65 results about "Allele frequency" patented technology

The invention relates to the technical field of biomedicine, in particular to a method for constructing a plasma ctDNA organ distribution characteristic spectrum of advanced colorectal cancer. The method comprises the following steps: collecting a peripheral blood sample at multiple time points, separating plasma by adopting a double-centrifugal method, and extracting circulating tumor DNA (Deoxyribose Nucleic Acid); carrying out whole exome sequencing based on ctDNA to obtain genome variation information and calculating variation allele frequency, and synchronously detecting the expression quantity of immune-related proteins by adopting an Olink proteomics technology; integrating the genome data, the protein expression data and the clinical pathological features, and constructing a multi-dimensional feature data matrix; and taking the organ metastasis condition confirmed by iconography as a supervision label, training a model by applying a machine learning algorithm, screening key prediction factors, constructing a quantitative prediction model, and finally generating a visual organ metastasis tendency prediction map. According to the method, early and accurate prediction of the advanced colorectal cancer organ metastasis tendency is realized through multi-omics data collaborative analysis and machine learning modeling.

To improve allele discrimination, the inventors adapted the system combining Cas13a detection sensitivity with allele-specific PCR amplification to propose CASPER (Cas13a Allele-Specific PCR Enzyme Recognition) as a new versatile, easy-to-implement, and highly sensitive method to detect low-frequency of sequence variant. CASPER enabled specific and sensitive detection of KRASG12D with low DNA input such as DNA extracted from patient's pancreatic ultrasound-guided fine-needle aspiration fluids. CASPER is easy to implement and a versatile reliable method virtually adaptable to any point mutation.

The application provides a STR typing method applied to second-generation sequencing data, and relates to the technical field of biology.The method specifically comprises the following steps: customizing an STR locus configuration file; constructing a k-mer index library of a flanking sequence of the STR locus; extracting STR allele sequences from each READ of a sequence alignment file in combination with a CIGAR value and the k-mer index; constructing a PCR ghost peak model of the STR locus, and estimating parameters of the PCR ghost peak model by using a maximum likelihood estimation method; estimating candidate allele frequencies by using a second-generation sequencing sample data set; calculating posterior probabilities of all candidate alleles by using an allele set extracted from a given sequence alignment file, and inferring the most possible allele.The STR typing method has higher detection rate and typing accuracy, and has faster typing speed, and can be used for whole genome sequencing data, high-coverage targeted sequencing data or amplicon sequencing data.

The application discloses a kind of molecular markers of wheat stripe rust SNP homozygous site based on whole genome sequence and application thereof.The application is analyzed to 28 strains of global wheat stripe rust genome sequence, compared with reference genome, and more than a million SNP sites are mined out.Sequence depth screening, linkage disequilibrium analysis and heterozygosity detection, identify 1076 SNP homozygous sites.Further based on the frequency of secondary allele, screening of deletion rate and adjacent simple repeat sequence, finally determine 37 core SNP markers.Through primer design to these SNP sites, and add fluorescent linker, develop KASP-SNP molecular marker, which can be used for accurate genotyping identification of wheat stripe rust population.The molecular marker developed based on global wheat stripe rust whole genome is suitable for wheat stripe rust population research in all regions of the world.Based on the development of molecular marker of homozygous site, polymorphism difference caused by heterozygous site can be effectively excluded, to ensure the accuracy of detection site.The set of KASP-SNP molecular marker has high polymorphism, good repeatability and high detection efficiency, and can be widely applied to genetic research of wheat stripe rust population.

The application discloses a kind of based on molecular marker clustering analysis's cotton hybrid breeding combination screening method, the screening method includes: step S1: using multi-traits related molecular marker to the gene typing experiment of test cotton variety, data collection and arrangement are carried out;Step S2: excellent allele frequency calculation and feature matrix construction;Step S3: data standardization and principal component analysis dimension reduction;Step S4: optimal cluster number selection and genetic clustering;Step S5: each population character analysis;Step S6: heterosis potential score and combination screening.The technical problem that present cotton breeding parent selection lacks multi-traits comprehensive quantitative evaluation is solved, and the data of breeding decision-making and intelligentization are realized.

