Methods, devices, and systems for automated cellular analysis of a body fluid sample are disclosed. The methods, devices, and systems apply watershed transform to data, generated by flowing a body fluid sample through a flow cytometer, to determine threshold(s) to be used for analysis of the data.

A system and method for determining a trajectory parameter of particles, comprising receiving a plurality of particles at a microfluidic channel, applying a force to each particle of the microfluidic channel, acquiring a dataset of each particle, measuring a trajectory of the particle, and determining a trajectory parameter of the particles.

Use of (i) an anti-CD3 antibody, (ii) an anti-CD56 antibody, (iii) an anti-CD14 antibody, (iv) an anti-CD38 antibody, (v) an anti-CD45 antibody, (vi) an anti-CD90 antibody, (vii) an anti-CD135 antibody, (viii) an anti-CD10 antibody, (ix) an anti-CD11c antibody, (x) an anti-CD19 antibody, (xi) an anti-CD34 antibody, (xii) an anti-CD45RA antibody, (xiii) an anti-CD7 antibody, (xiv) an anti-CD71 antibody, (xv) an anti-CD41/CD61 complex antibody or an anti-CD41 antibody and/or an anti-CD61 antibody (xvi) an anti-CD33 antibody and/or an anti-CD66b antibody, for identifying hematopoietic cell subtypes in an isolated sample, determining the relative frequency of hematopoietic cell subtypes in an isolated sample and/or quantifying the number of cells within hematopoietic cell subtypes in an isolated sample, wherein each of (i) to (xvi) is labelled with a different fluorochrome, wherein when (xvi) is an anti-CD33 antibody and an anti-CD66b antibody, the anti-CD33 antibody and anti-CD66b are labelled with the same fluorochrome, and wherein when (xv) is an anti-CD41 antibody and an anti-CD61 antibody, the anti-CD4 antibody and the anti-CD61 antibody are labelled with the same fluorochrome.

A main object of the present technology is to provide a technique for automatically proposing a better combination of fluorochrome-labeled antibodies.

The present technology provides an information processing apparatus including a processing unit that generates a combination list of phosphors with respect to biomolecules on the basis of expression level categories in which a plurality of biomolecules to be used for analysis of a sample is classified on the basis of expression levels in the sample, brightness categories in which a plurality of phosphors usable for the analysis of the sample is classified on the basis of brightness, and correlation information between the plurality of phosphors, in which the processing unit selects the phosphors to be allocated to the biomolecules in the combination list from phosphors belonging to a brightness category associated with an expression level category to which the biomolecules belong.

The disclosure provides methods, systems and related software, for automated or semi-automated sorting and/or isolating cells with visually distinguishable phenotypes. In some embodiments, the methods comprise providing a plurality cells with a photo-activatable detectable marker in their respective nuclei. The plurality of cells are imaged and, based on the image, the status for one or more visually identifiable phenotypes are determined. Cells determined to have the desired phenotype status are specifically exposed to a light wavelength for a time sufficient to uniquely activate the photo-activatable detectable marker in the individual cells with the desired phenotype status. The cells are then sorted on the basis of the activated detectable marker. The disclosure also provides methods for preparation and isolation of nuclei from fixed, adherent cells for analysis.

Aspects of the present disclosure include methods for processing and scaling cytometric data. Methods according to certain embodiments include obtaining cytometric data for a sample, wherein the cytometric data comprises measurements of a plurality of parameters from particles irradiated in the sample flowing in a flow stream; identifying a parameter of interest; specifying positive and negative measurement intervals on the parameter of interest; scaling the cytometric data by transforming the parameter of interest based at least in part on the corresponding specified positive and negative intervals. Systems for practicing the subject methods are also provided. Non-transitory computer readable storage mediums are also described.

A framework that includes a feature extractor and a cluster component for clustering is described herein. The framework supports (1) offline image-based unsupervised clustering that replaces time-consuming manual gating; (2) online image-based single cell sorting. During training, one or multiple cell image datasets with or without ground truth are used to train feature extractor, which is based on a neural network including several convolutional layers. Once trained, the feature extractor is used to extract features of cell images for unsupervised cell clustering and sorting. In addition, additional datasets may be used to further refine the feature extractor after it has been trained.

A method for presenting flow cytometry data includes accessing sensed data of a flow cytometer used to sense optical responses from a sample including a plurality of components; estimating optical characteristic values, physical characteristic values, and counts of the plurality of components based on the sensed data; transforming at least some of the optical characteristic values, the physical characteristic values, or the counts, of at least one of the plurality of components, by at least one of rotating or translating, to provide transformed values; and presenting a two-dimensional (2D) dot plot base on the transformed values and based on at least some of the optical characteristic values, the physical characteristic values, and the counts, of the plurality of components. The 2D dot plot has a first axis corresponding to the optical characteristic values and a second axis corresponding to the physical characteristic values.

Embodiments of the present invention encompass systems and methods for determining detection limits for various antibody-dye conjugates for flow cytometry. Exemplary techniques involve a linear superpositioning approach of spillover-induced enlargements of normally distributed measurement errors.

Disclosed herein include systems, devices, computer readable media, and methods for subsampling flow cytometric event data. First and second flow cytometric event data can be transformed into a lower-dimensional space, associated with a plurality of bins, and assigned to a first bin and a second bin. Subsampled flow cytometric event data comprising the first flow cytometric event data can be generated. The subsampled flow cytometric event data can comprise the second flow cytometric event data if the first bin and the second bin are different. The subsampled flow cytometric event data may not comprise the second flow cytometric event data if the first bin and the second bin are identical.