503 results about "High throughput sequence" patented technology

The invention discloses a method for evaluating enhancement and release seedling resources based on environmental DNA polymerization analysis. The method comprises the following steps: carrying out gridding partition on a target water area, collecting a water sample through a designed sampling scheme, and carrying out DNA extraction and high-throughput sequencing to obtain species sequence information of each sampling point. Sequencing data is subjected to species identification by using a bioinformatics method, released species are identified, a spatial abundance model is established, and a preliminary distribution map is generated. And establishing a DNA degradation kinetic model in combination with water area environmental parameters, and carrying out reverse correction on abundance distribution. And through a resource inversion model coupled with hydrodynamics, analyzing biomass distribution characteristics and migration laws of the release group, and obtaining a resource evaluation result. And finally, a species environment preference model is constructed based on migration path analysis, an optimal release area is matched in a target water area, a scientific scheme including release point locations, opportunities and quantity is generated, and a whole-process technical support and a decision basis are provided for enhancement and release.

The invention provides a nucleic acid aptamer for specific recognition of morphine and application of the nucleic acid aptamer, and belongs to the technical field of biosensing and detection. The nucleotide sequence of the nucleic acid aptamer is as shown in SEQ ID NO: 1. The screening method is based on a Capture-SELEX technology and comprises the key steps that streptavidin magnetic beads are used for fixing an ssDNA library, estradiol, deabietic acid and totarol are introduced to serve as reverse screening substances so as to remove non-specific sequences, and finally the high-specificity aptamer is obtained through high-throughput sequencing and affinity determination. The dissociation constant of the aptamer and morphine is 127.31 nM, and the aptamer shows high affinity and high specificity. The invention further relates to application of the aptamer in preparation of a sensor and a kit for detecting morphine, and a new technical means is provided for rapid detection of morphine.

The invention relates to the field of noninvasive prenatal diagnosis, and particularly discloses a preeclampsia noninvasive screening method based on deep sequencing 8bp oligonucleotide double-fragment characteristics, which comprises the following steps: collecting preeclampsia and healthy pregnant woman peripheral blood samples, and extracting free DNA for high-throughput sequencing; the method comprises the following steps: extracting core 8-mer sequences' GTGCGCCC 'and' GATGGGGT 'in a long fragment of 150-200bp through bioinformatics analysis; an integrated support vector machine, K-nearest neighbor, extreme gradient lifting, a random forest and a multi-layer perceptron are combined with a logistic regression element classifier to construct a stacking model, the frequency of a core sequence is normalized, machine learning analysis is carried out, and the preeclampsia risk is predicted. According to the invention, two 8bp oligonucleotide characteristic fragments are specifically screened, and a deep learning architecture of multi-model fusion is combined, so that the limitations of low specificity and invasive detection of a traditional screening method are effectively broken through.

The invention belongs to the technical field of biological detection, and particularly discloses a targeted sequencing primer group and a kit for detecting common pathogens of children and drug-resistant genes thereof. The primer group comprises 145 primer pairs of common children pathogen primer groups and 67 primer pairs of drug-resistant gene primer groups of the common children pathogen primer groups. According to the kit provided by the invention, nucleic acid in a clinical sample is directly extracted, 212 pairs of specific primers are adopted to realize multi-targeted amplification of a pathogen target area, a high-throughput sequencing platform is adopted to accurately identify pathogens and drug-resistant mutant genes thereof, 72 common children pathogens and drug-resistant genes thereof can be detected at the same time, and the kit has a wide application prospect. More accurate diagnosis information is provided for clinic, a key technical support is provided for early-stage accurate treatment of children infectious diseases, and the technical problems that in the prior art, in children pathogen detection, the detection speed is low, the number of missed detection is large, and the drug-resistant blind area is large are solved.

The invention relates to the technical field of environmental monitoring and water ecological safety, in particular to a eukaryotic algae outbreak early warning method and system based on genus-level specific recognition. The method comprises the following steps: collecting a water body sample at a monitoring position according to a preset sampling plan, collecting an environment measurement value, and respectively obtaining environment parameter data, a water sample sampling identifier and a sampling timestamp; extracting nucleic acid from the water sample at the monitoring position based on the water sample sampling identifier, performing targeted amplification, and performing high-throughput sequencing at the same time to obtain eDNA original sequencing data; therefore, by constructing the eukaryotic algae outbreak early warning process based on genus-level specific recognition, the problems that in a traditional method, sampling disturbance is uncontrollable, sequence judgment precision is insufficient, trend recognition is lagged, and an early warning link is not transparent are solved, and the accuracy, stability and traceability of early judgment of algae outbreak are improved.