The invention relates to the field of bioinformatics and artificial intelligence analysis, in particular to a chromosome anomaly detection system and method based on a random forest model. According to the method, variation detection is carried out on the purified file, base replacement, insertion and deletion events are recognized, the allele frequency of each variation site is calculated, a standardized VCF format file is generated, the allele frequency spectrum of the variation sites is divided into a plurality of continuous intervals according to the preset step length, and the variation sites are extracted. Counting the number of sites of the sample data falling into each interval in a whole genome range and on each chromosome, and carrying out normalization calculation to generate a standardized feature vector; a random forest classification model trained by historical sample sequencing data with diagnosis tags is adopted to automatically judge all chromosome anomalies of the samples based on the standardized feature vectors of the samples; the method is superior to the existing SNP Array technology in the aspects of detection precision, detection range, chimeric recognition capability, intelligent degree, platform compatibility and the like.

The present application belongs to the technical field of sample pollution evaluation, and discloses a sample cross-contamination evaluation method, device, equipment and medium, comprising: performing quality control on batch sequencing data, and performing mutation site detection and genetic marker typing according to a human reference genome sequence and a site interval file; according to the genetic marker typing result and the site interval file, the number of heterozygous genotype sites is counted and the sample heterozygosity is calculated, according to the sample heterozygosity and a preset threshold, the sample contamination state is determined; according to the copy number estimation of the sample, the allele frequency is diploid standardized correction; based on the allele frequency in the genetic marker typing result and the mutation site detection result, the cross-contamination relationship between each two samples is analyzed by using identification rules to determine the pollution source; the site for calculating the pollution proportion is selected, and the weighted average algorithm is used to calculate the pollution proportion. The sample pollution degree can be accurately estimated and the pollution source sample can be identified.

The application discloses a method for detecting glioma chromosome abnormalities based on targeted sequencing, and belongs to the technical field of biological medicine. The method first acquires the allele frequency of a to-be-detected sample at preset SNP sites (covering 1p, 1q, 19p, 19q, chromosome 7 and chromosome 10), and then calculates and determines whether specific chromosome arms or chromosomes have loss of heterozygosity. Meanwhile, the copy number of the region where each SNP site is located is calculated based on the sequencing depth, and the total copy number of the above-mentioned chromosomes is obtained by integration. Finally, the loss of heterozygosity determination result and the chromosome copy number information are comprehensively combined, so that the simultaneous identification of 1p / 19q co-deletion, gain of chromosome 7 (+7) and deletion of chromosome 10 (-10) is realized. The method does not require paired samples, can accurately quantify the copy number, avoid false positives, and only needs to detect part of the SNP sites, that is, can be combined with hot spot mutation detection, thereby saving cost and improving detection efficiency.

The application discloses a method for detecting sample cross contamination based on SNP sites and application thereof. The method comprises the following steps: screening SNP sites, simulating data, constructing a model, and evaluating contamination degree according to the model. The screening of SNP sites comprises the following steps: (1) downloading sequencing-related FASTQ files or bam files from a database; (2) performing variation detection on high-throughput sequencing data of each sample in the files to obtain gvcf format files of variation information of the samples; (3) merging all gvcf files of the samples to obtain vcf format variation information of all the samples; and (4) screening SNP sites according to heterozygous state population frequency and variation allele frequency. The application simulates data of stable SNP sites carrying high population frequency, constructs a model, and evaluates contamination degree according to the model. The AF values of these SNP sites in different samples are relatively stable, and are concentratedly distributed near 0, 0.5 and 1; and the dose change of the AF values after the SNP sites contaminate other samples can accurately reflect the degree of sample cross contamination, and the operation is simple, fast and convenient.

The present disclosure is directed to a method for producing a Vpb4Da2 resistant insect pest species colony and / or a Mpp75Aa1.1 resistant insect pest species colony from an insect pest species isolated from an agricultural field. The present disclosure is also directed to methods for determining the inheritance of resistance to Vpb4Da2 and / or Mpp75Aa1.1, determining the allele frequency of resistance in an agricultural field, and / or mapping the locus of disease resistant genes or loci in the resistant insect pest species.

The invention belongs to the field of biological detection, and relates to an SNP (Single Nucleotide Polymorphism) combination for identifying hybrid lineage of foreign varieties and northeast local beef cattle and an application method of the SNP combination. A whole genome re-sequencing technology is utilized, northeast local beef Yanbian cattle is taken as a target group, European common cattle is taken as a reference group, Asian common cattle is taken as a transition group, and variation sites and a group genetic structure of northeast local beef cattle are analyzed; it is found that hybrid individuals of lizan or simmental and Yanbian cattle of foreign varieties exist in local beef cattle groups in northeast China. By calculating inter-population differentiation index (Fst), linkage imbalance (LD) and allele frequency (AF) of variation sites in the population, 1640 SNP sites are screened, and the lineage of Yanbian cattle can be identified.

