700 nm, such as a laser array having gas lasers, excimer lasers, dye lasers, metal vapor lasers, and solid-state lasers as described above.

[0056] When two or more light sources are employed, the sample and / or control beads may be illuminated by the light sources simultaneously, sequentially, or a combination thereof. For example, each of the light sources may illuminate the sample and / or control beads simultaneously. In other embodiments, the flow stream is illuminated sequentially by each of the light sources. When two or more light sources are employed to sequentially illuminate the sample and / or control beads, the time for which each light source illuminates the sample and / or control beads may independently be 0.001 microseconds or more, such as 0.01 microseconds or more, such as 0.1 microseconds or more, such as 1 microsecond or more, such as 5 microseconds or more, such as 10 microseconds or more, such as 30 microseconds or more, such as 60 microseconds or more. For example, the method may include illuminating the sample and / or control beads with a light source (e.g., a laser) for a period ranging from 0.001 microseconds to 100 microseconds, such as 0.01 microseconds to 75 microseconds, such as 0.1 microseconds to 50 microseconds, such as 1 microsecond to 25 microseconds, and such as 5 microseconds to 10 microseconds. In embodiments in which the sample and / or control beads are illuminated sequentially with two or more light sources, the duration for which the sample and / or control beads are illuminated by each light source may be the same or different.

[0057] The time interval between illumination by each light source can also be independently variable, optionally separated by a delay of 0.001 microseconds or more, e.g., 0.01 microseconds or more, e.g., 0.1 microseconds or more, e.g., 1 microsecond or more, e.g., 5 microseconds or more, e.g., 10 microseconds or more, e.g., 15 microseconds or more, e.g., 30 microseconds or more, and e.g., 60 microseconds or more. For example, the time interval between illumination by each light source can range from 0.001 microseconds to 60 microseconds, e.g., 0.01 microseconds to 50 microseconds, e.g., 0.1 microseconds to 35 microseconds, e.g., 1 microsecond to 25 microseconds, and e.g., 5 microseconds to 10 microseconds. In certain embodiments, the time interval between illumination by each light source is 10 microseconds. In embodiments in which sample and / or control beads are illuminated sequentially by more than two (i.e., three or more) light sources, the delay between illumination by each light source can be the same or different.

[0058] The sample and / or control beads may be illuminated continuously or at discrete intervals. In some cases, the method includes continuously illuminating the sample and / or control beads with a light source. In other examples, the sample and / or control beads are illuminated by a light source at discrete intervals, including, for example, every 0.001 milliseconds, every 0.01 milliseconds, every 0.1 milliseconds, every 1 milliseconds, every 10 milliseconds, every 100 milliseconds, and every 1000 milliseconds, or some other interval.

[0059] Depending on the light source, the sample and / or control beads may be illuminated from various distances such as 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 2.5 mm or more, for example 5 mm or more, such as 10 mm or more, for example 15 mm or more, such as 25 mm or more, and for example 50 mm or more, and the angle or illumination may be variable in the range of an angle between 10° and 90°, such as 15° and 85°, for example 20° and 80°, such as 25° and 75°, for example 30° and 60°, such as 90°.

[0060] In certain cases, sample and / or control beads may be illuminated with multiple angularly polarized beams of frequency-shifted light, and cells in the flow stream may be illuminated with multiple angularly polarized beams of frequency-shifted light, as described in Diebold et al., Nature Photonics Vol. 7(10) 806-810 (2013), and 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, and 10,408,758, the disclosures of which are incorporated herein by reference. , 10,451,538, 10,620,111, and U.S. Patent Application Publication Nos. 2017 / 0133857, 2017 / 0328826, 2017 / 0350803, 2018 / 0275042, 2019 / 0376895, and 2019 / 0376894.

[0061] In embodiments, light from the illuminated sample and / or control beads is delivered to a light detection system and measured by one or more photodetectors. In practicing the subject methods, light from the sample and / or control beads is delivered to three or more wavelength separators, each configured to pass light having a predetermined spectral range. The spectral range of light from each of the wavelength separators is delivered to one or more photodetection modules having optical components configured to deliver light having a predetermined subspectral range to a photodetector.

[0062] The light may be measured continuously or at discrete intervals using a light detection system. In some cases, the method includes measuring the light continuously. In other examples, the light is measured at discrete intervals, including measuring the light every 0.001 milliseconds, 0.01 milliseconds, 0.1 milliseconds, 1 millisecond, 10 milliseconds, 100 milliseconds, and 1000 milliseconds, or at some other interval.

[0063] Measurements of the collected light may be taken one or more times during the subject method, such as two or more times, such as three or more times, such as five or more times, and ten or more times, In certain embodiments, the propagation of light is measured two or more times and the data for a particular instance is averaged.

[0064] In some embodiments, the method includes conditioning the light before detecting it with the optical detection system of interest. For example, light from the sample source and / or control beads may pass through one or more lenses, mirrors, pinholes, slits, gratings, optical refractors, and any combination thereof. In some cases, the collected light passes through one or more focusing lenses, such as to reduce the profile of the light directed to the optical detection system or optical collection system, as described above. In other examples, emitted light from the sample and / or control beads passes through one or more collimators to reduce the divergence of the light beam delivered to the optical detection system.

[0065] system Aspects of the present disclosure further include systems, such as computer control systems, for carrying out embodiments of the above-described methods. System aspects include a light scatter detector system configured to generate data signals from light received from an interrogation point of a flow cytometer, and a processor, the processor including a memory operatively coupled to the processor and having instructions stored in the memory that, when executed by the processor, cause the processor to generate control data with the flow cytometer, determine a quantitative metric of the alignment of the light scatter detector system based on the control data, and determine an alignment adjustment for the light scatter detector system based on the quantitative alignment metric.

[0066] In some embodiments, instructions are stored on the processor that, when executed by the processor, cause the processor to further provide an alignment adjustment to a user. In some embodiments, instructions are stored on the processor that, when executed by the processor, cause the processor to adjust the light scattering detector system based at least in part on the alignment adjustment. In some embodiments, the processor may be configured to automatically perform the alignment adjustment determination and adjustment implementation methods described above. In some cases, the system further includes one or more computers for full or partial automation of the methods described herein. In some embodiments, the system includes a computer having a computer-readable storage medium storing a computer program.

[0067] In an embodiment, the system includes an input module, a processing module, and an output module. The subject systems may include both hardware and software components, where the hardware components may take the form of one or more platforms, e.g., in the form of servers, such that functional elements, i.e., elements of the system that perform specific tasks of the system (e.g., managing information input and output, information processing, etc.), may be performed by running software applications on or across one or more computer platforms representative of the system.

[0068] 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 includes a processor that accesses memory storing instructions for performing the steps of the subject method. The processing module may include an operating system, a graphical user interface (GUI) controller, system memory, memory storage devices, and input / output controllers, cache memory, data backup units, and many other devices. The processor may be a commercially available processor or one of other processors that are or become available. The processor executes an operating system, which interfaces with firmware and hardware in well-known ways and facilitates the processor's coordination and execution of 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 known in the art. The operating system typically cooperates with the processor to coordinate and execute the functions of the other components of the computer. The operating system also provides scheduling, input / output control, file and data management, memory management, and communication control and related services, all in accordance with known techniques. In some embodiments, the processor includes analog electronics that provide feedback control, such as negative feedback control.

[0069] 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 a resident hard disk or tape, optical media such as a read-and-write compact disc, flash memory devices, or other memory storage devices. Memory storage devices may also be any of a variety of known or future devices, including compact disc 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 disc. Any of these program storage media, or others now in use or that may later be developed, 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 called computer control logic, are typically stored in system memory and / or program storage devices used in conjunction with memory storage devices.

[0070] 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 of 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. Implementing a hardware state machine to perform the functions described herein will be apparent to one skilled in the art.

[0071] The subject programmable logic may be implemented in any of a variety of devices, such as a specifically 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 circuitry. Combinations of computing devices, such as a combination of a DSP and a microprocessor, multiple microprocessors, one or more microprocessors in conjunction with a DSP core, or any other such configuration in at least partial data connection, may implement one or more of the features described herein.

[0072] The memory may be any suitable device from which a processor can store and retrieve data, such as a magnetic, optical, or solid-state storage device (including a magnetic or optical disk, or tape, or RAM, or any other suitable device, fixed or portable). The processor may include a general-purpose digital microprocessor that is appropriately programmed from a computer-readable medium carrying the necessary program code. The programming may be provided to the processor remotely through a communications channel or may be pre-stored in a computer program product, such as memory or some other portable or fixed computer-readable storage medium using any of these devices in conjunction with the memory. For example, a magnetic or optical disk may carry the program and be read by a disk writer / reader. The systems of the present disclosure also include programming in the form of a computer program product, e.g., algorithms for use in implementing the above-described methods. Programming according to the present disclosure may be recorded on a computer-readable medium, e.g., 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 floppy disks, hard disk storage media, and magnetic tape, optical storage media such as CD-ROMs, storage media such as RAM, ROM, portable flash drives, and hybrids of these categories such as magnetic / optical storage media.

