Abstract: Methods for classifying fluorescent flow cytometer data are provided. In some instances, methods include processing the flow cytometer data with a supervised algorithm configured to cluster the fluorescent flow cytometer data into distinct populations according to the relationship of data points to relevant threshold values. In embodiments, methods include determining a measure of spillover spreading by calculating spillover spreading coefficients and combining them in a spillover spreading matrix. In some embodiments, populations of fluorescent flow cytometer data are adjusted to subtract the magnitude of spillover spreading. In embodiments, spillover spreading adjusted populations are partitioned after potential partitions are evaluated relative to the threshold values. In embodiments, partitioned populations of fluorescent flow cytometer data are classified (i.e., phenotyped) according to a hierarchy. Systems and computer-readable media for classifying fluorescent flow cytometer data are also provided.

Abstract: Methods for characterizing spillover spreading originating from a first fluorochrome in fluorescent flow cytometer data collected for a second fluorochrome are provided. In some embodiments, methods include partitioning the fluorescent flow cytometer data according to the intensity of the data relative to the first fluorochrome. In embodiments, methods also include estimating with a first linear regression a zero-adjusted standard deviation for the intensity of light collected from the second fluorochrome for each of the partitioned quantiles based on the assumption that the intensity of light collected from the first fluorochrome is zero, and obtaining with a second linear regression a spillover spreading coefficient from the zero-adjusted standard deviations. Systems and computer-readable media for characterizing spillover spreading originating from a first fluorochrome in fluorescent flow cytometer data collected for a second fluorochrome are also provided.

Abstract: Methods for characterizing spillover spreading originating from a first fluorochrome in fluorescent flow cytometer data collected for a second fluorochrome are provided. In some embodiments, methods include partitioning the fluorescent flow cytometer data according to the intensity of the data relative to the first fluorochrome. In embodiments, methods also include estimating with a first linear regression a zero-adjusted standard deviation for the intensity of light collected from the second fluorochrome for each of the partitioned quantiles based on the assumption that the intensity of light collected from the first fluorochrome is zero, and obtaining with a second linear regression a spillover spreading coefficient from the zero-adjusted standard deviations. Systems and computer-readable media for characterizing spillover spreading originating from a first fluorochrome in fluorescent flow cytometer data collected for a second fluorochrome are also provided.

Abstract: Methods for classifying fluorescent flow cytometer data are provided. In some instances, methods include processing the flow cytometer data with a supervised algorithm configured to cluster the fluorescent flow cytometer data into distinct populations according to the relationship of data points to relevant threshold values. In embodiments, methods include determining a measure of spillover spreading by calculating spillover spreading coefficients and combining them in a spillover spreading matrix. In some embodiments, populations of fluorescent flow cytometer data are adjusted to subtract the magnitude of spillover spreading. In embodiments, spillover spreading adjusted populations are partitioned after potential partitions are evaluated relative to the threshold values. In embodiments, partitioned populations of fluorescent flow cytometer data are classified (i.e., phenotyped) according to a hierarchy. Systems and computer-readable media for classifying fluorescent flow cytometer data are also provided.

Abstract: Methods for classifying fluorescent flow cytometer data are provided. In some instances, methods include processing the flow cytometer data with a supervised algorithm configured to cluster the fluorescent flow cytometer data into distinct populations according to the relationship of data points to relevant threshold values. In embodiments, methods include determining a measure of spillover spreading by calculating spillover spreading coefficients and combining them in a spillover spreading matrix. In some embodiments, populations of fluorescent flow cytometer data are adjusted to subtract the magnitude of spillover spreading. In embodiments, spillover spreading adjusted populations are partitioned after potential partitions are evaluated relative to the threshold values. In embodiments, partitioned populations of fluorescent flow cytometer data are classified (i.e., phenotyped) according to a hierarchy. Systems and computer-readable media for classifying fluorescent flow cytometer data are also provided.

Abstract: Methods for characterizing spillover spreading originating from a first fluorochrome in fluorescent flow cytometer data collected for a second fluorochrome are provided. In some embodiments, methods include partitioning the fluorescent flow cytometer data according to the intensity of the data relative to the first fluorochrome. In embodiments, methods also include estimating with a first linear regression a zero-adjusted standard deviation for the intensity of light collected from the second fluorochrome for each of the partitioned quantiles based on the assumption that the intensity of light collected from the first fluorochrome is zero, and obtaining with a second linear regression a spillover spreading coefficient from the zero-adjusted standard deviations. Systems and computer-readable media for characterizing spillover spreading originating from a first fluorochrome in fluorescent flow cytometer data collected for a second fluorochrome are also provided.

Abstract: Methods for classifying fluorescent flow cytometer data are provided. In some instances, methods include processing the flow cytometer data with a supervised algorithm configured to cluster the fluorescent flow cytometer data into distinct populations according to the relationship of data points to relevant threshold values. In embodiments, methods include determining a measure of spillover spreading by calculating spillover spreading coefficients and combining them in a spillover spreading matrix. In some embodiments, populations of fluorescent flow cytometer data are adjusted to subtract the magnitude of spillover spreading. In embodiments, spillover spreading adjusted populations are partitioned after potential partitions are evaluated relative to the threshold values. In embodiments, partitioned populations of fluorescent flow cytometer data are classified (i.e., phenotyped) according to a hierarchy. Systems and computer-readable media for classifying fluorescent flow cytometer data are also provided.