The invention provides a method for evaluating grassland degradation based on microbial community structures and composition, and belongs to the technical field of grassland degradation degree evaluation. The method comprises the following steps: selecting a representative sample plot in a to-be-evaluated grassland degradation area, selecting a sample square in the sample plot, and collecting rhizosphere soil in the sample square; mixing rhizosphere soil of all quadrat belonging to the sample plot to obtain a soil sample; analyzing the OTU number of bacteria and the OTU number of fungi in the soil sample by adopting high-throughput sequencing; calculating a grassland degradation grade evaluation value according to the OTU number of the bacteria and the OTU number of the fungi; according to the grassland degradation grade evaluation value and the grassland degradation grade evaluation standard, grassland degradation evaluation is carried out, and an evaluation result is obtained. The grassland degradation grade evaluation value of the to-be-evaluated area is calculated by taking the microflora structure and composition of the to-be-evaluated area as evaluation indexes, and the grassland degradation grade of the to-be-evaluated area is determined in combination with the grassland degradation grade evaluation standard.

The invention belongs to the technical field of gene detection and gene molecular breeding, and particularly relates to a meat duck whole genome molecular probe combination based on molecular phenotype screening, a 50K gene chip and application thereof. The molecular probe combination and the gene chip of the marker site combination for meat duck whole genome breeding simultaneously cover 7 representative meat duck varieties and 71 economic characters, have richer polymorphism and higher pertinence in meat duck groups, and are lower in cost and higher in speed compared with high-throughput sequencing detection; the breeding chip is designed according to the growth, feed efficiency, slaughtering, breeding, egg quality and various molecular phenotypes of the meat ducks, and compared with a high-throughput sequencing technology, the breeding chip is higher in seed selection accuracy, has higher breeding value, can be widely applied to breeding genotype detection of the meat ducks, and can be used for detecting the breeding genotypes of the meat ducks. And the method has creative significance in the aspect of meat duck genome selective breeding.

The invention relates to the technical field of immune repertoire sequencing, in particular to a sequence data analysis method and device for biological system state modeling and a storage medium. According to the method, high-throughput sequencing data of B / T cell receptors are acquired, nonlinear gain correction and V-J gene combination preference feature extraction are performed, structured feature nodes are constructed, features are coded by using a Transform model, a system state vector is generated in combination with weighted average pooling, adversarial training is introduced to realize feature decoupling, and signal interference among functional categories is inhibited. And calculating a multi-dimensional immune intensity score based on the system state vector, and quantifying immune response active degrees of different function categories. According to the method, high-sensitivity and multi-dimensional parallel modeling and dynamic evaluation of the immune system state are achieved, the method is suitable for large-scale population immune monitoring and system biological research, and the analysis capacity and application value of immune group library data are remarkably improved.

The invention relates to an analysis method, device and equipment for pathogen targeted high-throughput sequencing data and a medium. The method comprises the steps that targeted enriched pathogen high-throughput sequencing data is generated through an integrated reaction of a chimeric primer and a pathogen sample to be analyzed, and the chimeric primer is composed of a targeted sequence and a linker sequence; corresponding analysis conditions are matched for pathogen species detected according to the pathogen high-throughput sequencing data, the analysis conditions are set based on quality control indexes of the pathogen sample to be analyzed, and the quality control indexes are obtained through comparative analysis of all pathogen test samples and standard pathogen samples; and analyzing the pathogen high-throughput sequencing data according to the analysis conditions to obtain a data analysis result. By adopting the method, the analysis accuracy of data analysis on the pathogen targeted high-throughput sequencing data is improved.

The invention provides an SNP molecular marker combination for paternity test and individual recognition of dairy cows and application, the SNP molecular marker combination comprises 300 SNP markers on 29 autosomes of the dairy cows, the marker combination can be applied to paternity test and individual recognition of the dairy cows, and an identification method comprises the step of preparing a liquid phase chip of the 300 SNP markers, constructing a high-throughput sequencing library by using the genome DNA of the dairy cow to be detected; mixing the liquid phase chip probe with a high-throughput sequencing library, capturing a DNA fragment containing a target SNP site in the dairy cow DNA high-throughput sequencing library, amplifying and purifying to obtain a genetic typing of a dairy cow individual to be detected, and performing paternity test inference according to the genetic typing. The invention provides a probe and a kit for identifying SNP (Single Nucleotide Polymorphism) site information. According to the invention, the SNP polymorphism is detected through targeted capture sequencing, through high-depth sequencing, the typing result is accurate and reliable, and the accuracy of paternity test and individual recognition is ensured.