[0073] The processor may also have access to a communication channel for communicating with a remote user, where remote means that the user is not in 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).

[0074] In some embodiments, a system according to the present disclosure may be configured to include a communications interface. In some embodiments, the communications interface includes a receiver and / or a transmitter for communicating with a network and / or another device. The communications interface may be configured for wired or wireless communications, including, but not limited to, radio frequency (RF) communications (e.g., radio frequency identification (RFID), Zigbee communications protocol, Wi-Fi, infrared, wireless universal serial bus (USB), ultra-wideband (UWB), Bluetooth® communications protocol, and cellular communications such as code division multiple access (CDMA) or global system for mobile communications (GSM).

[0075] In one embodiment, the communications interface is configured to include one or more communications ports, e.g., a physical port or interface such as a USB port, a USB-C port, an RS-232 port, or any other suitable electrical connection port that enables data communications between the subject system and other external devices, such as computer terminals (e.g., in a doctor's office or hospital environment) configured for similar complementary data communications.

[0076] In one embodiment, the communication interface is configured for infrared communication, Bluetooth® communication, or any other suitable wireless communication protocol to enable the subject system to communicate with computer terminals and / or other devices such as networks, communication-enabled mobile phones, personal digital assistants, or any other communication device that a user may use in conjunction with.

[0077] In one embodiment, the communication interface is configured to provide connectivity for data transfer using Internet Protocol (IP) over a cellular network, Short Message Service (SMS), a wireless connection to a personal computer (PC) in a local area network (LAN) connected to the Internet, or a Wi-Fi connection to the Internet at a Wi-Fi hotspot.

[0078] In one embodiment, the subject system is configured to wirelessly communicate with a server device via a communications interface using common standards such as, for example, 802.11 or Bluetooth® RF protocols, or the IrDA infrared protocol. The server device may be another portable device, such as a smartphone, personal digital assistant (PDA), or notebook computer, or a larger device, such as a desktop computer, appliance, etc. In some embodiments, the server device has a display, such as a liquid crystal display (LCD), and input devices, such as buttons, a keyboard, a mouse, or a touchscreen.

[0079] In some embodiments, the communications interface is configured to automatically or semi-automatically communicate data stored in the subject system, e.g., the optional data storage unit, with a network or server device using one or more of the communications protocols and / or mechanisms described above.

[0080] 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. When one of the display devices provides visual information, this information may typically be logically and / or physically organized as an array of pixels. A graphical user interface (GUI) controller provides a graphical input / output interface between the system and the user and may include any of a variety of known or future software programs for processing user input. The functional elements of a computer may communicate with each other via a system bus. Some of these communications may be realized in alternative embodiments using a network or other types of remote communications. The output manager may also communicate information generated by the processing modules to a remote user, for example, via the Internet, telephone, or satellite network, according to known techniques. Presentation of data by the output manager may be implemented according to various known techniques. As some examples, the data may include SQL, HTML, or XML documents, emails, or other files, or other formats of data. The data may also include Internet URL addresses so that the user can retrieve additional SQL, HTML, XML, or other documents or data from remote sources. The platform or platforms present in the subject system may be any type of known or future-developed computer platform, but they are typically computers of a class commonly referred to as servers. However, they may also be mainframe computers, workstations, or other computer types. They may be connected via any known or future type of cabling or other communication system, including wireless systems, and may or may not be networked. They may be co-located or physically separated. In some cases, various operating systems may be employed on any computer platform, depending on the type and / or manufacturer 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.

[0081] 4 shows a functional block diagram of an example flow cytometer control system for analyzing and displaying biological events, including a processor 402. The processor 402 can be configured to implement various processes for controlling the graphical display of the biological events.

[0082] The flow cytometer or sorting system 401 can be configured to acquire biological event data. For example, the flow cytometer can generate flow cytometry event data. The flow cytometer 401 can be configured to provide the biological event data to the processor 402. A data communication channel can be included between the flow cytometer or sorting system 401 and the processor 402. The biological event data can be provided to the processor 402 via the data communication channel.

[0083] The processor 402 can be configured to receive biological event data from the flow cytometer or sorting system 401. The biological event data received from the flow cytometer or sorting system 401 can include flow cytometry event data. The processor 402 can be configured to provide a graphical display including a first plot of the biological event data to the display device 404. The processor 402 can be further configured to render a region of interest, for example, as a gate around a population of the biological event data shown by the display device 404, overlaid on the first plot. In some embodiments, the gate can be a logical combination of one or more graphical regions of interest depicted in a histogram or bivariate plot of a single parameter. In some embodiments, the display can be used to display particle parameters or saturation detector data.

[0084] The processor 402 can be further configured to display the biological event data within the gate on the display device 404 differently from other events within the biological event data outside the gate. For example, the processor 402 can be configured to render the color of the biological event data contained within the gate differently from the color of the biological event data outside the gate. The display device 404 can be implemented as a monitor, tablet computer, smartphone, or other electronic device configured to present a graphical interface.

[0085] The processor 402 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 405. The mouse 405 may initiate a gate selection signal to the processor 402 identifying a gate to be displayed on or manipulated via the display device 404 (e.g., by clicking the desired gate when a cursor is positioned there). In some implementations, the first device may be implemented as a keyboard 406 or other means for providing input signals to the processor 402, such as a touchscreen, a stylus, 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 405 may include a right mouse button and a left mouse button, each of which may generate a trigger event. The trigger event may cause the processor 402 to change how data is displayed, which portions of the data are actually displayed on the display device 404, and / or provide input for further processing, such as selecting a population for particle sorting.

[0086] In some embodiments, the processor 402 can be configured to detect when a gate selection is initiated by the mouse 405. The processor 402 can be further configured to automatically modify the visualization of the plot to facilitate the gating process. The modification can be based on a particular distribution of the biological event data received by the processor 402.

[0087] The processor 402 may be connected to a storage device 403. The storage device 403 may be configured to receive and store biological event data from the processor 402. The storage device 403 may also be configured to receive and store flow cytometry event data from the processor 402. The storage device 403 may be further configured to enable retrieval of biological event data, such as flow cytometry event data, by the processor 402.

[0088] The display device 404 can be configured to receive display data from the processor 402. The display data can include plots of biological event data and gates that delineate sections of the plots. The display device 404 can be further configured to modify the information presented according to input received from the processor 402, along with input from the flow cytometer 401, the storage device 403, the keyboard 406, and / or the mouse 405.

[0089] In some implementations, the processor 402 can generate a user interface for receiving exemplary events for sorting. For example, the user interface can include controls 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 the sample and / or control beads or based on an initial set of events for a portion of the sample and / or control beads.

[0090] FIG. 5 illustrates the general architecture of an exemplary computing device 500 according to certain embodiments. The general architecture of computing device 500 illustrated in FIG. 5 includes an arrangement of computer hardware and software components. However, not all of these generally conventional elements need be shown to form an enabling disclosure. As illustrated, computing device 500 includes a processing unit 510, a network interface 520, a computer-readable medium drive 530, an input / output device interface 540, a display 550, and input devices 560, all of which may communicate with each other via a communications bus. Network interface 520 may provide connectivity to one or more networks or computing systems. Thus, processing unit 510 may receive information and instructions from other computing systems or services via a network. Processing unit 510 also communicates with memory 570 and may further provide output information to optional display 550 via input / output device interface 540. For example, analysis software (e.g., data analysis software or program 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 540 may also accept input from optional input device(s) 560, such as a keyboard, mouse, digital pen, microphone, touch screen, gesture recognition system, voice recognition system, gamepad, accelerometer, gyroscope, or other input device.

[0091] Memory 570 may include computer program instructions (grouped in some embodiments as modules or components) that processing unit 510 executes to implement one or more embodiments. Memory 570 generally includes RAM, ROM, and / or other persistent, secondary, or non-transitory computer-readable media. Memory 570 may store an operating system 572 that provides computer program instructions used by processing unit 510 in the general management and operation of computing device 500. Data may be stored in data storage device 590. Memory 570 may further include computer program instructions and other information for implementing aspects of the present disclosure.

[0092] In some embodiments, the system includes a particle analyzer. In certain embodiments, the particle analyzer is a flow cytometer. The flow cytometer of interest may include a flow cell for transporting particles in a flow stream, a light source for illuminating particles in the flow stream at an interrogation point, and a particle-modulated light detector for detecting the particle-modulated light. In some cases, the flow cytometer is a full-spectrum flow cytometer.

[0093] As described herein, "flow cell" is described in its conventional sense to refer to a component, such as a cuvette, that includes a flow channel with a liquid flow stream for transporting particles in a sheath fluid. A cuvette of interest includes a container with a passageway therethrough. The flow stream may include liquid sample and / or control beads injected from a sample tube. A flow cell of interest includes an optically accessible flow channel. In some instances, the flow cell includes a transparent material (e.g., quartz) that allows light to pass through. In some embodiments, the flow cell is a stream-in-air flow cell in which optical interrogation of particles occurs outside the flow cell (i.e., in free space).