This invention belongs to the field of animal molecular genetics and breeding technology, specifically relating to SNP molecular marker combinations for identifying kinship in Sunite Mongolian cattle and their applications. The marker combination consists of 141 highly polymorphic SNP loci distributed on bovine autosomes 1-29, with an average physical distance of 19.93 Mb between loci, exhibiting good genome coverage and locus independence. The selected SNP loci show high minimum allele frequency (MAF), expected heterozygosity (He), and polymorphism information content (PIC) in the Sunite Mongolian cattle population, with average values ​​of 0.4843, 0.4990, and 0.3745, respectively, and a cumulative exclusion probability of no less than 0.9999 under unknown maternal genotype conditions. The SNP molecular marker combination and its application method of this invention can provide a reliable molecular tool for the protection of Sunite Mongolian cattle germplasm resources, the construction of conservation populations, the selection of breeding bulls and cows, and the development of the Sunite Mongolian beef cattle industry, offering advantages such as ease of operation, moderate cost, and high accuracy.

The disclosure provides methods for estimating tumor purity from tumor samples without use of matched-normal controls. A set of genomic regions are identified based on a nucleic acid sequence data that is aligned to a reference genome. Each genomic region of the set of genomic regions includes one or more nucleotide-sequence variants relative to a corresponding genomic region of the reference genome. A B-allele frequency distribution for the biological sample is determined based on a B-allele frequency determined for each genomic region of the set of genomic regions. The B-allele frequency distribution is processed using a trained machine-learning model to estimate a metric identifying tumor purity in the biological sample.

The disclosure provides methods for estimating tumor purity from tumor samples without use of matched-normal controls. A set of genomic regions are identified based on a nucleic acid sequence data that is aligned to a reference genome. Each genomic region of the set of genomic regions includes one or more nucleotide-sequence variants relative to a corresponding genomic region of the reference genome. A B-allele frequency distribution for the biological sample is determined based on a B-allele frequency determined for each genomic region of the set of genomic regions. The B-allele frequency distribution is processed using a trained machine-learning model to estimate a metric identifying tumor purity in the biological sample.

The invention relates to the technical field of crop molecular breeding and biology, and discloses a sorghum whole genome 24K-SNP liquid chip and application thereof.The chip obtains 24062 SNP loci through process screening on the basis of whole genome re-sequencing data of global sorghum germplasm, and screening standards include that variation with the minimum allele frequency larger than 0.01 is reserved; it is ensured that the site flanking 100bp sequence is uniquely compared in a reference genome, and the consistency reaches 100%; removing redundant variation within 30bp at the downstream of the site; and implementing a distribution strategy that 6-7 sites are reserved in each 100Kb interval, a coding region is anchored preferentially, and a centromere region is filled. According to the method, the specific probe is used for liquid-phase hybrid capture, so that the method has the advantages of wide genetic background coverage, high capture specificity, uniform genome coverage and the like, can effectively solve the genetic typing problem of wild species and different-place germplasm, and is widely applicable to sorghum germplasm resource identification, whole-genome association analysis and molecular breeding research.

The present invention relates to a method for analyzing genetic material in a subject. More specifically, it relates to a method for analyzing genetic material using unphased genotypic information of polymorphic variants from one parent and one parent, in combination with the allele frequency of these variants in the subject's genetic material. Furthermore, the method of the present invention is particularly useful for analyzing isolated genetic material from a sample with a low amount of genetic material and / or for detecting low-level chromosomal mosaicism.

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.

A method of detecting loss of HLA allele heterozygosity is provided. The method may include accessing a trained machine learning model, the model being trained using a training dataset, the training dataset including at least the following training datasets: an adjusted B allele frequency, it represents a ratio between a first B allele frequency of a heterozygous allele corresponding to the genomic region in the tumor sample and a second B allele frequency of a heterozygous allele associated with one or more control samples in the genomic region. The method may also include using the machine learning model to generate a result corresponding to a probability of whether a loss of heterozygosity exists in HLA alleles identified in a biological sample of a particular subject by processing sequence data using the machine learning model.

