13 results about "Third generation sequencing" patented technology

The invention relates to the technical field of information, and discloses a method for carrying out automatic analysis and typing on HLA based on third-generation sequencing. The method comprises the steps that firstly, the HLA type of first sequencing read data of different data types of a to-be-detected sample is preliminarily judged, then second sequencing read data is selected, then the identified second sequencing read data of different HLA types and a corresponding HLA reference sequence are compared, verified and screened, and therefore the HLA type existing in the to-be-detected sample is determined; according to the method, long read length data generated based on a third-generation sequencing technology can be effectively processed, the calculation amount of accurate comparison is reduced, accurate analysis and report generation of typical third-generation HLA data within 15 minutes can be achieved, and the requirement for rapid HLA detection analysis is met; meanwhile, the method can be used for analyzing short read length data obtained by next-generation sequencing, and has relatively good data compatibility.

The invention provides an HLA typing method and an electronic device thereof. The method comprises the following steps: S1) comparing sequencing data of each sample gene with an HLA gene database to obtain a first candidate HLA gene typing set; s2, in the first candidate HLA genetic typing set, typing results with the coverage degree smaller than 30% or the average sequencing depth smaller than 30 * are filtered, and a second candidate HLA genetic typing set is obtained; s3) according to the consistency sequence of the corresponding sample gene in each typing result in the second candidate HLA gene typing set, the typing results which are different from the coding region of the corresponding consistency sequence in the coding region of the sample gene are filtered, a final HLA typing result is obtained, and the sample HLA gene is obtained through sequencing of a three-generation sequencing platform.

The invention discloses a virus species identification method, an identification system, equipment and a medium. The method comprises the following steps: acquiring an original reference database comprising non-redundant virus species and subspecies sequences; breaking the sequences in the original reference database, comparing the sequences with the original reference database, and replacing the sequences in the original reference database, which are compared more than 1, to obtain a first reference database; comparing original offline data of second-generation and third-generation sequencing to a first reference database, and identifying species based on comparison abundance; breaking the sequence of the original reference database, comparing the sequence with the original reference database, and replacing the compared sequence to obtain a second reference database; and comparing the spliced genome data to a second reference database, and identifying species based on the site score. According to the method, a read data comparison strategy is directly used and is used for a standardized analysis process of virus species identification, multiple species can be identified and can be accurate to a subspecies level, and the identification rate is high and rapid.

The invention provides a method for rapidly detecting microbial species, and particularly, the method comprises the following steps: constructing a double-level database and a corresponding gene cluster; constructing a reference matrix X based on the database and the gene cluster; comparing to-be-detected third-generation sequencing data with the gene cluster to generate equivalence classes, and constructing a counting matrix Y based on the equivalence classes and the gene cluster; based on the counting matrix Y and the reference matrix X, determining the gene abundance in the to-be-detected sample; and determining microbial species in the sample to be detected based on the gene abundance. The rapid pathogen detection method provided by the invention is high in analysis speed, fully utilizes the advantages of the three-generation sequencing data, and can more directly obtain the microorganism composition information of the sample; the method is low in computing resource demand, easy to deploy and high in precision detection capability.

The invention discloses a primer group, a kit and a detection system for thalassemia gene detection. In order to more comprehensively and accurately detect point mutation, small insertion, small deletion, gene fusion mutation, large fragment deletion and gene structure variation on a thalassemia core gene and a modified gene in single detection, the invention provides a thalassemia gene detection primer group and a kit. Based on third-generation sequencing platforms such as a single-base nanopore sequencing platform and the like, all point mutation, small insertion, small deletion and gene fusion mutation in the amplification range of the thalassemia core gene and the modified gene can be detected by utilizing the primer group or the kit; and 60 alpha large fragment deletion mutations, 60 beta large fragment deletion mutations and 7 gene structure variations. The method is beneficial to rapid and comprehensive screening of thalassemia, and is high in detection sensitivity and good in accuracy.

The application discloses a kind of based on third-generation sequencing genome short variation deep learning detection method and system, by setting the image coding mode of genome sequence generated to third-generation sequencing platform, and according to real variation set and corresponding sequence alignment data establish training set, verification set and test set;Convolutional neural network and the deep learning multi-task classifier integrated by bidirectional long short-term memory neural network is constructed, training set and verification set are used to train and verify deep learning classifier, and the accuracy of deep learning classifier is tested using test set;Based on the deep learning classifier trained, the classification prediction of the stacked image generated by sequence alignment or real variation set is carried out;According to the classification prediction result of stacked image, variation site detection is carried out to sequence alignment data, and complete candidate variation information is obtained, to realize the automatic detection of genome SNP and INDEL short variation.

The application discloses a method and device for short tandem repeat sequence typing based on third-generation sequencing data and a storage medium. The method for short tandem repeat sequence typing based on third-generation sequencing data provided by the application first extracts all read segments completely covering the short tandem repeat sequence region according to a short tandem repeat sequence site directory; and filters the read segments by average alignment quality to remove low-quality read segments; then calculates the copy number of the short tandem repeat sequence in each read segment, and combines mutation site information of the short tandem repeat sequence to confirm short tandem repeat sequence typing. The method provided by the application can accurately calculate the repetition number of the short tandem repeat sequence, and combines the mutation site to determine the short tandem repeat sequence typing, so that more accurate genotyping results can be provided. Moreover, the method provided by the application is suitable for third-generation sequencing data of different sequencing platforms, has strong applicability, and can maximize the advantages of the third-generation sequencing read length.

