96 results about "Genetic variants" patented technology

A system and method for processing genomic data using dynamic latent manifolds that transforms multi-modal genomic datasets into geometric representations within a curved manifold space. The system receives genomic datasets including DNA sequences, genetic variants, and expression data, then extracts biological features and assesses importance using trained neural networks. Manifold curvature values are computed based on biological significance, and genomic data is embedded as geometric structures where semantic relationships are represented through distance and curvature properties. The system generates compression pressure fields that influence processing decisions and computes optimal geodesic paths through the manifold to minimize cognitive action functionals. Adaptive compression rates are determined for different genomic regions based on geometric properties and biological importance. The manifold structure evolves through use, strengthening frequently accessed pathways while applying thermodynamic decay to unused concepts. The system supports hierarchical organization across biological scales, reversible navigation, and federated learning capabilities that enable privacy-preserving collaboration.

The present disclosure provides systems and methods to detect somatic or germline variants by providing a predetermined genomic DNA (gDNA) to an assay mixture, and capturing a sample of a subject's genetic information using a DNA sequencer and detecting genetic variants from the genetic information. A mutation may then be classified as being from a germline source if gDNA derived molecules have lengths inconsistent with those expected from cell-free DNA (cfDNA) derived molecules.

Methods for detecting a short genetic variant in a test sample are described herein. In some exemplary methods, the short genetic variant is called using one or match scores, which are determined using one or more sequencing data sets obtained from a test nucleic acid molecule, wherein the test sequencing data sets are determined by sequencing the test nucleic acid molecule using non-terminating nucleotides provided in separate nucleotide flows according to a flow-cycle order. Also described herein are methods of sequencing a test nucleic acid molecule using two or more different flow-cycle orders and / or extended flow cycle orders having five or more nucleotide flows per flow cycle.

Examples may use pathogenicity evidence data associated with genetic variants and health conditions to create input data for a causal machine learning model. Examples may apply a causal machine learning model to input data to produce a trained causal model. A graphical representation of the trained causal model may include nodes connected via acyclic directed edges. A first node of the nodes may represent a pathogenic evidence variable associated with the health condition. The at least one second node may represent a cause of the pathogenic evidence variable. The at least one third node may represent the impact of the pathogenic evidence variable. The non-cyclic directed edge may represent a relationship between two nodes. Examples may output prediction data sampled from the trained causal model.

Described herein are methods for making genetically modified cells by introducing combinations of genetic variants (designed or random) or constructs (genes or otherwise arbitrary DNA) into a population of cells, and for tracking each variant combination by sequentially building an array of barcodes at a common locus (chromosomal or plasmid), termed the barcode locus. Also described are the cells made by such methods.

The invention relates to a computer-implemented method for determining pharmacogenetic star alleles from high-throughput sequencing data, the method comprising the following steps: providing a plurality of result files which have been output by a plurality of different computer programs for genotyping and which each have a plurality of result elements, wherein each result element has at least one gene designation; shortening the allele designation as far as possible on the right for each result element of the plurality of result elements from each result file of the plurality of result files; and outputting the gene designation and a specific result diplotype. The invention also relates to a computer-implemented method for determining rare genetic variants. Finally, the invention also relates to a device having a processor and a memory in order to carry out such methods.

Systems and methods herein provide for rapid patient information to healthcare providers such that the healthcare providers can make more informed diagnoses. One method includes storing gene sequencing data and called genetic variants of a patient in a data structure. The method also includes receiving a request from a healthcare provider for results of a test that reports at least a portion of the called genetic variants in relation to a diagnosis of the patient by the healthcare provider, and delivering the results of the test to the healthcare provider if a quality control value of said at least a portion of the called genetic variants meets or exceeds a predetermined threshold of quality for assisting the healthcare provider.

Methods and apparatus for selecting genetic variants for a tumour-informed assay are provided. The method includes receiving a sample collected from a patient, the sample being associated with a cancer type, generating a mutational catalogue for the sample, the mutational catalogue indicating a proportion of genetic mutation types observed in the sample, selecting a set of signatures associated with the cancer type, the set including one or more signatures, each signature comprising a mutational profile, determining, based on the set of signatures associated with the cancer type and the mutational catalogue, a set of genetic variants most likely to be genuine somatic variants associated with the sample, and outputting the set of genetic variants for use in creating a tumour-informed assay for the patient.

