Abstract: In flow cytometry, particles (2) can be distinguished between populations (8) by combining n-dimensional parameter data, which may be derived from signal data from a particle, to mathematically achieve numerical results representative of an alteration (48). An alteration may include a rotational alteration, a scaled alteration, or perhaps even a translational alteration. Alterations may enhance separation of data points which may provide real-time classification (49) of signal data corresponding to individual particles into one of at least two populations.

Abstract: Aspects of the present disclosure include reconfigurable integrated circuits for characterizing particles of a sample in a flow stream. Reconfigurable integrated circuits according to certain embodiments are programmed to calculate parameters of a particle in a flow stream from detected light; compare the calculated parameters of the particle with parameters of one or more particle classifications; classify the particle based on the comparison between the parameters of the particle classifications and the calculated parameters of the particle; and adjust one or more parameters of the particle classifications based on the calculated parameters of the particle. Methods for characterizing particles in a flow stream with the subject integrated circuits are also described. Systems and integrated circuit devices programmed for practicing the subject methods, such as on a flow cytometer, are also provided.

Abstract: Flow cytometric droplet dispensing systems and methods for using the same to flow cytometrically dispense droplets into partitions are provided. Aspects of embodiments of the systems include sorting flow cytometers configured to sort both particle-occupied and particle-unoccupied droplets into a partition. Also provided are methods of using the systems. Systems and methods of the invention find use in a variety of applications.

Abstract: Aspects of the present disclosure include reconfigurable integrated circuits for characterizing particles of a sample in a flow stream. Reconfigurable integrated circuits according to certain embodiments are programmed to calculate parameters of a particle in a flow stream from detected light; compare the calculated parameters of the particle with parameters of one or more particle classifications; classify the particle based on the comparison between the parameters of the particle classifications and the calculated parameters of the particle; and adjust one or more parameters of the particle classifications based on the calculated parameters of the particle. Methods for characterizing particles in a flow stream with the subject integrated circuits are also described. Systems and integrated circuit devices programmed for practicing the subject methods, such as on a flow cytometer, are also provided.

Abstract: Some embodiments of the methods provided herein relate to sample analysis and particle characterization methods. Some such embodiments include receiving, from a particle analyzer, measurements for a first portion of particles associated with an experiment. Some embodiments also include generating a tree representing groups of related particles based at least in part on the measurements, wherein the tree includes at least three groups. Some embodiments also include generating a measure of relatedness between a first group and a second group of the tree based at least in part on the measurements. Some embodiments also include and configuring the particle analyzer to classify a subsequent particle associated with the experiment with the first group real-time, wherein the subsequent particle is not included in the first portion of particles. Some embodiments also include sorting the subsequent particle.

Abstract: In flow cytometry, particles (2) can be distinguished between populations (8) by combining n-dimensional parameter data, which may be derived from signal data from a particle, to mathematically achieve numerical results representative of an alteration (48). An alteration may include a rotational alteration, a scaled alteration, or perhaps even a translational alteration. Alterations may enhance separation of data points which may provide real-time classification (49) of signal data corresponding to individual particles into one of at least two populations.

Abstract: Aspects of the present disclosure include methods for integrating data quality assessment with data acquisition with a flow cytometer. Methods according to certain embodiments include detecting light with a light detection system from a sample irradiated by a light source in a flow stream, generating event data signals in response to events detected with the light detection system, binning the generated event data signals in a plurality of binning windows having overlapping data bins and assessing the plurality of binning windows for outlier events in the generated data signals. Systems having a processor with memory having instructions for practicing the subject methods are also described. Non-transitory computer readable storage medium is also provided.

Abstract: In flow cytometry, particles (2) can be distinguished between populations (8) by combining n-dimensional parameter data, which may be derived from signal data from a particle, to mathematically achieve numerical results representative of an alteration (48). An alteration may include a rotational alteration, a scaled alteration, or perhaps even a translational alteration. Alterations may enhance separation of data points which may provide real-time classification (49) of signal data corresponding to individual particles into one of at least two populations.

Abstract: Flow cytometric droplet dispensing systems and methods for using the same to flow cytometrically dispense droplets into partitions are provided. Aspects of embodiments of the systems include sorting flow cytometers configured to sort both particle-occupied and particle-unoccupied droplets into a partition. Also provided are methods of using the systems. Systems and methods of the invention find use in a variety of applications.

Abstract: Some embodiments of the methods provided herein relate to sample analysis and particle characterization methods. Some such embodiments include receiving, from a particle analyzer, measurements for a first portion of particles associated with an experiment. Some embodiments also include generating a tree representing groups of related particles based at least in part on the measurements, wherein the tree includes at least three groups. Some embodiments also include generating a measure of relatedness between a first group and a second group of the tree based at least in part on the measurements. Some embodiments also include and configuring the particle analyzer to classify a subsequent particle associated with the experiment with the first group real-time, wherein the subsequent particle is not included in the first portion of particles. Some embodiments also include sorting the subsequent particle.

