MICROSATELLITE INSTABILITY DETECTION IN CELL-FREE DNA

    公开(公告)号:US20240247319A1

    公开(公告)日:2024-07-25

    申请号:US18500890

    申请日:2023-11-02

    CPC classification number: C12Q1/6886 G16B20/20 G16B30/10 G16B40/20

    Abstract: Provided herein are methods for determining the microsatellite instability status of samples. In one aspect, the methods include quantifying a number of different repeat lengths present at each of a plurality of microsatellite loci from sequence information to generate a site score for each of the plurality of the microsatellite loci. The methods also include comparing the site score of a given microsatellite locus to a site specific trained threshold for the given microsatellite locus for each of the plurality of the microsatellite loci and calling the given microsatellite locus as being unstable when the site score of the given microsatellite locus exceeds the site specific trained threshold for the given microsatellite locus to generate a microsatellite instability score, which includes a number of unstable microsatellite loci from the plurality of the microsatellite loci.

    CORRECTING FOR DEAMINATION-INDUCED SEQUENCE ERRORS

    公开(公告)号:US20240141425A1

    公开(公告)日:2024-05-02

    申请号:US18336281

    申请日:2023-06-16

    CPC classification number: C12Q1/6874 C12Q1/6806

    Abstract: Sequencing nucleic acids can identify variations associated with presence, susceptibility or prognosis of disease. However, the value of such information can be compromised by errors introduced by or before the sequencing process including preparing nucleic acids for sequencing. Blunting single-stranded overhangs on nucleic acids in a sample can introduce deamination-induced sequencing errors. The disclosure provides methods of identifying and correcting for such deamination-induced sequencing errors and distinguishing them from real sequence variations.

    MICROSATELLITE INSTABILITY DETECTION IN CELL-FREE DNA

    公开(公告)号:US20230416843A1

    公开(公告)日:2023-12-28

    申请号:US18456362

    申请日:2023-08-25

    CPC classification number: C12Q1/6886 G16B30/10 G16B20/20 G16B40/20

    Abstract: Provided herein are methods for determining the microsatellite instability status of samples. In one aspect, the methods include quantifying a number of different repeat lengths present at each of a plurality of microsatellite loci from sequence information to generate a site score for each of the plurality of the microsatellite loci. The methods also include comparing the site score of a given microsatellite locus to a site specific trained threshold for the given microsatellite locus for each of the plurality of the microsatellite loci and calling the given microsatellite locus as being unstable when the site score of the given microsatellite locus exceeds the site specific trained threshold for the given microsatellite locus to generate a microsatellite instability score, which includes a number of unstable microsatellite loci from the plurality of the microsatellite loci.

    COMPUTATIONAL MODELING OF LOSS OF FUNCTION BASED ON ALLELIC FREQUENCY

    公开(公告)号:US20230360727A1

    公开(公告)日:2023-11-09

    申请号:US18347986

    申请日:2023-07-06

    CPC classification number: G16B20/20

    Abstract: The disclosure relates to computer technology for precision diagnosis of various states of genetic material such as a gene sequenced from cell-free DNA in a sample. The state may include a somatic homozygous deletion, a somatic heterozygous deletion, a copy number variation, or other states. A computer system may generate competing probabilistic models that each output a probability that the genetic material is in a certain state. Each model may be trained on a training sample set to output a probability that the genetic material is in a respective state. In some embodiments, the computer system may use various probabilistic distributions to generate the models. For example, the computer system may use a beta-binomial distribution, a binomial distribution, a normal (also referred to as “Gaussian”) distribution, or other type of probabilistic modeling techniques.

    NORMALIZING TUMOR MUTATION BURDEN
    26.
    发明申请

    公开(公告)号:US20220154289A1

    公开(公告)日:2022-05-19

    申请号:US17529694

    申请日:2021-11-18

    Inventor: Darya CHUDOVA

    Abstract: Values for tumor mutation burden from different samples can be made more comparable to each other or control standards by a normalization regime that takes into account the minor allele fraction of highly rated mutations in a sample. Such analysis can provide an indication where the tumor mutation burden of a test sample lies on a distribution of tumor mutation burdens in a control population, and thus, whether the individual providing the test sample is likely to be amenable to immunotherapy to treat cancer.

    CORRECTING FOR DEAMINATION-INDUCED SEQUENCE ERRORS

    公开(公告)号:US20200377941A1

    公开(公告)日:2020-12-03

    申请号:US16866252

    申请日:2020-05-04

    Abstract: Sequencing nucleic acids can identify variations associated with presence, susceptibility or prognosis of disease. However, the value of such information can be compromised by errors introduced by or before the sequencing process including preparing nucleic acids for sequencing. Blunting single-stranded overhangs on nucleic acids in a sample can introduce deamination-induced sequencing errors. The disclosure provides methods of identifying and correcting for such deamination-induced sequencing errors and distinguishing them from real sequence variations.

    METHODS FOR MULTI-RESOLUTION ANALYSIS OF CELL-FREE NUCLEIC ACIDS

    公开(公告)号:US20200185060A1

    公开(公告)日:2020-06-11

    申请号:US16719768

    申请日:2019-12-18

    Abstract: The present disclosure provides a method for enriching for multiple genomic regions using a first bait set that selectively hybridizes to a first set of genomic regions of a nucleic acid sample and a second bait set that selectively hybridizes to a second set of genomic regions of the nucleic acid sample. These bait set panels can selectively enrich for one or more nucleosome-associated regions of a genome, said nucleosome-associated regions comprising genomic regions having one or more genomic base positions with differential nucleosomal occupancy, wherein the differential nucleosomal occupancy is characteristic of a cell or tissue type of origin or disease state.

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