Disclosed are methods, systems and computer-program products for the determination of complex genetic variants. The disclosed methods, systems and computer-program products may include obtaining a mutant scaffold nucleotide sequence that comprises a sequence that includes mutations characteristic of the complex genetic variant; obtaining a wild-type scaffold nucleotide sequence having a wild-type sequence; generating an alignment of at least one sequence from the sample to the mutant scaffold and to the wild-type scaffold; and determining that the sample contains a mutation characteristic of the complex genetic variant based on alignment to the mutant scaffold and not the wild-type scaffold.

The present disclosure relates to analyzing genetic data. In one arrangement, a method operates on input data comprising the strength of association between one or more phenotypes, including a target phenotype, and a plurality of genetic variants. A fine-mapping algorithm is applied to all or a subset of the input data to identify one or more independent phenotype-variant associations. For each association, a set of one or more fine-mapped variants is identified. A fine-mapping prediction model is calculated based on the input data and the set of fine-mapped variants. The effect of the set of fine-mapped variants on the target phenotype is subtracted from the input data to obtain residual association data. A machine learning algorithm is applied to the residual association data to identify further predictive correlations between the target phenotype and the plurality of genetic variants.

The types of genetic variants detected by NGS are very wide and not all genetic variants always lead to diseases, and thus it is difficult to quickly and accurately interpret the meaning of disease relevance for detected genetic variants. The present invention relates to a method of interpreting genetic variants based on nucleic acid sequencing. The method of interpreting genetic variants according to the present invention provides a logic tree for interpreting NGS variant data, which can classify the pathogenicity of genetic variants based on the ACMG guidelines and determine the level of pathogenicity of the genetic variants, and thus it is expected to be widely used in the life sciences and medical health fields.

An apparatus for generating personalized risk assessments for neurodegenerative diseases includes a computing device that receives user data containing genetic and medical information. It processes the data to create genotype identification and gene detection modules, identifying user genotypes and relevant genetic markers. The user's mitochondrial haplogroup is examined to refine the assessment. A risk calculation module employs machine learning to weigh genetic variants against population-based data, calculating a polygenic risk score (PRS). The PRS forms a personalized risk profile, displayed through a visual interface. The disclosed systems offer a comprehensive approach to accurate risk assessment, enabling targeted interventions and informed decision-making in neurodegenerative disease management.

Methods and devices are provided for selecting genetic variants for tumor awareness assays. A method includes receiving a sample collected from a patient, the sample associated with a cancer type; generating a directory of mutations for the sample, the directory of mutations indicating a proportion of genetic mutation types observed in the sample; selecting a set of features associated with the cancer type, the set comprising one or more features, each feature comprising a profile of mutations; determining a set of genetic variants most likely to be a true cell variant associated with the sample based on the set of features and the directory of mutations associated with the type of cancer; and outputting the set of genetic variants for creating a tumor awareness assay for the patient.

Systems and methods for estimating tumor fraction in a biological sample are disclosed. One method may include: receiving sequencing data for each of a plurality of biological samples included on a combined targeted sequencing panel, wherein the sequencing data for each of the plurality of biological samples includes: genetic variant sequencing data covering one or more genetic variants of each of the plurality of biological samples; and background sequencing data covering all other genetic variants from all of the other biological samples; calculating, from the background sequencing data associated with each of the plurality of biological samples, a site-specific error rate for each genomic location associated with each of the one or more genetic variants; and establishing, based on the calculated site-specific error rate, a threshold for tumor fraction estimation for each of the one or more genetic variants. Other aspects are described and claimed.

The present invention refers to an in vitro method for predicting whether cattle are susceptible or resistant to paratuberculosis (PTB), or for classifying and / or selecting cattle according to whether they are susceptible or resistant to PTB; and / or for preventing susceptibility to PTB or to increase resistance to PTB.

The disclosure relates to analysing genetic data. In one arrangement, a method operates on input data comprising strengths of association between one or more phenotypes including a target phenotype and a plurality of genetic variants. A fine-mapping algorithm is applied to all or a subset of the input data to identify one or more independent phenotype-variant associations. A set of one or more fine-mapped variants is identified for each association. A fine-mapping predictive model is calculated on the basis of the input data and the set of fine-mapped variants. The effect on the target phenotype of the set of fine-mapped variants is subtracted from the input data to obtain residual association data. A machine learning algorithm is applied to the residual association data to identify further predictive correlations between the target phenotype and the plurality of genetic variants.