[0094] In some cases, the flow stream is configured to be illuminated with light from a light source at an interrogation point. The flow stream comprising the flow channel may contain liquid sample and / or control beads injected from a sample tube. In certain embodiments, the flow stream may comprise a narrow, rapid flow stream of liquid arranged so that linearly separated particles transported therein are separated from one another in single file. As discussed herein, "interrogation point" refers to the region within the flow cell where particles are illuminated by light from a light source, e.g., for analysis. The size of the interrogation point may vary as needed. For example, if 0 μm represents the axis of light emitted by the light source, the interrogation point may range from -100 μm to 100 μm, e.g., -50 μm to 50 μm, e.g., -25 μm to 40 μm, and e.g., -15 μm to 30 μm.

[0095] After particles are illuminated in a flow cell, particle-modulated light can be observed. "Particle-modulated light" refers to light received from particles in a flow stream after illuminating the particles with light from a light source. In some cases, the particle-modulated light is side-scattered light. As discussed herein, side-scattered light refers to light refracted and reflected from the surface and internal structure of a particle. In further embodiments, the particle-modulated light includes forward-scattered light (i.e., light traveling primarily in a forward direction through or around the particle). In still other cases, the particle-modulated light includes fluorescent light (i.e., light emitted from a fluorescent dye after illumination with excitation wavelength light).

[0096] As mentioned above, aspects of the present disclosure also include a light source configured to illuminate particles passing through the flow cell at the point of interrogation. Any convenient light source may be employed as the light source described herein. In some embodiments, the light source is a laser. 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 CO 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 examples, a subject flow cytometer includes a dye laser, such as a stilbene, coumarin, or rhodamine laser. In yet another example, 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 yet another example, flow cytometers of interest include solid-state lasers such as ruby, Nd:YAG, NdCrYAG, Er:YAG, Nd:YLF, Nd:YVO, Nd:YCaO(BO), Nd:YCOB, titanium sapphire, thulium YAG, ytterbium YAG, ytterbium O, or cerium-doped lasers, and combinations thereof.

[0097] The laser light source according to certain embodiments may also include one or more optical conditioning components. In certain embodiments, the optical conditioning components may include any device located between the light source and the flow cell that can change the spatial width of the illumination or some other characteristic of the illumination from the light source, such as the illumination direction, wavelength, beam width, beam intensity, and focus. The optical conditioning 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 certain embodiments, the target flow cytometer includes one or more focusing lenses. The focusing lens may, in one example, be a demagnification lens. In yet other embodiments, the target flow cytometer includes optical fibers.

[0098] If the optical adjustment component is configured to move, it may be configured to move continuously or at discrete intervals, including, 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, and 25 mm or more.

[0099] Any displacement protocol may be employed to move the optical adjustment component structure, such as those coupled to a movable support stage or employing a motorized translation stage, a lead screw translation assembly, a geared translation device, e.g., a stepper motor, a servo motor, a brushless electric motor, a brushed DC motor, a microstep drive motor, a high resolution stepper motor, among other types of motors.

[0100] 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 a distance of 0.005 mm or more, for example, 0.01 mm or more, for example, 0.05 mm or more, for example, 0.1 mm or more, for example, 0.5 mm or more, for example, 1 mm or more, for example, 5 mm or more, for example, 10 mm or more, for example, 25 mm or more, for example, 100 mm or more. Furthermore, the light source may be positioned at any suitable angle relative to the flow cell, for example, an angle ranging from 10 degrees to 90 degrees, for example, 15 degrees to 85 degrees, for example, 20 degrees to 80 degrees, for example, 25 degrees to 75 degrees, etc., including 30 degrees to 60 degrees, for example, an angle ranging from 90 degrees.

[0101] In some embodiments, the target light source includes multiple 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, and e.g., fifteen or more lasers, configured to provide laser light for discrete illumination of the flowstream. Depending on the desired wavelength of light for illuminating the flowstream, each laser may have a particular wavelength 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, and e.g., between 400 nm and 800 nm. In certain embodiments, the target lasers may include one or more of a 405 nm laser, a 488 nm laser, a 561 nm laser, and a 635 nm laser.

[0102] As described above, a subject flow cytometer may further include one or more particle-modulated light detectors for detecting particle-modulated light intensity data. In some embodiments, the particle-modulated light detector includes one or more forward scatter detectors configured to detect forward scatter light. For example, a subject flow cytometer may include one forward scatter detector or multiple forward scatter detectors, e.g., two or more, e.g., three or more, e.g., four or more, and e.g., five or more. In certain embodiments, the flow cytometer includes one forward scatter detector. In other embodiments, the flow cytometer includes two forward scatter detectors.

[0103] Any convenient detector for detecting collected light may be used in the forward scattered light detector described herein. Detectors of interest may include optical sensors or detectors such as, but not limited to, active pixel sensors (APS), avalanche photodiodes, image sensors, charge-coupled devices (CCDs), intensified charge-coupled devices (ICCDs), light-emitting diodes, photon counters, bolometers, pyroelectric detectors, photoresistors, photocells, photodiodes, photomultiplier tubes (PMTs), phototransistors, quantum dot photoconductors, or photodiodes, and combinations thereof, among other detectors. In certain 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 certain embodiments, the detector has a resolution of 0.01 cm. 2 ~10cm 2 , e.g. 0.05cm 2 ~9cm 2 , e.g. 0.1cm 2 ~8cm 2 , e.g. 0.5cm 2 ~7cm 2 , and e.g. 1 cm 2 ~5cm 2 and a photomultiplier tube such as a photomultiplier tube having an active detection surface area in each region that is in the range of .mu.m.

[0104] In embodiments, the forward scattered light detector is configured to measure light continuously or at discrete intervals. In some cases, the detector is configured to continuously obtain measurements of the collected light. In other examples, the detector is configured to perform measurements at discrete intervals, such as measuring light every 0.001 milliseconds, 0.01 milliseconds, 0.1 milliseconds, 1 millisecond, 10 milliseconds, 100 milliseconds, and every 1000 milliseconds, or some other interval.

[0105] In additional embodiments, the one or more particle modulation light detectors may include one or more side scatter light detectors for detecting side scatter wavelengths of light (i.e., light refracted and reflected from the surface and internal structures of the particle). In some embodiments, the flow cytometer includes a single side scatter light detector. In other embodiments, the flow cytometer includes a plurality of side scatter light detectors, such as two or more, three or more, four or more, and even five or more.

[0106] Any convenient detector for detecting collected light may be used in the side scatter light detectors described herein. Detectors of interest may include optical sensors or detectors such as, but not limited to, active pixel sensors (APS), avalanche photodiodes, image sensors, charge-coupled devices (CCDs), intensified charge-coupled devices (ICCDs), light-emitting diodes, photon counters, bolometers, pyroelectric detectors, photoresistors, photocells, photodiodes, photomultiplier tubes (PMTs), phototransistors, quantum dot photoconductors, or photodiodes, and combinations thereof, among other detectors. In certain 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 certain embodiments, the detector has a resolution of 0.01 cm. 2 ~10cm 2 , e.g. 0.05cm 2 ~9cm 2 , e.g. 0.1cm 2 ~8cm 2 , e.g. 0.5cm 2 ~7cm 2 , and e.g. 1 cm 2 ~5cm 2 and a photomultiplier tube such as a photomultiplier tube having an active detection surface area in each region that is in the range of .mu.m.

[0107] In embodiments, a subject flow cytometer also includes a fluorescence detector configured to detect one or more fluorescent wavelengths of light, hi other embodiments, the flow cytometer includes multiple fluorescence detectors, such as 2 or more, such as 3 or more, such as 4 or more, 5 or more, 10 or more, 15 or more, and such as 20 or more.

[0108] Any convenient detector for detecting collected light may be used in the fluorescence detectors described herein. Detectors of interest may include, but are not limited to, optical sensors or detectors such as active pixel sensors (APS), avalanche photodiodes, image sensors, charge-coupled devices (CCDs), intensified charge-coupled devices (ICCDs), light-emitting diodes, photon counters, bolometers, pyroelectric detectors, photoresistors, photocells, photodiodes, photomultiplier tubes (PMTs), phototransistors, quantum dot photoconductors, or photodiodes, and combinations thereof, among other detectors. In certain 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 certain embodiments, the detector has a resolution of 0.01 cm. 2 ~10cm 2 , e.g. 0.05cm 2 ~9cm 2 , e.g. 0.1cm 2 ~8cm 2 , e.g. 0.5cm 2 ~7cm 2 , and e.g. 1 cm 2 ~5cm 2 and a photomultiplier tube such as a photomultiplier tube having an active detection surface area in each region that is in the range of .mu.m.