The invention belongs to the technical field of biological detection, and discloses a transgenic crop intelligent identification method based on high-throughput sequencing, which comprises the following steps: acquiring multi-platform high-throughput sequencing original data and sample metadata, evaluating quality by platforms, dividing according to a sample partitioning rule, and generating a quality-controlled data block set; distributing data blocks to a plurality of parallel computing nodes, synchronously executing technical detection to obtain technical fact fragments, aggregating and supplementing batch statistical information, and generating a technical fact report; matching the judgment rule set, carrying out parallel judgment, triggering expert rechecking on boundary cases, and integrating to generate a supervision judgment conclusion set; the method comprises the following steps: extracting original sequencing reads of all samples, generating a unique hash for each read, constructing a processing track chain, integrating metadata and visual evidence, generating a credible authentication report, dividing different scene versions, and performing targeted distribution; and extracting identification cases for mining and clustering, generating optimization suggestions, and feeding back the optimization suggestions to the quality control rule base and the judgment rule base.

The invention provides a phytophagous insect food web DNA molecular data automatic analysis method and device based on high-pass sequencing and a storage medium, and relates to the field of molecular biological information detection.The method comprises the steps that sequence splicing, screening and species identification are carried out on obtained double-end sequencing data and local and downloaded DNA databases through an automatic system, and a DNA molecular database is obtained; generating an Excel table containing species names and a DNA bar code sequence file; performing comparative analysis on the double-end sequencing data by adopting matching splicing, and generating a contiguous group sequence based on a local DNA database; if the matching splicing cannot generate the effective sequence, generating a new gene file by adopting non-parameter splicing, and performing gene annotation in combination with the downloaded DNA database; all analysis steps are connected in series through standardized parameter input, including gene screening through threshold values and generation of insect recipe identification results. According to the method, the sequencing data can be subjected to full-process automatic analysis through a one-key command, and the efficiency of food web authentication high-throughput sequencing data processing is greatly improved.

The invention relates to an eDNA method for identifying bumblebee honeycombs in permafrost regions of Qinghai-Tibet Plateau. The eDNA method comprises the following steps: S1, positioning observation sample belts and arranging sampling points on the basis of multi-source data in combination with a Bayesian hierarchical model; s2, performing deep freezing and complete excavation on matrixes around and inside all the sampling points; s3, stratified sampling and anti-degradation treatment are carried out, and a spatial attribute database is established; s4, extracting and purifying eDNA (enhanced deoxyribonucleic acid); s5, determining a nest host based on PCR amplification, high-throughput sequencing and sequence comparative analysis; and S6, constructing a Bayesian hierarchical model in combination with biological information, and judging honeycomb characteristics. The method is simple, rapid and low in cost, not only is suitable for Qinghai-Tibet Plateau permafrost regions, has the core advantages of non-destructiveness and high sensitivity, but also is also suitable for underground insect nest identification research in other environment sensitive regions or regions difficult to physically explore in principle, and has wide application prospects. The method is especially suitable for monitoring rare, secret or difficult-to-approach organisms.

The invention belongs to the technical field of tumor molecular diagnosis and biological information analysis, and relates to a high-throughput sequencing method and system for monitoring acute lymphocytic leukemia (MRD). Through targeted sequencing with a unique molecular identifier and / or a double-chain tag, error modeling based on a background noise spectrum and statistics / machine learning pseudo variation filtering, ultra-deep accurate detection of IG / TCR cloning and related gene low-frequency variation is realized. And an artificial intelligence recurrence risk prediction model is established by combining a time sequence MRD index, cloning diversity and clinical information, and a structured clinical report is output and docked with LIS / HIS. According to the method, the sensitivity and the specificity of ALL minimal residual disease detection can be remarkably improved, dynamic evaluation on leukemia cloning evolution and recurrence risks is realized, and a reliable basis is provided for individualized treatment decision and long-term follow-up visit.

Provided is an application of a circular RNA in the preparation of a cerebral stroke diagnosis product, belonging to the field of circular RNA medical treatments. Provided is a kit, comprising a reagent and / or test paper and / or gene chip for detecting a circular RNA-circ-Magi1. The nucleotide sequence of the circular RNA-circ-Magi1 is as shown in SEQ ID NO: 1 or SEQ ID NO: 4. Further provided is the application of a detection system for the diagnosis, assisted diagnosis or prognosis evaluation of cerebral stroke, and a detection reagent of the circular RNA-circ-Magi1 in the preparation of a kit, test paper, chip or high-throughput sequencing platform for the diagnosis, assisted diagnosis or prognosis evaluation of cerebral stroke.

Disclosed herein are methods for profiling a cancerous tumor using a high-throughput sequencing technique.