The disclosed embodiments concern methods, apparatus, systems and computer program products for determining sequences of interest using unique molecular index (UMI) sequences that are uniquely associable with individual polynucleotide fragments, including sequences with low allele frequencies and long sequence length. In some implementations, the UMIs include both physical UMIs and virtual UMIs. In some implementations, the unique molecular index sequences include non-random sequences. System, apparatus, and computer program products are also provided for determining a sequence of interest implementing the methods disclosed.

The application discloses a method for detecting thyroid cancer driving gene mutations based on multiplex fluorescence PCR, and belongs to the technical field of molecular biology detection. The method simultaneously detects nine mutation sites, namely BRAF V600E, NRAS Q61R, NRAS Q61K, HRAS Q61R, HRAS Q61K, KRAS G12V, KRAS G12D, TERT C228T and TERT C250T in a single tube reaction. The method enhances the distinguishing ability of wild type and mutant types by using a locked nucleic acid modified allele-specific primer, suppresses wild type amplification by using a peptide nucleic acid clamp, introduces a competitive internal reference probe to correct amplification efficiency difference, and reduces the sample usage to one fifth of that of a traditional multi-tube scheme. The mutation detection lower limit reaches 0.5% allele frequency, and the total time consumption is not more than 2.5 h.

The invention discloses a tumor main clone allele frequency dynamic monitoring and closed-loop control method, and belongs to the field of biological gene detection and data processing. The method comprises the following steps: firstly, constructing a state space dynamic model containing state parameters of a master clone and a slave clone, introducing a molecular regulatory factor, then setting a main clone allele frequency monitoring threshold interval, synchronously acquiring abundance of the master clone and the slave clone detected by digital PCR at multiple rates, CRP, albumin and other hematopathology indexes as observation parameters, and carrying out quantitative analysis on the observation parameters. According to the method, observation parameters are predicted based on an extended Kalman filtering fusion model, the main clone allele frequency is accurately estimated in real time, and according to a comparison result of the main clone allele frequency and a monitoring threshold interval, the number of days for taking or stopping the targeted drug is dynamically adjusted, so that closed-loop control of the main clone allele frequency is realized. Closed-loop fusion of tumor monitoring and drug administration regulation is achieved, drug resistance germination is intervened in advance, and the progression-free lifetime of a patient is remarkably prolonged.

The invention relates to the technical field of biological information processing, in particular to a cattle embryo pre-implantation genetic evaluation method and system based on whole genome sequencing, and the method comprises the following steps: obtaining whole genome sequencing data of a male parent and a female parent, embryo trophoblast live detection sequencing data and culture solution free desoxyribonucleic acid sequencing data; performing variation detection and haplotype phasing on male and female parent data to form haplotype data, and calculating a haplotype transmission posterior at an anchor point based on trophoblast data; performing genome segmentation based on reading depth observation and allele frequency observation of a trophoblast and a culture solution, and performing Bayesian inference by combining haplotype transfer posteriori as priori to obtain posteriori probabilities of aneuploid, copy number variation, chimera, pathogenic homozygosis and pollution events; and outputting a passing / rechecking / elimination conclusion, adding sequencing and updating the posteriori during rechecking until ending, and outputting a final conclusion and a genome breeding value, so that the evaluation reliability and the decision interpretability are improved.

The application belongs to the technical field of molecular biology and molecular marker, and particularly relates to a SNP molecular marker related to pig daily weight gain on chromosome 1 of pig and application. The site of the SNP molecular marker related to pig daily weight gain on chromosome 1 of pig corresponds to the 162158624th nucleotide site on chromosome 1 of the international pig reference genome 11.1 version, and the base of the site is T or C. Through selecting the dominant allele of the SNP, the dominant allele frequency can be increased generation by generation, the pig daily weight gain is improved, the pig genetic breeding progress is accelerated, and thus the economic benefit of pig breeding is effectively improved.

This invention provides a molecular marker 27W1 for breeding high-fertility Litopenaeus vannamei populations and its applications. The nucleotide sequence of the molecular marker 27W1 is shown in SEQ ID No. 1, wherein the allele frequency of G at base 301 in high-fertility Litopenaeus vannamei populations is ≥98.33%. This invention also provides primers for the molecular marker 27W1, including amplification primers with nucleotide sequences shown in SEQ ID No. 2 and SEQ ID No. 3, and extension primers with nucleotide sequences shown in SEQ ID No. 4. The high-fertility molecular marker 27W1 for Litopenaeus vannamei can be used for early breeding of Litopenaeus vannamei, regardless of growth stage, to rapidly select parent populations with excellent reproductive traits and promote the breeding process of new high-fertility Litopenaeus vannamei varieties.