[0109] When a subject flow cytometer includes multiple fluorescence detectors, each fluorescence detector may be the same, or the collection of fluorescence detectors may be a combination of different types of detectors. For example, when a subject flow cytometer includes two fluorescence detectors, in some embodiments, the first fluorescence detector is a CCD-type device and the second fluorescence detector (or imaging sensor) is a CMOS-type device. In other embodiments, both the first fluorescence detector and the second fluorescence detector are CCD-type devices. In still other embodiments, both the first fluorescence detector and the second fluorescence detector are CMOS-type devices. In still other embodiments, the first fluorescence detector is a CCD-type device and the second fluorescence detector is a photomultiplier tube (PMT). In still other embodiments, the first fluorescence detector is a CMOS-type device and the second fluorescence detector is a photomultiplier tube. In still other embodiments, both the first fluorescence detector and the second fluorescence detector are photomultiplier tubes.

[0110] In embodiments of the present disclosure, the subject fluorescence detectors are configured to measure collected light at one or more wavelengths, for example, to measure light emitted by sample and / or control beads in the flow stream at two or more wavelengths, for example, five or more different wavelengths, for example, ten or more different wavelengths, for example, twenty-five or more different wavelengths, for example, fifty or more different wavelengths, for example, one hundred or more different wavelengths, for example, two hundred or more different wavelengths, for example, three hundred or more different wavelengths, and for example, four hundred or more different wavelengths. In some embodiments, two or more detectors in the flow cytometers described herein are configured to measure the same or overlapping wavelengths of collected light.

[0111] In some embodiments, the intended fluorescence detector is configured to measure light collected over any range of wavelengths (e.g., 200 nm to 1000 nm). In certain embodiments, the intended detector is configured to collect a spectrum of light over any range of wavelengths. For example, a flow cytometer may include one or more detectors configured to collect a spectrum of light over one or more wavelength ranges from 200 nm to 1000 nm. In still other embodiments, the intended detector is configured to measure light emitted by sample and / or control beads in the flow stream at one or more specific wavelengths. For example, a flow cytometer may include 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 certain embodiments, the one or more detectors may be configured to pair with a particular fluorophore, such as one used with a sample in a fluorescence assay.

[0112] In some embodiments, the flow cytometer includes one or more wavelength separators disposed between the flow cell and the particle-modulated light detector. The term "wavelength separator" is used herein in its conventional sense to refer to an optical component configured to separate light collected from the sample and / or control beads into predetermined spectral ranges. In some embodiments, the flow cytometer includes a single wavelength separator. In other embodiments, the flow cytometer includes multiple wavelength separators, e.g., two or more wavelength separators, e.g., three or more, four or more, five or more, six or more, seven or more, eight or more, nine or more, ten or more, fifteen or more, twenty-five or more, fifty or more, seventy-five or more, and even one hundred or more wavelength separators. In some embodiments, the wavelength separators are configured to separate light collected from the sample and / or control beads into predetermined spectral ranges by passing light having the predetermined spectral ranges and reflecting one or more remaining spectral ranges of light. In other embodiments, the wavelength separator is configured to separate light collected from the sample and / or control beads into predetermined spectral ranges by passing light having the predetermined spectral ranges and absorbing one or more remaining spectral ranges of light. In yet other embodiments, the wavelength separator is configured to spatially diffract light collected from the sample and / or control beads into predetermined spectral ranges. 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 optical detection system is a dichroic mirror.

[0113] Suitable flow cytometry systems include those described in Ormerod (ed.), Flow Cytometry: A Practical Approach, Oxford Univ. Press (1997); Jaroszeski et al. (ed.), 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 Thromb 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 certain instances, flow cytometry systems of interest include BD Biosciences FACSCanto™ flow cytometer, BD Biosciences FACSCanto™ II flow cytometer, BD Accuri™ flow cytometer, BD Accuri™ C6 Plus flow cytometer, BD Biosciences FACSCelesta™ flow cytometer, BD Biosciences FACSLyric™ flow cytometer, BD Biosciences FACSVerse™ flow cytometer, BD Biosciences FACSymphony™ flow cytometer, BD Biosciences LSRFortessa™ flow cytometer, BD Biosciences LSRFortessa™ X-20 flow cytometer, BD Biosciences FACSPresto™ flow cytometer, BD Biosciences FACSVia™ flow cytometer, and BD Biosciences FACSCalibur™ cell sorter, BD Biosciences FACSCount™ cell sorter, BD Biosciences FACSLyric™ cell sorter, and ...Verse™ flow cytometer, BD Biosciences FACSSymphony™ flow cytometer, BD Biosciences LSRFortessa™ flow cytometer, BD Biosciences LSR These include the BD Biosciences Via™ cell sorter, BD Biosciences Influx™ cell sorter, BD Biosciences Jazz™ cell sorter, BD Biosciences Aria™ cell sorter, BD Biosciences FACSAria™ II cell sorter, BD Biosciences FACSAria™ III cell sorter, BD Biosciences FACSAria™ Fusion cell sorter, and BD Biosciences FACSMelody™ cell sorter, BD Biosciences FACSymphony™ S6BD, and FACSDiscover™ S8 Cell Sorter cell sorters.

[0114] In some embodiments, the subject systems may be implemented using the same or similar technology as disclosed in U.S. Patent Nos. 10,663,476, 10,620,111, 10,613,017, 10,605,713, 10,585,031, 10,578,542, 10,578,469, 10,478,479, and 10,478,479, the disclosures of which are incorporated herein by reference in their entireties. Specification No. 81,074, Specification No. 10,302,545, Specification No. 10,145,793, Specification No. 10,113,967, Specification No. 10,006,852, Specification No. 9,952, Specification No. 076, Specification No. 9,933,341, Specification No. 9,726,527, Specification No. 9,453,789, Specification No. 9,200,334, Specification No. 9,097,640 , Specification No. 9,095,494, Specification No. 9,092,034, Specification No. 8,975,595, Specification No. 8,753,573, Specification No. 8,233,146, Specification No. 8,14 Specification No. 0,300, Specification No. 7,544,326, Specification No. 7,201,875, Specification No. 7,129,505, Specification No. 6,821,740, Specification No. 6,813,017 and flow cytometry systems such as those described in the following patents: US Pat. Nos. 6,809,804, 6,372,506, 5,700,692, 5,643,796, 5,627,040, 5,620,842, 5,602,039, 4,987,086, and 4,498,766.

[0115] In certain cases, the flow cytometry system of the present disclosure may be implemented using the same or similar techniques as those described in, for example, Diebold, et al. Nature Photonics Vol. 7(10), 806-810 (2013), 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, and configured to image particles in the flow stream by fluorescence imaging using radio frequency tagged emission (FIRE), as described in U.S. Patent Application Publication Nos. 451,538, 10,620,111, and U.S. Patent Application Publication Nos. 2017 / 0133857, 2017 / 0328826, 2017 / 0350803, 2018 / 0275042, 2019 / 0376895, and 2019 / 0376894. In such cases, the flow cytometry data may include image data of particles, e.g., cells, present in the sample. See, for example, Schraivogel et al., Science Vol. 375(6578) pp. 315-320(2022), the disclosures of which are incorporated herein in their entireties, and U.S. Provisional Patent Application No. 63 / 256,974, the disclosures of which are incorporated herein in their entireties. An example of such a system is the FACSDiscover™ S8 cell sorter.

[0116] In some embodiments, the system is a flow cytometer, and a flow cytometry system 600 ( FIG. 6 ) can be used to analyze and characterize particles, with or without physically sorting the particles into a collection vessel. FIG. 6 shows a functional block diagram of a flow cytometry system for computationally based sample analysis and particle characterization. In some embodiments, the flow cytometry system 600 is a flow system. The flow cytometry system 600 shown in FIG. 6 can be configured to perform, in whole or in part, the methods described herein. The flow cytometry system 600 includes a fluidics system 602. The fluidics system 602 can include or be coupled to a sample tube 610 and a moving fluid column within the sample tube through which particles 630 (e.g., cells) of the sample move along a common sample path 620.

[0117] The flow cytometry system 600 includes a detection system 604 configured to collect a signal from each particle as it passes through one or more detection stations along a common sample path. A detection station 608 generally refers to a monitoring area 640 of the common sample path. Detection, in some implementations, can include detecting light or one or more other characteristics of a particle 630 as it passes through the monitoring area 640. FIG. 6 shows one detection station 608 with one monitoring area 640. Some implementations of the flow cytometry system 600 can include multiple detection stations. Additionally, some detection stations can monitor more than one area.

[0118] Each signal is assigned a signal value to form a data point for each particle. This data may be referred to as event data, as described above. The data points may be multidimensional data points that include values ​​for each property measured for the particle. The detection system 604 is configured to collect a series of such data points over a first time interval.

[0119] The flow cytometry system 600 may also include a control system 606. The control system 606 may include one or more processors, amplitude control circuitry, and / or frequency control circuitry. The illustrated control system may be operatively associated with the fluidics system 602. The control system may be configured to generate a calculated signal frequency for at least a portion of the first time interval based on the Poisson distribution and the number of data points collected by the detection system 604 during the first time interval. The control system 606 may further be configured to generate an experimental signal frequency based on the number of data points for the portion of the first time interval. The control system 606 may further compare the experimental signal frequency to the calculated signal frequency or a predetermined signal frequency.

