12 results about "Germline mutation" patented technology

This invention provides a germline mutation detection method and system with a low false positive rate. The system is computer-executed and includes: first, performing a PCR repeat cluster consistency test on sequence alignment files generated from high-throughput sequencing reads, down-regulating the base count weights of inconsistent sites within the cluster; then, based on the sample-specific background error baseline, calculating the variation confidence index of each genomic site using an empirical Bayesian framework to obtain candidate single nucleotide variants (SNPs); obtaining candidate insertion / deletion variants through read clustering and physical verification of insertion fragment lengths; subsequently, performing a dual-engine cross-feedback iteration on the two candidate types until convergence, integrating and filtering, and outputting a structured mutation detection report. This invention significantly reduces the false positive rate of both SNPs and insertion / deletion variants while maintaining sensitivity, and improves the detection capability of complex insertion / deletion variants.

Systems and methods for characterizing a mutation include obtaining reference sequence reads mapping to a genomic location of the mutation from a first sequencing reaction using a reference sample of a subject, and obtaining tumor sequence reads mapping to the genomic location of the mutation from a second sequencing reaction using a solid tumor sample of the subject. A reference base fraction of the mutation is determined using the reference sequence reads. A germline expectation of the mutation is determined using a tumor purity of the solid tumor sample, the major and the minor copy number at the genomic location of the mutation derived from tumor sequence reads. The reference base fraction and the germline expectation of the mutation are inputted into a model thereby obtaining, as output from the model, a determination of whether the mutation is a clonal hematopoiesis of indeterminate potential mutation or a germline mutation.

The present disclosure provides a probabilistic model for accurate and sensitive somatic single nucleotide variant (SNV) detection in cell-free nucleic acid samples comprising a set of sequence data. A joint genotype may be determined for each locus in the set of sequence data, and germline mutations may be intrinsically removed. A set of filtrations can be applied to eliminate low quality somatic variant calls. Further, a global tumor cell-free deoxyribonucleic acid (cfDNA) fraction and overlapping read mates can be considered, thereby enabling accurate SNV detection and variant allele frequency estimation from samples with low tumor cfDNA fraction. A sensitive early detection of minimal residual disease (MRD) is designed by using the probabilistic model and the machine learning model for distinguishing true variants from sequencing errors.

The application provides a prediction method of pathogenic embryonic mutation, comprising the following steps: obtaining a variation site set of an embryonic mutation to be predicted, and performing population frequency screening on the variation site; filtering variation sites which are not annotated or are only annotated as clinically uncertain by using a clinical variation database; calculating a pathogenic posterior probability score of a candidate pathogenic variation by using a variation Bayesian inference (VBI) model with multiple types of function annotations; and cross- verifying the posterior probability score, external pathogenic prediction tool scores and variation types to determine a final pathogenicity discrimination result. Compared with an existing method based on single site frequency or single function score, the present application provides a posterior probability evaluation model with more biological interpretation in the field of rare variation judgment, effectively improves the prediction accuracy in a complex scene, significantly improves the risk classification accuracy based on multi-level evidence fusion discrimination, and effectively reduces the misdiagnosis and missed diagnosis rate in clinical stratification.

The invention provides a method for measuring the mutation rate of a sexual reproduction animal whole genome level nucleotide germline. The method comprises the following steps: (1) performing genome sequencing on a to-be-detected species to obtain sequences of all coding proteins of the to-be-detected species; (2) constructing a phylogenetic tree of a to-be-tested species; (3) obtaining the divergence time Tdivergence between the species to be detected and the sibling species; (4) optimizing the phylogenetic tree of the species to be tested; and (5) obtaining the annual germline mutation rate [mu] year of the species to be detected. The principle of the method is as follows: neutral regions or neutral sites are widely distributed in a genome, and mutations generated at the positions are generally not influenced by natural selection; the mutation rate of the germline can be calculated by analyzing the change of the variation frequency of the sites along with time. The method provided by the invention not only is widely applicable to sexual reproduction animal species with obtained genome or transcriptome data, but also is accurate and efficient, fills up the blank of the prior art, and has great significance in theoretical research and practical application of biomedical engineering.