The invention discloses a distributed sequence alignment method and system based on Spark, and relates to the technical field of bioinformatics, and the method comprises the steps: receiving a Minimap2 reference sequence, and generating a multi-part index of the reference sequence based on a multi-part index generation function of the Minimap2; partitioning the multi-part index of the reference sequence based on a character string in the multi-part index of the reference sequence as an identifier to obtain a partitioned copy, and distributing the partitioned copy to each node of a Spark cluster; receiving a query sequence, partitioning the query sequence through a file format of FASTA or FASTQ, and generating a multi-node shared task queue based on the number of partitions of the reference sequence, the number of partitions of the query sequence and partition copies on each node; and based on the multi-node shared task queue, each node selects the task in the task queue which needs to process all the remaining tasks and takes the longest time in the task queues corresponding to all the index file partition copies of the node to process, and a task processing result is obtained. According to the method, strategies of query sequence partitioning and reference sequence database partitioning are combined, dynamic load balancing is achieved by establishing a multi-node shared task queue, and the efficiency of comparison between Minimap2 and a large-scale data set is optimized. The method is suitable for long sequence data generated by a third-generation sequencing technology, and is especially suitable for application scenes of on-site rapid sequencing and analysis.

The application discloses a method for identifying and evaluating schizophrenia risk structural variations based on third-generation sequencing, relates to the field of molecular biology, and performs whole genome sequencing on peripheral blood DNA of a patient through third-generation sequencing, adopts multi-tool joint detection, integrates multi-sample results, and generates a high-confidence SV data set; through cross-queue comparison, patient-specific SV is screened, and high-risk potential pathogenic SV is identified in combination with an SV prioritization tool, SVJudge; transcription factor binding analysis, SCZ drug target data and tissue cell-specific expression data are combined to evaluate the influence of SV on gene regulation and analyze the potential action mechanism of SV in SCZ. SCZ risk genes are screened based on SVJudge scores and patient carrying conditions, the genetic risk and pathogenic mechanism of the SCZ risk genes are verified through pathway enrichment, protein interaction network and functional module analysis, and a new technical means and theoretical basis are provided for genetic research of SCZ.

The invention discloses a method for detecting a molecular marker related to cattle heat stress adaptability, which comprises the following steps: comparing genomic sequences obtained by a three-generation sequencing method on northern cattle and southern cattle samples, detecting structural variation and verifying biological functions; the difference between the carrying condition of deletion mutation of the PADI3 gene region 2: 135317354-135317410 and the length of 57 bp in a cattle population and the heat stress adaptability among individuals is investigated through correlation analysis, wherein the deletion mutation is located in a cattle reference genome and is in a region 2: 135317354-135317410; finally, it is revealed that the structural variation region can provide candidate molecular markers for effective detection on the DNA level for breeding and improvement of bovine heat stress tolerance populations.

The invention discloses a deep learning detection method and system for genome structure variation based on third-generation sequencing. Simulation data and real data are used for constructing a sequence data set; the method comprises the following steps of: according to comparison modes of various structural variations, extracting comparison and depth signals from comparison data of a long read sequence generated by a third-generation sequencing technology, realizing coding from a genome sequence to a four-channel image, and constructing a supervised training set, a supervised verification set and a supervised test set based on a structural variation set and the corresponding comparison data; establishing a double-path CNN integrated deep learning classification model with an attention mechanism, and performing model training, verification and testing by using a training set, a verification set and a test set; and predicting a four-channel image generated by sequence alignment data coding based on the trained deep learning classification model, and identifying a genome structure variation type and a breakpoint coordinate according to a prediction result of image classification so as to realize automatic detection of genome insertion, deletion, inversion and repeated structure variation.

The invention discloses a splicing type library building method based on complementary tail sequence annealing and collaborative extension connection reaction. Dividing a nucleic acid library to be detected into two parts, and respectively adding complementary tail sequences to obtain two parts of reaction products; mixing the two reaction products after the complementation of the tail sequence, performing denaturation cooling treatment, performing specific annealing on the complementation tail sequence to form an inter-fragment bridging structure, and performing annealing-extension-connection in the solution after the reaction to form a continuous controller long-chain molecule so as to obtain a double-chain product; the method comprises the following steps: adding a primer with end repair, adding polymerase, ligase and a nucleotide substrate at the same time, carrying out annealing treatment to obtain a preliminary library, and finally carrying out magnetic bead purification treatment and linker connection to obtain a final spliced library. According to the method, the problems of limited read length and low hole utilization rate in the construction of the third-generation sequencing library are solved, the average read length and the sequencing hole utilization rate are remarkably improved, the library construction process is simplified, and the cost is reduced.

The application relates to the field of information technology and discloses a method for automatically analyzing and typing HLA based on third-generation sequencing; first, the HLA types of first sequencing read data of different data types of a to-be-tested sample are preliminarily judged, then second sequencing read data is selected, then the identified second sequencing read data of different HLA types is compared with corresponding HLA reference sequences for verification and screening, so that the HLA types existing in the to-be-tested sample are determined; the method can effectively process long read length data generated based on third-generation sequencing technology, reduces the calculation amount of accurate comparison, can realize accurate analysis and report generation of typical third-generation HLA data within 15 minutes, and meets the demand of rapid HLA detection and analysis; meanwhile, the method can also analyze short read length data obtained by second-generation sequencing, and has good data compatibility.