[0120] 7 shows a system 700 for flow cytometry according to an exemplary embodiment of the invention. System 700 includes a flow cytometer 710, a controller / processor 790, and a memory 795. Flow cytometer 710 includes one or more excitation lasers 715a-715c, a focusing lens 720, a flow chamber 725, a forward scatter detector 730, a side scatter detector 735, a fluorescence collection lens 740, one or more beam splitters 745a-745g, one or more bandpass filters 750a-750e, one or more longpass ("LP") filters 755a-755b, and one or more fluorescence detectors 760a-760f.

[0121] Pump lasers 715a-715c emit light in the form of laser beams. In the exemplary system of FIG. 7, the wavelengths of the laser beams emitted from pump lasers 715a-715c are 488 nm, 633 nm, and 325 nm, respectively. The laser beams are first directed through one or more of beam splitters 745a and 745b. Beam splitter 745a transmits 488 nm light and reflects 633 nm light. Beam splitter 745b transmits ultraviolet light (light with wavelengths ranging from 10 nm to 400 nm) and reflects 488 nm and 633 nm light.

[0122] The laser beam is then directed onto a focusing lens 720, which focuses the beam onto a portion of the fluid stream in which the sample and / or control bead particles are located, within a flow chamber 725. The flow chamber is part of a fluidics system that directs particles in the stream, typically one at a time, towards the focused laser beam for interrogation. The flow chamber can comprise a flow cell in a benchtop cytometer or a nozzle tip in a stream-in air cytometer.

[0123] Light from the laser beam interacts with particles in the sample by diffraction, refraction, reflection, scattering, and absorption, with re-emission at a variety of different wavelengths depending on the particle's properties, such as its size, internal structure, and the presence of one or more fluorescent molecules attached to or naturally present on or in the particle. Fluorescent emissions and diffracted, refracted, reflected, and scattered light may be sent through one or more of beam splitters 745a-g, bandpass filters 750a-e, longpass filters 755a-b, and fluorescence collection lens 740 to one or more of forward scatter detector 730, side scatter detector 735, and one or more fluorescence detectors 760a-f.

[0124] The fluorescence collection lens 740 collects light emitted from particle-laser beam interactions and directs it toward one or more beam splitters and filters. Bandpass filters, such as bandpass filters 750a-750e, allow a narrow range of wavelengths to pass through the filter. For example, bandpass filter 750a is a 510 / 20 filter. The first number represents the center of the spectral band. The second number indicates 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 wavelengths of light below a specific wavelength. Longpass filters, such as longpass filters 755a-755b, transmit wavelengths of light below a specific wavelength. For example, longpass filter 755a, a 670 nm longpass filter, transmits light above 670 nm. Filters are often selected to optimize the detector's specificity for a particular fluorochrome. The filter can be configured so that the spectral band of light transmitted to the detector is close to the emission peak of the fluorescent dye.

[0125] Beam splitters direct light of different wavelengths in different directions. Beam splitters can be characterized by filter properties such as short-pass and long-pass. For example, beam splitter 745g is a 620SP beam splitter, meaning that beam splitter 745g transmits light with wavelengths of 620 nm or less and reflects light with wavelengths longer than 620 nm in various directions. In one embodiment, beam splitters 745a-745g can comprise optical mirrors, such as dichroic mirrors.

[0126] The forward scatter detector 730 is positioned slightly off-axis from the direct beam through the flow cell and is configured to detect diffracted light, primarily traveling forward 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 735 is configured to detect refracted and reflected light from the particle's surface and internal structure, which tends to increase as the particle's structure becomes more complex. Fluorescence emission from fluorescent molecules associated with the particle can be detected by one or more fluorescence detectors 760a-760f. The side scatter detector 735 and the fluorescence detector may include photomultiplier tubes. The signals detected by the forward scatter detector 730, side scatter detector 735, and fluorescence detector can be converted to electronic signals (voltage) by the detectors. This data can provide information about the sample.

[0127] 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 7, 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 at various wavelengths and in a variety of different configurations.

[0128] During operation, the operation of the cytometer is controlled by the controller / processor 790, and measurement data from the detectors may be stored in memory 795 and processed by the controller / processor 790. Although not explicitly shown, the controller / processor 790 is coupled to the detectors to receive output signals from the detectors, and may also be coupled to electrical and electromechanical components of the flow cytometer 710 to control lasers, fluid flow parameters, etc. Input / output (I / O) functionality 797 may also be provided in the system. The memory 795, controller / processor 790, and I / O 797 ​​may be provided entirely as an integral part of the flow cytometer 710. In such an embodiment, a display may form part of the I / O functionality 797 for presenting experimental data to a user of the cytometer 710. Alternatively, some or all of the memory 795 and controller / processor 790 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 795 and controller / processor 790 may be in wireless or wired communication with the cytometer 710. Controller / processor 790, together with memory 795 and I / O 797, can be configured to perform a variety of functions associated with the preparation and analysis of flow cytometer experiments.

[0129] The system shown in FIG. 7 includes six different detectors that detect fluorescence in six different wavelength bands (sometimes referred to herein as the “filter windows” of a given detector), as defined by the configuration of filters and / or splitters in the beam path from the flow cell 725 to each detector. Various fluorescent molecules used in a flow cytometer experiment emit light in their own characteristic wavelength bands. The particular fluorescent labels used in the experiment and their associated fluorescence emission bands may be selected to approximately match the filter windows of the detectors. However, as many detectors are provided and many labels are utilized, perfect correspondence between filter windows and fluorescence emission spectra is not possible. While the peak of the emission spectrum of a particular fluorescent molecule may fall within the filter window of one particular detector, it is generally true that a portion of that label’s emission spectrum also overlaps with the filter window of one or more other detectors. This is sometimes referred to as spillover. The I / O 797 ​​can be configured to receive data for a flow cytometer experiment involving a panel of fluorescent labels and multiple cell populations with multiple markers, each cell population having a subset of the multiple markers. I / O 797 ​​may also be configured to receive biological data assigning one or more markers to one or more cell populations, data on marker density, emission spectrum data, data assigning labels to one or more markers, and cytometer configuration data. Flow cytometer experimental data, such as label spectral characteristics and flow cytometer configuration data, may also be stored in memory 795. Controller / processor 790 may be configured to evaluate one or more assignments of labels to markers.

[0130] FIG. 8 is a schematic diagram of a particle sorter system 800 (e.g., a sorting system of a flow cytometer) according to one embodiment presented herein. In some embodiments, the particle sorter system 800 is a cell sorter system. As shown in FIG. 8 , a droplet-forming transducer 802 (e.g., a piezoelectric oscillator) is coupled to a fluid conduit 801, which can be coupled to, can include, or can be a nozzle 803. Within the fluid conduit 801, a sheath fluid 804 hydrodynamically focuses a sample fluid 806 containing particles 809 into a moving fluid column 808 (e.g., a stream). Within the moving fluid column 808, the particles 809 (e.g., cells) are aligned single file across a monitoring area 811 (e.g., where laser streams intersect) and are illuminated by an illumination source 812 (e.g., a laser). Vibration of droplet-forming transducer 802 causes moving fluid column 808 to break up into multiple droplets 810 , some of which contain particles 809 .

[0131] During operation, the detection station 814 (e.g., an event detector) identifies when a particle of interest (or cell of interest) crosses the monitoring area 811. The detection station 814 is fed to a timing circuit 828, which in turn is fed to a flash charge circuit 830. At a droplet break-off point, signaled by a timed droplet delay (Δt), a flash charge can be applied to the moving fluid column 808 so that the droplets of interest carry a charge. The droplets 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 droplets into a container, such as a collection tube or a multi-well or microwell sample plate, where wells or microwells can be associated with specific droplets of interest. As shown in FIG. 8, the droplets can be collected in a drain container 838.

[0132] Detection system 816 (e.g., a droplet boundary detector) serves to automatically determine the phase of the droplet drive signal when a particle of interest passes through monitoring area 811. An exemplary droplet boundary detector is described in U.S. Pat. No. 7,679,039, which is incorporated herein by reference in its entirety. Detection system 816 allows the instrument to accurately calculate the position of each detected particle within the droplet. Detection system 816 can provide amplitude signal 820 and / or phase signal 818, which then provide amplitude control circuit 826 and / or frequency control circuit 824 (via amplifier 822). Amplitude control circuit 826 and / or frequency control circuit 824 then control droplet forming transducer 802. Amplitude control circuit 826 and / or frequency control circuit 824 can be included within the control system.

[0133] In some implementations, the sorting electronics (e.g., detection system 816, detection station 814, and processor 840) can be coupled with a memory configured to store detected events and sorting decisions based on the detected events. The sorting decisions can be included in the particle's event data. In some implementations, the detection system 816 and detection station 814 can be implemented as a single detection unit or communicatively coupled such that event measurements can be collected by either the detection system 816 or the detection station 814 and provided to a non-collection element.

