Abstract:
The disclosure provides for methods, compositions, and kits for multiplex nucleic acid analysis of single cells. The methods, compositions and systems may be used for massively parallel single cell sequencing. The methods, compositions and systems may be used to analyze thousands of cells concurrently. The thousands of cells may comprise a mixed population of cells (e.g., cells of different types or subtypes, different sizes).
Abstract:
Compositions, methods and kits are disclosed for high-sensitivity single molecule digital counting by the stochastic labeling of a collection of identical molecules by attachment of a diverse set of labels. Each copy of a molecule randomly chooses from a non-depleting reservoir of diverse labels. Detection may be by a variety of methods including hybridization based or sequencing. Molecules that would otherwise be identical in information content can be labeled to create a separately detectable product that is unique or approximately unique in a collection. This stochastic transformation relaxes the problem of counting molecules from one of locating and identifying identical molecules to a series of binary digital questions detecting whether preprogrammed labels are present. The methods may be used, for example, to estimate the number of separate molecules of a given type or types within a sample.
Abstract:
The disclosure provides for methods, compositions, and kits for multiplex nucleic acid analysis of single cells. The methods, compositions and systems may be used for massively parallel single cell sequencing. The methods, compositions and systems may be used to analyze thousands of cells concurrently. The thousands of cells may comprise a mixed population of cells (e.g., cells of different types or subtypes, different sizes).
Abstract:
Disclosed herein include methods and systems for identifying multiplet expression profiles. A plurality of synthetic multiplet expression profiles can be generated from a plurality of expression profiles. An expression profile can be identified as an expression for a singlet or a multiplet using a machine learning model trained using the plurality of synthetic multiplet (e.g., doublet) expression profiles.
Abstract:
Some embodiments disclosed herein provide a plurality of compositions each comprising a protein binding reagent conjugated with an oligonucleotide. The oligonucleotide comprises a unique identifier for the protein binding reagent it is conjugated with, and the protein binding reagent is capable of specifically binding to a protein target. Further disclosed are methods and kits for quantitative analysis of a plurality of protein targets in a sample and for simultaneous quantitative analysis of protein and nucleic acid targets in a sample. Also disclosed herein are systems and methods for preparing a labeled biomolecule reagent, including a labeled biomolecule agent comprising a protein binding reagent conjugated with an oligonucleotide.
Abstract:
Disclosed herein are methods and systems for correcting errors in sample amplification, including the errors occurred in determining the number of targets in samples. In some embodiments, the method comprises: stochastically barcoding a plurality of targets in the samples using oligonucleotides comprising stochastic barcodes to generate stochastically barcoded targets; contacting one or more defined barcoded primers with each of the one or more samples; and determining an amplification noise.
Abstract:
Compositions, methods and kits are disclosed for high-sensitivity single molecule digital counting by the stochastic labeling of a collection of identical molecules by attachment of a diverse set of labels. Each copy of a molecule randomly chooses from a non-depleting reservoir of diverse labels. Detection may be by a variety of methods including hybridization based or sequencing. Molecules that would otherwise be identical in information content can be labeled to create a separately detectable product that is unique or approximately unique in a collection. This stochastic transformation relaxes the problem of counting molecules from one of locating and identifying identical molecules to a series of binary digital questions detecting whether preprogrammed labels are present. The methods may be used, for example, to estimate the number of separate molecules of a given type or types within a sample.
Abstract:
The disclosure provides for methods, compositions, and kits for multiplex nucleic acid analysis of single cells. The methods, compositions and systems may be used for massively parallel single cell sequencing. The methods, compositions and systems may be used to analyze thousands of cells concurrently. The thousands of cells may comprise a mixed population of cells (e.g., cells of different types or subtypes, different sizes).
Abstract:
Methods, systems and platforms for digital imaging of multiple regions of an array, and detection and counting of the labeled features thereon, are described.