Abstract: Disclosed are methods, systems, and articles of manufacture for performing a process on biological samples. An analysis of biological samples in multiple regions of interest in a microfluidic device and a timeline correlated with the analysis may be identified. One or more region-of-interest types for the multiple regions of interest may be determined; and multiple characteristics may be determined for the biological samples based at least in part upon the one or more region-of-interest types. Associated data that respectively correspond to the multiple regions of interest in a user interface for at least a portion of the biological samples in the user interface based at least in part upon the multiple identifiers and the timeline. A count of the biological samples in a region of interest may be determined based at least in part upon a class or type of data using a convolutional neural network (CNN).

Abstract: Methods are described herein for isolating clonal populations of T cells having a defined genetic modification. The methods are performed, at least in part, in a microfluidic device comprising one or more sequestration pens. The methods include the steps of: maintaining individual T cells (or precursors thereof) that have undergone a genomic editing process in corresponding sequestration pens of a microfluidic device; expanding the T cells into respective clonal populations of T cells; detecting, in one or more T cells of each clonal population, the absence of a cell surface marker that was present in the individual T cells (or precursors thereof); and detecting, in one or more T cells of each clonal population, the presence of a first nucleic acid sequence that is indicative of the presence of an on-target genome edit in the clonal population of T cells. Also described are compositions comprising one or more clonal populations of T cells isolated according to the methods disclosed herein.

Abstract: Disclosed are methods, systems, and articles of manufacture for performing a process on biological samples. An analysis of biological samples in multiple regions of interest in a microfluidic device and a timeline correlated with the analysis may be identified. One or more region-of-interest types for the multiple regions of interest may be determined; and multiple characteristics may be determined for the biological samples based at least in part upon the one or more region-of-interest types. Associated data that respectively correspond to the multiple regions of interest in a user interface for at least a portion of the biological samples in the user interface based at least in part upon the multiple identifiers and the timeline. A count of the biological samples in a region of interest may be determined based at least in part upon a class or type of data using a convolutional neural network (CNN).

Abstract: Disclosed are methods, systems, and articles of manufacture for performing a process on biological samples. An analysis of biological samples in multiple regions of interest in a microfluidic device and a timeline correlated with the analysis may be identified. One or more region-of-interest types for the multiple regions of interest may be determined; and multiple characteristics may be determined for the biological samples based at least in part upon the one or more region-of-interest types. Associated data that respectively correspond to the multiple regions of interest in a user interface for at least a portion of the biological samples in the user interface based at least in part upon the multiple identifiers and the timeline. A count of the biological samples in a region of interest may be determined based at least in part upon a class or type of data using a convolutional neural network (CNN).

Abstract: Disclosed are methods, systems, and articles of manufacture for performing a process on biological samples. An analysis of biological samples in multiple regions of interest in a microfluidic device and a timeline correlated with the analysis may be identified. One or more region-of-interest types for the multiple regions of interest may be determined; and multiple characteristics may be determined for the biological samples based at least in part upon the one or more region-of-interest types. Associated data that respectively correspond to the multiple regions of interest in a user interface for at least a portion of the biological samples in the user interface based at least in part upon the multiple identifiers and the timeline. A count of the biological samples in a region of interest may be determined based at least in part upon a class or type of data using a convolutional neural network (CNN).

Abstract: Disclosed herein are methods for performing assays, including general functional assays, on a biological cell. The methods can include contacting a biological cell with a test agent for a period of time; lysing the biological cell while the biological cell is disposed within a sequestration pen located within an enclosure of a microfluidic device; and allowing RNA molecules released from the lysed biological cell to be captured by capture oligonucleotides linked to a capture object disposed within the sequestration pen of the microfluidic device. Each capture oligonucleotide can include a priming sequence that binds a primer, and a capture sequence. Each cDNA transcribed from a captured RNA can have an oligonucleotide sequence complementary to the captured RNA molecule, with the complementary oligonucleotide sequence being covalently linked to one of the capture oligonucleotides of the capture object.

Abstract: Methods are described herein for isolating clonal populations of T cells having a defined genetic modification. The methods are performed, at least in part, in a microfluidic device comprising one or more sequestration pens. The methods include the steps of: maintaining individual T cells (or precursors thereof) that have undergone a genomic editing process in corresponding sequestration pens of a microfluidic device; expanding the T cells into respective clonal populations of T cells; detecting, in one or more T cells of each clonal population, the absence of a cell surface marker that was present in the individual T cells (or precursors thereof); and detecting, in one or more T cells of each clonal population, the presence of a first nucleic acid sequence that is indicative of the presence of an on-target genome edit in the clonal population of T cells. Also described are compositions comprising one or more clonal populations of T cells isolated according to the methods disclosed herein.

Abstract: Apparatuses, compositions and processes for DNA barcode deconvolution are described herein. A DNA barcode may be used to provide a bead specific identifier, which may be detected in situ using hybridization strategies. The DNA barcode provides identification by sequencing analysis. The dual mode of detection may be used in a wide variety of applications to link positional information with assay information including but not limited to genetic analysis. Methods are described for generation of barcoded single cell sequencing libraries. Isolation of nucleic acids from a single cell within a microfluidic environment can provide the foundation for cell specific sequencing library preparation.