[0134] FIG. 9 is a schematic diagram of a particle sorter system according to one embodiment presented herein. The particle sorter system 900 shown in FIG. 9 includes deflection plates 952 and 954. An electric charge can be applied via a stream charging wire within the barb, creating a stream of droplets 910 containing particles 910 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 or another detection system (not shown in FIG. 9). The deflection plates 952 and 954 can be independently controlled to attract or repel the charged droplets, directing them toward a desired collection vessel (e.g., one of 972, 974, 976, or 978). As shown in FIG. 9, the deflection plates 952 and 954 can be controlled to direct particles along a first path 962 toward vessel 974 or along a second path 968 toward vessel 978. If the particle is not of interest (e.g., does not exhibit scattering or illumination information within a specified sort range), the deflector may allow the particle to continue along flow path 964. Such uncharged droplets may be diverted into a waste container, such as via aspirator 970.

[0135] Sorting electronics may be included to initiate the collection of measurements, receive fluorescent signals for the particles, and determine how to adjust the deflection plates to cause particle sorting. Exemplary implementations of the embodiment shown in Figure 9 include the BD FACSAria™ system of flow cytometers, commercially available from Becton, Dickinson and Company (Franklin Lakes, NJ).

[0136] In some embodiments, the subject particle sorting system is configured to sort particles using an enclosed particle sorting module, such as that described in U.S. Patent Publication No. 2017 / 0299493, filed March 28, 2017, the disclosure of which is incorporated herein by reference. In certain embodiments, particles (e.g., cells) of a sample are sorted using a sorting determination module having multiple sorting determination units, such as that described in U.S. Patent Publication No. 2020 / 0256781, the disclosure of which is incorporated herein by reference. In some embodiments, the subject system includes a particle sorting module with deflection plates, such as that described in U.S. Patent Publication No. 2017 / 0299493, filed March 28, 2017, the disclosure of which is incorporated herein by reference.

[0137] In certain embodiments, the system includes fluorescence imaging using a radio-frequency tagged luminescence image-enabled particle sorter, as shown in FIG. 10A. The particle sorter 1000 includes an illumination component 1000a including a light source 1001 (e.g., a 488 nm laser) generating an output beam of light 1001a, which is split into beams 1002a and 1002b by a beam splitter 1002. The light beam 1002a is propagated through an acousto-optic device (e.g., an acousto-optic deflector, AOD) 1003 to generate an output beam 1003a having one or more angularly deflected beams of light. In some cases, the output beam 1003a generated from the acousto-optic device 1003 includes a local oscillator beam and multiple radio-frequency comb beams. The light beam 1002b is propagated through an acousto-optic device (e.g., an acousto-optic deflector, AOD) 1004 to generate an output beam 1004a having one or more angularly deflected beams of light. In some cases, the output beam 1004a generated from the acousto-optic device 1004 includes a local oscillator beam and multiple high-frequency comb beams. The output beams 1003a and 1004a generated from the acousto-optic devices 1003 and 1004, respectively, are combined with a beam splitter 1005 to generate output beam 1005a, which is conveyed through an optical component 1006 (e.g., an objective lens) to illuminate particles in a flow cell 1007. In certain embodiments, the acousto-optic device 1003 (AOD) splits a single laser beam into an array of beamlets, each having a different optical frequency and angle. A second AOD 1004 adjusts the optical frequency of a reference beam, which is then overlapped with the array of beamlets at the beam combiner 1005. In certain embodiments, the light illumination system having a light source and an acousto-optical device may also include those described in Schraivogel et al. ("High-speed fluorescence image-enabled cell sorting", Science (2022), 375(6578), 305-320) and U.S. Patent Application Publication No. 2021 / 0404943, the disclosure of which is incorporated herein by reference.

[0138] Output beam 1005a illuminates sample particles 1008 propagating through flow cell 1007 (e.g., with sheath fluid 1009) in illumination region 1010. As shown in illumination region 1010, multiple beams (e.g., angularly deflected, high-frequency shifted optical beams shown as dots across illumination region 1010) overlap with a reference local oscillator beam (shown as shading across illumination region 1010). Due to their different optical frequencies, the overlapping beams exhibit beating behavior, whereby each beamlet emits a distinct frequency f 1~n carries a sinusoidal modulation.

[0139] Light from the illuminated sample is conveyed to a light detection system 1000b that includes multiple light detectors. The light detection system 1000b includes a forward-scattered light photodetector 1011 for generating a forward-scattered light image 1011a and a side-scattered light photodetector 1012 for generating a side-scattered light image 1012a. The light detection system 1000b also includes a bright-field light detector 1013 for generating a light loss image 1013a. In some embodiments, the forward-scattered light detector 1011 and the side-scattered light detector 1012 are photodiodes (e.g., avalanche photodiodes, APDs). In some cases, the bright-field light detector 1013 is a photomultiplier tube (PMT). Fluorescence from the illuminated sample is also detected by fluorescence light detectors 1014-1017. In some cases, the light detectors 1014-1017 are photomultiplier tubes. Light from the illuminated sample is directed through beam splitter 1020 to side scatter detection channel 1012 and fluorescence detection channels 1014-1017. Light detection system 1000b includes bandpass optical components 1021, 1022, 1023, and 1024 (e.g., dichroic mirrors) for transmitting light of predetermined wavelengths to photodetectors 1014-1017. In some cases, optical component 1021 is a 534 nm / 40 nm bandpass. In some cases, optical component 1022 is a 586 nm / 42 nm bandpass. In some cases, optical component 1023 is a 700 nm / 54 nm bandpass. In some cases, optical component 1024 is a 783 nm / 56 nm bandpass. The first number represents the center of the spectral band. The second number indicates the range of the spectral band. Thus, a 510 / 20 filter extends 10 nm on either side of the center of the spectral band, i.e., from 500 nm to 520 nm.

[0140] Data signals generated in response to light detected in scattered light detection channels 1011 and 1012, bright-field light detection channel 1013, and fluorescence detection channels 1014-1017 are processed by real-time digital processing by processors 1050 and 1051. Images 1011a-1017a can be generated in each light detection channel based on the data signals generated by processors 1050 and 1051. Image-enabled sorting is performed in response to a sorting signal generated by a sorting trigger 1052. Sorting component 1000c includes deflection plates 1031 for deflecting particles into a sample container 1032 or to a waste stream 1033. In some cases, sorting component 1000c is configured to sort particles in an enclosed particle sorting module, such as that described in U.S. Patent Application Publication No. 2017 / 0299493, filed March 28, 2017, the disclosure of which is incorporated herein by reference. In certain embodiments, the sorting component 1000c includes a sorting determination module having multiple sorting determination units, such as those described in U.S. Patent Application Publication No. 2020 / 0256781, the disclosure of which is incorporated herein by reference.

[0141] FIG. 10B illustrates image-enabled particle sorting data processing, according to certain embodiments. In some instances, the image-enabled particle sorting data processing is a low-latency data processing pipeline. Each photodetector generates pulses with high-frequency modulation that encodes an image (waveform). Fourier analysis is performed to reconstruct the image from the modulated pulses. The image processing pipeline generates a set of image features (image analysis) that are combined with features derived from the pulse processing pipeline (event packets). Real-time sorting electronics then classify particles based on the image features and generate sort decisions that are used to selectively charge droplets.

[0142] Non-transitory computer-readable storage medium Aspects of the present disclosure further include non-transitory computer-readable storage media having instructions for implementing the subject methods. The computer-readable storage medium may be employed by one or more computers for fully or partially automating systems for implementing the methods described herein. In certain embodiments, instructions according to the methods described herein may be encoded on a computer-readable medium in the form of "programming," in which case 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 floppy disks, hard disks, optical disks, magneto-optical disks, CD-ROMs, CD-Rs, magnetic tape, 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 the information so that it can be accessed and retrieved at a later date by a computer. The computer-implemented methods described herein may be performed using programming 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.

[0143] In some embodiments, a target computer-readable storage medium stores a computer program that, when loaded into a computer, includes instructions for determining (e.g., automatically) an alignment adjustment of the light scatter detector system of the flow cytometer by generating control data with the flow cytometer, determining a quantitative metric of the alignment of the light scatter detector system based on the control data, and determining an alignment adjustment of the light scatter detector system based on the quantitative alignment metric, as described above and herein. In some embodiments, the computer program, when loaded into a computer, further includes instructions for adjusting the light scatter detector system based at least in part on the determined alignment adjustment, e.g., as described above and herein.

[0144] kit Aspects of the present disclosure further include kits, which include storage media such as magneto-optical disks, CD-ROMs, CD-Rs, magnetic tape, non-volatile memory cards, ROMs, DVD-ROMs, Blu-ray discs, solid-state disks, and network-attached storage (NAS). Some of these program storage media, or others now in use or that may later be developed, may be included in the subject kits. In embodiments, the program storage media include instructions for determining alignment adjustments for a light scatter detector system of a flow cytometer, e.g., as described above and herein. In embodiments, the program storage medium includes instructions for adjusting the light scatter detector system based at least in part on the determined alignment adjustments, e.g., as described above and herein. In some embodiments, instructions included on computer-readable media provided with the subject kits, or portions thereof, may be implemented as software components of software for analyzing data. In these embodiments, a computerized control system according to the present disclosure may function as a software “plug-in” for an existing software package (e.g., FlowJo®).

