Abstract:
Disclosed herein include methods and compositions for selectively amplifying and/or extending nucleic acid target molecules in a sample. The methods and compositions can, for example, reduce the amplification and/or extension of undesirable nucleic acid species in the sample, and/or allow selective removal of undesirable nucleic acid species in the 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:
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:
Disclosed herein include methods and compositions for selectively amplifying and/or extending nucleic acid target molecules in a sample. The methods and compositions can, for example, reduce the amplification and/or extension of undesirable nucleic acid species in the sample, and/or allow selective removal of undesirable nucleic acid species in the sample.
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:
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:
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:
Methods, kits and systems are disclosed for analyzing one or more molecules in a sample. Analyzing the one or more molecules may comprise quantitation of the one or more molecules. Individual molecules may quantitated by PCR, arrays, beads, emulsions, droplets, or sequencing. Quantitation of individual molecules may further comprise stochastic labeling of the one or more molecules with a plurality of oligonucleotide tags to produce one or more stochastically labeled molecules. The methods may further comprise amplifying, sequencing, detecting, and/or quantifying the stochastically labeled molecules. The molecules may be DNA, RNA and/or proteins.
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).