Provided herein are computer-implemented methods for assigning maternal or fetal origin to one or more genetic variants in cell free DNA (cfDNA) from a sample from a pregnant mammal, preferably a pregnant human, using a probabilistic model for assigning maternal or fetal origin to genetic variants in DNA from a sample obtained from a pregnant mammal, wherein the model assigns maternal or fetal origin based on a combination of fetal fraction and DNA fragment size.

The present disclosure provides, in part, a method of identifying genetic variants in an embryo. The method comprises: (a) obtaining two or more analyte sources from the embryo; (b) analyzing the two or more analyte sources to obtain genetic information for each source; (c) comparing the genetic information for each source to one or more reference genomes using at least one variant call program, wherein the variant call program identifies variants between each source and the reference genomes; and (d) combining the variants to identify the difference presented only by the source, wherein the difference is a genetic variant in the embryo.

The invention relates to a method for detecting changes of nucleotide sequences by using an isothermal nucleic acid amplification technology, a primer set for detecting selected genetic variants and components of a reaction mixture.

The present invention relates to a vascular endothelial growth factor (VEGF) inhibitor for use in the treatment of wet macular degeneration, wherein the VEGF inhibitor is adapted to be administered intravitreally to a patient, wherein the patient has previously been treated intravitreally with the VEGF inhibitor for approximately one year, and has one or more genetic variants that are single nucleotide polymorphisms selected from rs2106124, rs1879796, rs12148845, rs12148100, rs17482885, and rs17629019.

Bag3 is a multifunctional protein expressed predominantly in the heart, the skeletal muscle, the central nervous system and in many cancers. Although BAG3 was cloned only a decade ago, studies have shown that genetic variants, particularly those that result in haplo-insufficiency, can lead to severe left ventricular dysfunction; however, the full mechanisms responsible have remained obscure. To obviate the influence of heart failure itself on the biology of Bag3, transgenic mice harboring a single allele knock-out were studied between 8 and 10 weeks of age before any obvious signs of heart failure were evident. The results were surprising and informative. First, it was found that despite a normal phenotype, young Bag3+ / − had marked changes in the proteome that were characterized by changes in proteins associated with metabolism and apoptosis. Consistent with this finding, a decrease in the levels of critical proteins charged with maintaining the mitochondrial membrane potential was observed. It was also found that young mice shifted from a balance between the extrinsic and intrinsic pathways of apoptosis. However, in the presence of stress and the absence of Bag3 there was a shift from a balanced to an extrinsic dominant system (cleaved caspase 8). The diverse array of critical pathways regulated by Bag3 suggests a more important role especially during stress and that this role might include serving as an intracellular glue that holds proteins where they can be most effective rather than having them meet accidentally.

Methods for detecting a short genetic variant in a test sample are described herein. In some exemplary methods, the short genetic variant is called using one or match scores, which are determined using one or more sequencing data sets obtained from a test nucleic acid molecule, wherein the test sequencing data sets are determined by sequencing the test nucleic acid molecule using non-terminating nucleotides provided in separate nucleotide flows according to a flow-cycle order. Also described herein are methods of sequencing a test nucleic acid molecule using two or more different flow-cycle orders and / or extended flow cycle orders having five or more nucleotide flows per flow cycle.

This invention discloses a method and system for selecting functional gene variant sites, relating to the field of gene site selection. The method includes: acquiring chromatin accessibility distribution information across the entire genome; performing convolutional block transformation based on the accessibility distribution information to obtain accessibility feature values; determining genomic information across the entire genome based on regulatory maps; determining an initial weight value set based on the accessibility feature values ​​and genomic information; the initial weight value set is a set of initial weight values ​​corresponding to each of the accessibility feature values ​​and genomic information; inputting the accessibility feature values, genomic information, and the initial weight value set into a site selection model, and outputting selected functional gene variant site information and regulated susceptibility gene information; the selected functional gene variant site information includes: site variant bases that meet set threshold conditions and their corresponding site coordinates; this invention can improve the selection efficiency of functional gene variant sites.