[0145] In some embodiments, the subject kits may include a set of submicron standard / control beads for determining alignment adjustments, e.g., as described above and herein. In some cases, the beads may include four or more different sized beads and have diameters between 50 nm and 2000 nm. In some embodiments, the control beads include polystyrene. In some cases, the control beads include fluorescent beads. For example, the control beads may include seven different types of beads, i.e., six different sized polystyrene beads having diameters between 100 nm and 1200 nm, and one type of fluorescent bead. In some embodiments, the subject kits may include a set of beads for determining alignment adjustments and a program storage medium containing instructions, e.g., as described above and herein.

[0146] In addition to the above components, the subject kits may (in some embodiments) further include instructions for, for example, installing a plug-in to 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 present is information printed on a suitable medium or substrate, such as one or more pieces of paper on which the information is printed, kit packaging, a package insert, etc. Yet another form in which these instructions may be present is a computer-readable medium having the information recorded thereon, 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 the removed site.

[0147] Utilities The present methods and systems find use in a variety of applications where it is desirable to analyze and possibly sort particulate components of a sample in a fluid medium, such as a biological sample, and then store the sorted product for later use, such as, for example, therapeutic use. The present disclosure finds particular use where it is desirable to determine, e.g., perform, alignment adjustments for a light scatter detector system of a flow cytometer. Embodiments of the present disclosure also find use where it is desirable to provide a flow cytometer with improved cell sorting accuracy, enhanced particle collection, particle charging efficiency, accurate particle charging, and enhanced particle deflection during cell sorting.

[0148] The subject methods and systems find use in applications where it is desirable to reduce variation across different flow cytometers and / or compare data generated by different flow cytometers. Embodiments of the present disclosure also find use where it is desirable to identify extracellular vesicles or specific cell populations in a biological sample and / or derive the diameter or refractive index of small particles in a sample.

[0149] The subject methods and systems find use in a variety of applications where cellular analysis of biological samples may be desired for research, laboratory testing, or therapeutic use. In some embodiments, the subject systems and methods facilitate the analysis of cells obtained from fluid or tissue samples, e.g., specimens for diseases, including, but not limited to, cancer. For example, the subject methods and systems facilitate obtaining cells from fluid or tissue samples used as research or diagnostic samples for diseases such as cancer. Similarly, the subject methods and systems may facilitate obtaining cells from fluid or tissue samples used in therapy. The disclosed methods and devices enable the separation and collection of cells from biological samples (e.g., organs, tissues, tissue fragments, bodily fluids) with improved efficiency and at lower cost compared to conventional flow cytometry systems.

[0150] Notwithstanding the scope of the appended claims, the present disclosure is also defined by the following clauses. 1. A method for determining alignment adjustment of a light scatter detector system of a flow cytometer, comprising: (a) generating control data by a flow cytometer; (b) determining a quantitative metric of the alignment of the light scattering detector system based on the control data; and (c) determining an alignment adjustment for the light scattering detector system based on the quantitative alignment metric; and A method comprising: 2. The method of clause 1, wherein determining the quantitative alignment metric includes calculating a collection angle based on control data. 3. The method of clause 2, wherein the collection angle is calculated relative to the interrogation point of the flow cytometer. 4. The method of clause 2, wherein the collection angle is calculated using a light scattering model. 5. The method of clause 4, wherein the light scattering model comprises a Mie light scattering model. 6. The method of any one of clauses 1 to 5, wherein the light scatter detector system comprises a side scatter detector, a forward scatter detector, or both. 7. Generating control data i) illuminating the beads in a flow cytometer; ii) measuring the data signal generated by the light scattering detector system; and 7. The method of any one of clauses 1 to 6, comprising: 8. The method of clause 7, wherein control data is generated for a plurality of beads, the plurality of beads comprising a first bead and a second bead that is larger than the first bead. 9. The method of clause 8, wherein the plurality of beads have a diameter of 50 nm to 3000 nm. 10. The method of clause 9, wherein the plurality of beads have a diameter of 100 nm to 1200 nm. 11. The method of any one of clauses 8 to 10, wherein the plurality of beads comprises polystyrene. 12. The method of any one of clauses 8 to 11, wherein the plurality of beads comprises fluorescent beads. 13. The method of any one of clauses 1 to 12, further comprising providing an alignment adjustment to a user. 14. The method of clause 13, wherein the alignment adjustment comprises a software alignment adjustment. 15. The method of clause 14, wherein the software alignment adjustments include collection angle calibration values, trigger thresholds, trigger channel options, detector setting options, pulse processing options, or any combination thereof. 16. The method of clause 13, wherein the alignment adjustment includes hardware alignment adjustment. 17. The method of clause 16, wherein the hardware alignment adjustment includes an aperture adjustment distance, an aperture adjustment angle, a detector adjustment distance, a detector adjustment angle, or any combination thereof. 18. The method of any one of clauses 1 to 17, further comprising adjusting the light scattering detector system based at least in part on the alignment adjustment. 19. The method of clause 18, wherein adjusting the light scattering detector system includes performing a software alignment adjustment. 20. The method of clause 19, wherein the software alignment adjustment includes adjusting a collection angle calibration value, a trigger threshold, a trigger channel option, a detector setting option, a pulse processing option, or any combination thereof. 21. The method of clause 18, wherein adjusting the light scattering detector system includes performing a hardware alignment adjustment. 22. The method of clause 21, wherein the hardware alignment adjustment comprises adjusting the position and / or orientation of an optical alignment component of the flow cytometer. 23. The method of clause 22, wherein the optical conditioning component is an aperture, a filter, or both. 24. The method of any one of clauses 21 to 23, wherein adjusting the hardware alignment comprises adjusting the position and / or orientation of a light scattering detector of a light scattering detector system. 25. A system configured to carry out the method according to any one of clauses 1 to 24. 26. A system comprising: a light scatter detector system configured to generate data signals from light received from an interrogation point of the flow cytometer; 1. A processor comprising: a memory operatively coupled to the processor, the memory storing instructions, the instructions, when executed by the processor, causing the processor to: (a) generating control data by a flow cytometer; (b) determining a quantitative metric of the alignment of the light scattering detector system based on the control data; and (c) determining alignment adjustments for the light scattering detector system based on the quantitative alignment metrics; and A system comprising: 27. The system of clause 26, wherein determining the quantitative alignment metric includes calculating a collection angle based on control data. 28. The system of clause 27, wherein the collection angle is calculated relative to the interrogation point of the flow cytometer. 29. The system of clause 27, wherein the collection angle is calculated using a light scattering model. 30. The system of clause 29, wherein the light scattering model comprises a Mie light scattering model. 31. The system of any one of clauses 26 to 30, wherein the light scatter detector system comprises a side scatter detector, a forward scatter detector, or both. 32. Generating control data is i) illuminating the beads in a flow cytometer; ii) measuring the data signal generated by the light scattering detector system; and 32. The system of any one of clauses 26 to 31, comprising: 33. The system of clause 32, wherein the control data is generated for a plurality of beads, the plurality of beads comprising a first bead and a second bead that is larger than the first bead. 34. The system of clause 33, wherein the plurality of beads have a diameter of 50 nm to 3000 nm. 35. The system of clause 34, wherein the plurality of beads have a diameter of 100 nm to 1200 nm. 36. The system of any one of clauses 33 to 35, wherein the plurality of beads comprises polystyrene. 37. The system of any one of clauses 33 to 36, wherein the plurality of beads comprises fluorescent beads. 38. A system according to any one of clauses 26 to 37, wherein the instructions, when executed by the processor, further cause the processor to provide alignment adjustments to a user. 39. The system of clause 38, wherein the alignment adjustment comprises a software alignment adjustment. 40. The system of clause 39, wherein the software alignment adjustments include collection angle calibration values, trigger thresholds, trigger channel options, detector setting options, pulse processing options, or any combination thereof. 41. The system of clause 38, wherein the alignment adjustment includes hardware alignment adjustment. 42. The system of clause 41, wherein the hardware alignment adjustment includes an aperture adjustment distance, an aperture adjustment angle, a detector adjustment distance, a detector adjustment angle, or any combination thereof. 43. The system of any one of clauses 26 to 42, wherein the instructions, when executed by a processor, further cause the processor to adjust the light scattering detector system based at least in part on the alignment adjustment. 44. The system of clause 43, wherein adjusting the light scattering detector system includes performing a software alignment adjustment. 45. The system of clause 44, wherein the software alignment adjustment includes adjusting a collection angle calibration value, a trigger threshold, a trigger channel option, a detector setting option, a pulse processing option, or any combination thereof. 46. ​​The system of clause 43, wherein adjusting the light scattering detector system includes performing hardware alignment adjustments. 47. The system of clause 46, wherein the hardware alignment adjustment includes adjusting the position and / or orientation of optical alignment components of the flow cytometer. 48. The system of clause 47, wherein the optical conditioning component is an aperture, a filter, or both. 49. The system of any one of clauses 46 to 48, wherein the hardware alignment adjustment comprises adjusting the position and / or orientation of the light scattering detector of the light scattering detector system. 50.(a) Generating control data by a flow cytometer; (b) determining a quantitative metric of the alignment of the light scattering detector system based on the control data; and (c) determining an alignment adjustment for the light scattering detector system based on the quantitative alignment metric; and A non-transitory computer-readable storage medium having stored thereon instructions for determining alignment adjustments for a light scatter detector system of a flow cytometer by a method comprising: 51. The non-transitory computer-readable storage medium of clause 50, wherein determining the quantitative alignment metric includes calculating a collection angle based on control data. 52. The non-transitory computer-readable storage medium of clause 51, wherein the collection angle is calculated relative to an interrogation point of a flow cytometer. 53. The non-transitory computer-readable storage medium of clause 51, wherein the collection angle is calculated using a light scattering model. 54. The non-transitory computer-readable storage medium of clause 53, wherein the light scattering model comprises a Mie light scattering model. 55. The non-transitory computer-readable storage medium of any one of clauses 50 to 54, wherein the light scatter detector system comprises a side scatter detector, a forward scatter detector, or both. 56. Generating control data is i) illuminating the beads in a flow cytometer; ii) measuring a data signal generated by the light scattering detector system. 57. The non-transitory computer-readable storage medium of clause 56, wherein the control data is generated for a plurality of beads, the plurality of beads comprising a first bead and a second bead that is larger than the first bead. 58. The non-transitory computer-readable storage medium of clause 57, wherein the plurality of beads have a diameter of between 50 nm and 3000 nm. 59. The non-transitory computer-readable storage medium of clause 58, wherein the plurality of beads have a diameter of 100 nm to 1200 nm. 60. The non-transitory computer-readable storage medium of any one of clauses 57 to 59, wherein the plurality of beads comprises polystyrene. 61. The non-transitory computer-readable storage medium of any one of clauses 57 to 60, wherein the plurality of beads comprises fluorescent beads. 62. The non-transitory computer-readable storage medium of any one of clauses 50 to 61, further comprising providing alignment adjustments to a user. 63. The non-transitory computer-readable storage medium of clause 62, wherein the alignment adjustment comprises software alignment adjustment. 64. The non-transitory computer-readable storage medium of clause 63, wherein the software alignment adjustments include collection angle calibration values, trigger thresholds, trigger channel options, detector setting options, pulse processing options, or any combination thereof. 65. The non-transitory computer-readable storage medium of clause 62, wherein the alignment adjustment includes hardware alignment adjustment. 66. The non-transitory computer-readable storage medium of clause 65, wherein the hardware alignment adjustment includes an aperture adjustment distance, an aperture adjustment angle, a detector adjustment distance, a detector adjustment angle, or any combination thereof. 67. The non-transitory computer-readable storage medium of any one of clauses 50 to 66, further comprising adjusting the light scattering detector system based at least in part on the alignment adjustment. 68. The non-transitory computer-readable storage medium of clause 67, wherein adjusting the light scattering detector system includes performing a software alignment adjustment. 69. The non-transitory computer-readable storage medium of clause 68, wherein the software alignment adjustment includes adjusting a collection angle calibration value, a trigger threshold, a trigger channel option, a detector setting option, a pulse processing option, or any combination thereof. 70. The non-transitory computer-readable storage medium of clause 67, wherein adjusting the light scattering detector system includes performing hardware alignment adjustments. 71. The non-transitory computer-readable storage medium of clause 70, wherein the hardware alignment adjustment includes adjusting the position and / or orientation of an optical alignment component of the flow cytometer. 72. The non-transitory computer-readable storage medium of clause 71, wherein the optical conditioning component is an aperture, a filter, or both. 73. The non-transitory computer-readable storage medium of any one of clauses 70 to 72, wherein the hardware alignment adjustment includes adjusting the position and / or orientation of a light scattering detector of a light scattering detector system. A kit comprising a set of standard beads for use in flow cytometry having 74.5 or more known diameter sizes, the beads having diameters between 50 nm and 3000 nm. 75. The kit of clause 74, wherein the beads comprise six different known diameter sizes. 76. The kit of clause 74 or 75, wherein the beads have a diameter of 50 nm to 1200 nm. 77. The kit of any one of clauses 74 to 76, wherein the beads comprise polystyrene. 78. The kit of any one of clauses 74 to 77, wherein the kit further comprises fluorescent beads.