Abstract: Some embodiments of the methods provided herein relate to sample analysis and particle characterization methods. Some such embodiments include receiving, from a particle analyzer, measurements for a first portion of particles associated with an experiment. Some embodiments also include generating a tree representing groups of related particles based at least in part on the measurements, wherein the tree includes at least three groups. Some embodiments also include generating a measure of relatedness between a first group and a second group of the tree based at least in part on the measurements. Some embodiments also include and configuring the particle analyzer to classify a subsequent particle associated with the experiment with the first group real-time, wherein the subsequent particle is not included in the first portion of particles. Some embodiments also include sorting the subsequent particle.

Abstract: Aspects of the present disclosure include reconfigurable integrated circuits for characterizing particles of a sample in a flow stream. Reconfigurable integrated circuits according to certain embodiments are programmed to calculate parameters of a particle in a flow stream from detected light; compare the calculated parameters of the particle with parameters of one or more particle classifications; classify the particle based on the comparison between the parameters of the particle classifications and the calculated parameters of the particle; and adjust one or more parameters of the particle classifications based on the calculated parameters of the particle. Methods for characterizing particles in a flow stream with the subject integrated circuits are also described. Systems and integrated circuit devices programmed for practicing the subject methods, such as on a flow cytometer, are also provided.

Abstract: In flow cytometry, particles (2) can be distinguished between populations (8) by combining n-dimensional parameter data, which may be derived from signal data from a particle, to mathematically achieve numerical results representative of an alteration (48). An alteration may include a rotational alteration, a scaled alteration, or perhaps even a translational alteration. Alterations may enhance separation of data points which may provide real-time classification (49) of signal data corresponding to individual particles into one of at least two populations.

Abstract: In flow cytometry, particles (2) can be distinguished between populations (8) by combining n-dimensional parameter data, which may be derived from signal data from a particle, to mathematically achieve numerical results representative of an alteration (48). An alteration may include a rotational alteration, a scaled alteration, or perhaps even a translational alteration. Alterations may enhance separation of data points which may provide real-time classification (49) of signal data corresponding to individual particles into one of at least two populations.

Abstract: Some embodiments of the methods provided herein relate to sample analysis and particle characterization methods. Some such embodiments include receiving, from a particle analyzer, measurements for a first portion of particles associated with an experiment. Some embodiments also include generating a tree representing groups of related particles based at least in part on the measurements, wherein the tree includes at least three groups. Some embodiments also include generating a measure of relatedness between a first group and a second group of the tree based at least in part on the measurements. Some embodiments also include and configuring the particle analyzer to classify a subsequent particle associated with the experiment with the first group real-time, wherein the subsequent particle is not included in the first portion of particles. Some embodiments also include sorting the subsequent particle.

Abstract: In flow cytometry, particles (2) can be distinguished between populations (8) by combining n-dimensional parameter data, which may be derived from signal data from a particle, to mathematically achieve numerical results representative of an alteration (48). An alteration may include a rotational alteration, a scaled alteration, or perhaps even a translational alteration. Alterations may enhance separation of data points which may provide real-time classification (49) of signal data corresponding to individual particles into one of at least two populations.

Abstract: In flow cytometry, particles (2) can be distinguished between populations (8) by combining n-dimensional parameter data, which may be derived from signal data from a particle, to mathematically achieve numerical results representative of an alteration (48). An alteration may include a rotational alteration, a scaled alteration, or perhaps even a translational alteration. Alterations may enhance separation of data points which may provide real-time classification (49) of signal data corresponding to individual particles into one of at least two populations.

Abstract: In flow cytometry, particles (2) can be distinguished between populations (8) by combining n-dimensional parameter data, which may be derived from signal data from a particle, to mathematically achieve numerical results representative of an alteration (48). An alteration may include a rotational alteration, a scaled alteration, or perhaps even a translational alteration. Alterations may enhance separation of data points which may provide real-time classification (49) of signal data corresponding to individual particles into one of at least two populations.

Abstract: In flow cytometry, particles (2) can be distinguished between populations (8) by combining n-dimensional parameter data, which may be derived from signal data from a particle, to mathematically achieve numerical results representative of an alteration (48). An alteration may include a rotational alteration, a scaled alteration, or perhaps even a translational alteration. Alterations may enhance separation of data points which may provide real-time classification (49) of signal data corresponding to individual particles into one of at least two populations.

Abstract: In flow cytometry, particles (2) can be distinguished between populations (8) by combining n-dimensional parameter data, which may be derived from signal data from a particle, to mathematically achieve numerical results representative of an alteration (48). An alteration may include a rotational alteration, a scaled alteration, or perhaps even a translational alteration. Alterations may enhance separation of data points which may provide real-time classification (49) of signal data corresponding to individual particles into one of at least two populations.