Provided herein are methods and transgenic systems termed Ifegenia (Inherited Female Elimination by Genetically Encoded Nucleases to Interrupt Alleles) comprising transgenic animal strains encoding Cas9 and / or gRNA that targets a female essential gene which are capable of passing down these genes as well as mutant female essential genes in wild populations in order to suppress the population of the animals, as well as methods and systems for making such animals. In some instances, the methods and systems provided herein result in both somatic and heritable germline mutations of the female essential gene resulting in daughter killing, and female essential gene mutant males reproductively viable to pass along the female essential gene mutation and related transgenes into subsequent generations. The methods and systems are adaptable to population control of insects, in particular mosquitoes such as Anopheles gambiae.

The invention relates to the technical field of medical data processing, and discloses a method and a system for constructing a breast cancer susceptibility gene harmful embryonic line variation evaluation model, and the method comprises the following steps: carrying out regression analysis on clinical data, pathological data and family history data of a breast cancer patient group; an evaluation factor with statistical significance for evaluating the harmful embryonic line variation of the breast cancer susceptibility gene is obtained; establishing a relationship between data corresponding to evaluation factors with statistical significance for evaluating the harmful embryonic system variation of the breast cancer susceptibility gene in clinical data, pathological data and family history data of a breast cancer patient group and evaluation data of the harmful embryonic system variation of the breast cancer susceptibility gene of a target group through the model; the model can identify mutations of a plurality of breast cancer susceptibility genes at the same time, is beneficial to early discovery of high-risk breast cancer patients, reduction of excessive detection of the patients and optimization of cost benefits of gene screening, and has important clinical significance.

A method may include a method for aiding in preventing breast cancer in a subject having a heterozygous germline mutation in BRCA1 or BRCA2, comprising: a. identifying a subject having a heterozygous germline mutation in BRCA1 or BRCA2; b. administering to the subject a therapeutically effective amount of a P53 protein stabilizer, wherein the P53 protein stabilizer comprises an MDM2 inhibitor.

An analysis method of analyzing a nucleic acid sequence derived from a patient sample with a computer, may include: obtaining analysis data relating to a mutation determined based on nucleic acid sequence data derived from the patient sample; and generating a first report providing information relating to the determined mutation in a first form which is different from a second form of a second report, wherein the second report provides information relating to a germline mutation among the determined mutation in the second form.

The disclosure is related to using machine learning algorithms to detect minimum residual disease (MRD) in cancer patients. For example, a method includes detecting somatic variants from pre-treatment samples from a patient using a variant caller. The method also includes filtering any germline mutations and sequencing artifacts from the detected somatic mutations. The method also includes classifying sequencing reads covering remaining somatic variants from the filtering using a machine learning model to identify somatic variants used for minimum residual disease (MRD) detection. The machine learning model may be trained using a random forest classifier based on a plurality of features. The method also includes analyzing the identified somatic variants to determine whether the patient is positive or negative for MRD.

The invention provides a method for constructing simulated tumor standard sequencing data and application of the simulated tumor standard sequencing data. The method comprises the following steps: acquiring a first strain mutation site set from a first human genome standard; obtaining a second strain mutation site set from a second human genome standard; selecting a unique germline mutation site relative to the second germline mutation set in the first germline mutation set; obtaining sequencing data of the second human genome standard substance and the first human genome standard substance; and for a preset simulated somatic mutation site, replacing corresponding data in the sequencing data of the second human genome standard with the sequencing data of the first human genome standard according to a predetermined replacement ratio, and generating the sequencing data of the tumor standard containing simulated somatic mutation. Compared with a real tumor cell standard substance, the method has the advantages that the mutation number and frequency can be accurately controlled, positive and negative sites are defined, the cost is saved, and the research efficiency is improved; and meanwhile, a real sequencing result is reserved.

The application provides a method for measuring the whole genome level nucleotide germline mutation rate of an animal of sexual reproduction. The method comprises the following steps: (1) performing genome sequencing on a to-be-tested species to obtain the sequences of all protein-coding genes of the to-be-tested species; (2) constructing a phylogenetic tree of the to-be-tested species; (3) obtaining the divergence time T between the to-be-tested species and a close relative species divergence ; (4) optimizing the phylogenetic tree of the to-be-tested species; (5) obtaining the annual germline mutation rate mu of the to-be-tested species year . The principle of the method is that neutral regions or neutral sites are widely distributed in the genome, and mutations at these positions are usually not affected by natural selection; by analyzing the variation frequency of these sites over time, the germline mutation rate can be calculated. The method described in the application is not only widely applicable to animal species of sexual reproduction that have obtained genome or transcriptome data, but also accurate and efficient, fills the gap in the prior art, and has important significance for theoretical research and practical application of biomedical engineering.