[0151] Although the foregoing disclosure has been described in some detail by way of illustration and example for clarity of understanding, it will be readily apparent to those skilled in the art that certain changes and modifications can be made in light of the teachings of the present invention without departing from the spirit or scope of the appended claims.

[0152] Accordingly, the foregoing merely illustrates the principles of the present disclosure. It will be appreciated that those skilled in the art will be able to devise various configurations, not explicitly described or shown herein, that embody the principles of the present disclosure and are within its spirit and scope. Furthermore, all examples and conditional language recited herein are intended primarily to aid the reader in understanding the principles of the present disclosure and the concepts that the inventors have contributed to advancing the art, and should not be construed as being limited to such specifically recited examples and conditions. Furthermore, all statements herein reciting principles, aspects, and embodiments of the present disclosure, as well as specific examples thereof, are intended to encompass both structural and functional equivalents thereof. Furthermore, such equivalents are intended to include both currently known equivalents and equivalents developed in the future, i.e., any elements developed that perform the same function, regardless of structure. Furthermore, nothing disclosed herein is intended as a dedication to the public, regardless of whether such disclosure is expressly recited in the claims.

[0153] Accordingly, the scope of the present disclosure is not intended to be limited to the exemplary embodiments shown and described herein. Rather, the scope and spirit of the present disclosure are embodied by the appended claims. In the claims, 35 U.S.C. §112(f) or 35 U.S.C. §112(6) are expressly defined as being invoked for a limitation in a claim only if the exact phrase "means for" or the exact phrase "step" appears at the beginning of such limitation in the claim. If such exact phrases are not used in a claim limitation, 35 U.S.C. §112(f) or 35 U.S.C. §112(6) is not invoked.

[0154] CROSS-REFERENCE TO RELATED APPLICATIONS Pursuant to 35 U.S.C. § 119(e), this application claims priority to the filing date of U.S. Provisional Patent Application No. 63 / 632,452, filed April 10, 2024, the disclosure of which is incorporated herein by reference in its entirety.

Claims

1. 1. A method for determining alignment adjustment of a light scatter detector system of a flow cytometer, comprising: (d) generating control data with the flow cytometer; (e) determining a quantitative metric of alignment of the light scattering detector system based on the control data; and (f) determining the alignment adjustment of the light scattering detector system based on the quantitative alignment metric; and A method comprising:

2. The method of claim 1 , wherein determining the quantitative alignment metric comprises calculating a collection angle based on the contrast data.

3. 3. The method of claim 2, wherein the collection angle is calculated relative to an interrogation point of the flow cytometer or calculated using a light scattering model.

4. 4. The method of claim 1, wherein the light scatter detector system comprises a side scatter detector, a forward scatter detector, or both.

5. generating said control data iii) illuminating the beads in the flow cytometer; iv) measuring the data signals generated by the light scattering detector system; and 5. The method of claim 1, comprising:

6. The method of claim 1 , further comprising providing the alignment adjustment to a user.

7. The method of claim 1 , further comprising adjusting the light scattering detector system based at least in part on the alignment adjustment.

8. The method of claim 7 , wherein adjusting the light scattering detector system comprises performing a software alignment adjustment.

9. The method of claim 8 , wherein the software alignment adjustment comprises adjusting a collection angle calibration value, a trigger threshold, a trigger channel option, a detector setting option, a pulse processing option, or any combination thereof.

10. The method of claim 9 , wherein adjusting the light scattering detector system comprises performing a hardware alignment adjustment.

11. The method of claim 10 , wherein the hardware alignment adjustment comprises adjusting the position and / or orientation of optical alignment components of the flow cytometer.

12. The method of claim 11 , wherein the hardware alignment adjustment comprises adjusting the position and / or orientation of a light scatter detector of the light scatter detector system.

13. 1. A system comprising: a light scatter detector system configured to generate data signals from light received from an interrogation point of the flow cytometer; 1. A processor comprising: a memory operatively coupled to the processor, the memory storing instructions that, when executed by the processor, cause the processor to: (d) generating control data with the flow cytometer; (e) determining a quantitative metric of alignment of the light scattering detector system based on the control data; and (f) determining an alignment adjustment for the light scattering detector system based on the quantitative alignment metric; and a processor that analyzes the control data to perform A system comprising:

14. (d) generating control data by a flow cytometer; (e) determining a quantitative metric of the alignment of the light scattering detector system based on the control data; and (f) determining an alignment adjustment for the light scattering detector system based on the quantitative alignment metric; and a non-transitory computer readable storage medium having stored thereon instructions for determining the alignment adjustment of the light scatter detector system of the flow cytometer by a method comprising:

15. A kit comprising a set of standard beads for use in flow cytometry having five or more known diameter sizes, said beads having diameters between 50 nm and 3000 nm.

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