A method of genotyping one or more genetic rare variants in a plurality of nucleic acid samples is described. The method comprises running one or more assays of the plurality of nucleic acid samples using at least one microarray comprising a plurality of probesets and generating assay data. Heterozygous genotypes in the plurality of nucleic acid samples are called and evaluated to identify any rare heterozygous genotype calls that are from a probeset having at least one probe, wherein the number of heterozygous genotype calls for the probeset does not exceed a maximum threshold value. Each identified rare heterozygous genotype call is evaluated to determine whether the identified rare heterozygous genotype call comprises a true rare heterozygous genotype call using a support vector machine prediction model or supervised machine learning classification model comprising a plurality of predictor values for identifying a true rare heterozygous genotype call.

The present invention provides to an improved high-throughput system and method for generated and screening of genetic variants by combinatorial modifications. Also provided are optimized SpCas9 enzyme variants produced by this system.

The present invention discloses a genomic biomarker combination for diagnosing keratoconus. Based on the whole-genome sequencing data of keratoconus, the present invention conducts association analysis, screens significant variant sites related to keratoconus, and performs polygenic risk score modeling and susceptibility risk prediction. The results show that the genetic variant risk sites screened by the present invention can effectively distinguish between normal populations and keratoconus populations.

Prenatal genetic testing allows early detection of genetic disease in a fetus. Described herein are methods of detecting the presence or absence of a genetic variant in a region of interest in the genome of a fetus in a pregnant woman. The methods are noninvasive, and can use cell-free DNA (cfDNA) present in the plasma of the pregnant woman. A DNA library is constructed from the cfDNA, and DNA molecules comprising the region of interest or portions thereof are enriched and analyzed, for example by sequencing. The methods described herein can also rely on constructing a maternal haplotype to provide even higher resolution fetal genetic variant determination.

The present application relates to a gene mutation and phenotype information association analysis method and system, belonging to the technical field of automatic medical analysis. The method comprises the following steps: S1: obtaining a high-frequency pathogenic gene mutation white list; S2: obtaining genotype data of the object to be analyzed, comparing with the gene mutation in the white list, taking the intersection, and obtaining the high-frequency pathogenic gene mutation; S3: obtaining the high-frequency pathogenic gene mutation and the phenotype information of the object to be analyzed, performing high-frequency pathogenic gene mutation association analysis, and obtaining the associated high-frequency pathogenic gene mutation set; S4: obtaining the genotype data and the phenotype information of the object to be analyzed, performing conventional association analysis, and obtaining the associated gene mutation set; S5: obtaining the associated high-frequency pathogenic gene mutation set and the associated gene mutation set, taking the union, and outputting the gene mutation list in the union, which is the candidate pathogenic gene mutation list. The method can solve the problem of false negatives in conventional analysis methods (software).

Described herein is an improved method of treating a patient in need of such treatment with iloperidone or an active metabolite thereof wherein the patient has a gout history or carries a genetic variant associated with an increase in serum uric acid concentration induced by iloperidone. The improved method comprises monitoring a serum uric acid level of a patient; when the serum uric acid level of the patient exceeds a reference level, a uric acid lowering treatment is initiated or a dose thereof is increased.

The invention discloses a method for inducing litchi girdling callus and peripheral bud differentiation in a field, and relates to the technical field of plant propagation, the method comprises the following steps: cutting off the top of a trunk branch of a litchi growing vertically, and carrying out spiral girdling below the section of the top until the girdling depth reaches a wood layer; soaking absorbent cotton in a bud differentiation inducer to obtain an induction matrix; after the top section and the girdling opening of the litchi branch are covered with the induction matrix, bud differentiation treatment is conducted on the litchi branch; after bud differentiation treatment is completed, the litchi branches are subjected to moisture preservation and light shielding treatment, and adventitious buds are obtained. According to the method, wound induction is directly carried out on the litchi plants in the field, the browning problem in the in-vitro culture process is avoided by utilizing a plant self-repairing mechanism and combining with local medicament treatment, adventitious bud differentiation around girdling openings is promoted, a stable material source is provided for field screening of the polyploidy plants, the equipment and labor cost is reduced, and the method is suitable for large-scale popularization and application. Meanwhile, the survival rate of genetic variants is improved.