Patent classifications
G16B30/00
SYSTEM AND METHOD FOR IDENTIFYING ANALYTES IN ASSAY USING NORMALIZED TM VALUES
Techniques are provided for generating an array-specific range of Tm values to be used for calling a sample in a given array positive or negative for a target nucleic acid sequence. A sample well in an array is provided with a control sample containing a control nucleic acid sequence. The control sample is amplified by thermal cycling the sample well. A Tm value for the control sample is identified and compared to an expected Tm value for the control nucleic acid sequence to calculate a relationship between the identified control Tm value and the expected control Tm value. By applying this relationship to an expected Tm value for a target nucleic acid sequence, an array-specific range of Tm values for the target nucleic acid sequence is generated and can be used for calling an experimental sample in the same array positive or negative for the target nucleic acid sequence.
B(EAD-BASED) A(TACSEQ) P(ROCESSING)
Methods and compositions for determining the proximity of two barcoding oligonucleotides (e.g., in a single partition or adjacent on a tissue section) using a determination of the presence of a 9 bp sequence resulting from tagmentation in different nucleic acid fragments linked to different barcoding oligonucleotides is provided.
Transposition of native chromatin for personal epigenomics
Provided herein is a method for analyzing polynucleotides such as genomic DNA. In certain embodiments, the method comprises: (a) treating chromatin isolated from a population of cells with an insertional enzyme complex to produce tagged fragments of genomic DNA; (b) sequencing a portion of the tagged fragments to produce a plurality of sequence reads; and (c) making an epigenetic map of a region of the genome of the cells by mapping information obtained from the sequence reads to the region. A kit for performing the method is also provided.
Transposition of native chromatin for personal epigenomics
Provided herein is a method for analyzing polynucleotides such as genomic DNA. In certain embodiments, the method comprises: (a) treating chromatin isolated from a population of cells with an insertional enzyme complex to produce tagged fragments of genomic DNA; (b) sequencing a portion of the tagged fragments to produce a plurality of sequence reads; and (c) making an epigenetic map of a region of the genome of the cells by mapping information obtained from the sequence reads to the region. A kit for performing the method is also provided.
Non-invasive prenatal diagnosis of fetal genetic condition using cellular DNA and cell free DNA
Disclosed are methods for determining at least one sequence of interest of a fetus of a pregnant mother. In various embodiments, the method can determine one or more sequences of interest in a test sample that comprises a mixture of fetal cellular DNA and mother-and-fetus cfDNA. In some embodiments, methods are provided for determining whether the fetus has a genetic disease. In some embodiments, methods are provided for determining whether the fetus is homozygous in a disease causing allele when the mother is heterozygous of the same allele. In some embodiments, methods are provided for determining whether the fetus has a copy number variation (CNV) or a non-CNV genetic sequence anomaly.
Non-invasive prenatal diagnosis of fetal genetic condition using cellular DNA and cell free DNA
Disclosed are methods for determining at least one sequence of interest of a fetus of a pregnant mother. In various embodiments, the method can determine one or more sequences of interest in a test sample that comprises a mixture of fetal cellular DNA and mother-and-fetus cfDNA. In some embodiments, methods are provided for determining whether the fetus has a genetic disease. In some embodiments, methods are provided for determining whether the fetus is homozygous in a disease causing allele when the mother is heterozygous of the same allele. In some embodiments, methods are provided for determining whether the fetus has a copy number variation (CNV) or a non-CNV genetic sequence anomaly.
Systems and methods for paired end sequencing
Systems and methods for analyzing overlapping sequence information can obtain first and second overlapping sequence information for a polynucleotide, align the first and second sequence information, determine a degree of agreement between the first and second sequence information for a location along the polynucleotide, and determine a base call and a quality value for the location.
Systems and methods for paired end sequencing
Systems and methods for analyzing overlapping sequence information can obtain first and second overlapping sequence information for a polynucleotide, align the first and second sequence information, determine a degree of agreement between the first and second sequence information for a location along the polynucleotide, and determine a base call and a quality value for the location.
Methods and systems for copy number variant detection
Methods and systems for determining copy number variants are disclosed. An example method can comprise applying a sample grouping technique to select reference coverage data, normalizing sample coverage data comprising a plurality of genomic regions, and fitting a mixture model to the normalized sample coverage data based on the selected reference coverage data. An example method can comprise identifying one or more copy number variants (CNVs) according to a Hidden Markov Model (HMM) based on the normalized sample coverage data and the fitted mixture model. An example method can comprise outputting the one or more copy number variants.
Methods and systems for copy number variant detection
Methods and systems for determining copy number variants are disclosed. An example method can comprise applying a sample grouping technique to select reference coverage data, normalizing sample coverage data comprising a plurality of genomic regions, and fitting a mixture model to the normalized sample coverage data based on the selected reference coverage data. An example method can comprise identifying one or more copy number variants (CNVs) according to a Hidden Markov Model (HMM) based on the normalized sample coverage data and the fitted mixture model. An example method can comprise outputting the one or more copy number variants.