Provided is a technical method system for the identification of a gene frequency based on polymerase chain reaction (PCR) technology. Compared with other methods, the method has the following advantages: (1) reduced operation complexity and simple operation; (2) a shortened reaction time and lower cost; (3) resolution exceeding 1 in 100,000, with the largest and smallest frequencies differing by more than 10 orders of magnitude; (4) a detection throughput adjustable at will in a PCR tube system; (5) can implement single-tube, one-step detection of specific types of gene frequencies among a huge number of samples; and (6) capable of precise quantitative identification of gene frequencies across samples and / or across genes, corresponding to respective gene frequencies in different samples. The present invention can provide a reference for fields including, but not limited to, breeding, medical diagnosis, biomedical research and development, and pathogenic microorganism detection.

The application belongs to the technical field of animal molecular marker, and discloses a SNP marker combination for identifying Diqing Tibetan pigs. Based on whole genome resequencing data of Diqing Tibetan pigs and other pig breeds, sample quality control and population structure analysis are carried out to determine the core samples with clear genetic background. On this basis, the deletion rate of whole genome SNP sites is filtered, the polymorphism is filtered, and the linkage disequilibrium is filtered to reduce redundant sites. Further combined with the difference of allele frequency and genetic differentiation index, a specific SNP site set with stable allele frequency distribution in Diqing Tibetan pig population and significant difference from other pig breeds is screened to obtain 57 SNP sites. Compared with the traditional method depending on appearance characteristics or pedigree record, the application has the advantages of high sensitivity, convenient operation and low detection cost, and is suitable for breed verification in Diqing Tibetan pig germplasm resource protection and production management.

The invention discloses an ultrahigh-sensitivity chromosome copy number variation detection system and method, and belongs to the technical field of biological detection and gene sequencing. The technical problems to be solved are that an existing detection system lacks multi-feature integration capability, signal enrichment is weak, a threshold value is fixed, and sensitivity and anti-interference performance are insufficient. According to the technical scheme, the system is characterized by comprising a sample processing and sequencing module, a data preprocessing and quality control module, a multi-dimensional feature extraction module, a signal enrichment and model prediction module and a dynamic threshold value screening and result judgment module. And enriching signals through an integrated model and multiple attention mechanisms, fitting a dynamic threshold value based on a healthy person reference sample, and outputting a scenarized detection result in combination with multi-standard verification.

The invention discloses a method for rapidly identifying male and female cannabis sativa plants based on a specific DNA (Deoxyribose Nucleic Acid) sequence. Based on high-quality haplotype genome data of the cannabis sativa, population genetic differentiation indexes and allele frequency difference analysis are adopted, the fact that the cannabis sativa belongs to an XX / XY type sex determination system is determined, the sex chromosome of the cannabis sativa is positioned to be a 10 # chromosome, and a specific linkage region on a Y chromosome is positioned in a 28.17-118.28 Mb region. A Y specific gene sequence is identified, a specific PCR primer is further designed, and a rapid PCR amplification system is established. Compared with a traditional phenotype-dependent identification method, the method can simply, efficiently, accurately and rapidly screen the plants with the target gender in the seedling stage, remarkably saves field planting space and management cost, and is suitable for accurate screening of cannabis sativa with different purposes. The method can improve the breeding efficiency and economic benefits of the cannabis industry, provides technical support for sex control production of the cannabis, and has industrial application prospects.

Provided herein are systems and methods for allele-specific copy number (ASCN) calling using sequencing data. The presently described systems and methods can support various configurations based on different sequencing assays and disease contexts. The techniques include segmentation of target regions of interest based on similarity of coverage ratio and B-allele frequency (BAF) values for adjacent target regions, and estimation of an allele-specific copy number for each segment based at least one the observed coverage ratio, an expected coverage ratio, an observer BAF value, and an expected BAF value for each segment, wherein the expected coverage ratio and / or the expected BAF are calculated based on tumor purity, tumor ploidy, and total copy number for each segment.

Disclosed herein includes systems, devices, and methods for determining a B-allele frequency (BAF) value (e.g., a normalized BAF value) of a SNP for a test sample obtained from a test subject (e.g., a human subject) from optical genome mapping (OGM) data.