The invention relates to the technical field of intelligent peanut disease monitoring, in particular to an intelligent peanut disease monitoring method based on community diversity analysis. According to the method, soil environment parameters are collected in real time through a multi-source sensor array, and rhizosphere microorganism DNA is extracted based on an improved CTAB-PEG method for high-throughput sequencing; constructing a dynamic baseline model fusing a Shannon-Wiener index, a phylogenetic diversity index and an environment correction factor; synchronously analyzing spatial distribution and time evolution characteristics of an OTU abundance matrix by adopting a deep space-time convolutional network, and decoding a microbial anomaly succession signal through a gating circulation unit; and when the disease risk index exceeds a threshold value, activating an early warning terminal and generating a resistant variety adaptation scheme. According to the method, the problems of incomplete microorganism capture, misjudgment of environmental interference, early warning lag and the like of a traditional method are solved, and collaborative optimization of precise early warning and prevention and control decision of peanut diseases is realized.

The invention relates to the technical field of microbial directional cultivation, in particular to a gene editing-based MICP functional bacteria directional cultivation method and system, and the method comprises the following steps: obtaining an original strain library with MICP activity, carrying out strain activation on the original strain library, carrying out high-throughput sequencing on the original strain library, and carrying out gene mining on an initial sequence; the method comprises the following steps: carrying out gene editing on strains in an initial strain library by using a gene editing tool, carrying out shake-flask activation on engineered candidate strains to obtain an activated recombinant bacterium solution, carrying out high-density culture on the activated recombinant bacterium solution by using a pre-constructed fermentation tank, screening out an MICP strain with the optimal function, carrying out continuous passage bacterium function detection on the optimal MICP strain, and carrying out high-density culture on the MICP strain with the optimal function. And based on the MICP functional bacteria, finishing directional cultivation of the MICP functional bacteria based on gene editing. According to the invention, directional cultivation of the MICP functional bacteria is efficiently realized by accurately targeting the key gene with the MICP function, and the MICP functional bacteria are corrected when the problems of function instability and the like exist, so that the more stable MICP functional bacteria are obtained.

The present invention discloses a method for regulating carbon accumulation in degraded karst forest soil by synergistic microbial functions, comprising: measuring and collecting bacterial and fungal diversity sequence data of degraded karst forest soil samples by high-throughput sequencing equipment, storing the original sequencing data including diversity, community structure, functional abundance values, etc. in a computer-readable storage medium, and constructing a structured microbial community database; based on the database, a computer system performs screening of core functional microorganisms that affect carbon storage; based on the screening results, the computer system performs the following processing: calculating the functional abundance index of core microorganisms; determining the microbial function weight by multivariate linear regression; establishing a carbon accumulation regulation coefficient calculation model; preparing a microbial agent and generating a control instruction including the microbial agent application amount and the vegetation coverage optimization plan according to the calculated value of the carbon accumulation regulation coefficient and the soil organic carbon saturation deficit value, and transmitting the control instruction to the field operation equipment.

The invention relates to a flora transplantation clinical pathway standardization management method, device and equipment and a medium. The method comprises the following steps: on the basis of clinical data of a patient and screening data of a donor, executing flora suitability evaluation by using a deep learning model and selecting an adaptive donor; obtaining a flora sample of an adaptive donor, and carrying out high-throughput sequencing; generating a donor flora quality evaluation score according to a preset flora composition diversity index based on a sequencing result; screening the flora samples of which the quality evaluation scores are higher than a preset quality threshold value to prepare a flora preparation; detecting activity parameters and diversity parameters of the flora preparation, and performing colonization potential classification prediction by combining clinical data of the patient and adopting a support vector machine algorithm so as to output a potential colonization success rate; and when the potential colonization success rate exceeds a preset success rate threshold, outputting a clinical transplantation scheme through a preset transplantation scheme generation algorithm based on the flora preparation and the clinical data of the patient. According to the method, through multi-stage intelligent decision making, the safety and the effectiveness are improved.

Disclosed are methods of preparing a composition of non-naturally occurring DNA, comprising: (a) extracting DNA from a sample of a subject; (b) contacting the extracted DNA or its derivative with a panel of oligonucleotide probes designed to hybridize to a plurality of preselected genomic regions, thereby generating selected DNA, wherein at least 50% of the preselected genomic regions are CpG regions that each comprises at least 3 CpG sites and a CpG density of at least 0.02 CpG / bp, wherein the preselected genomic regions cover 10-500 Mb of sequence space in human genome, wherein the extracted DNA or its derivative or the selected DNA or its derivative is further treated with an agent or a combination of agents that discriminates between methylated and unmethylated cytosines; and (c) performing high-throughput sequencing on the selected DNA or its derivative and generating sequencing reads.

The invention discloses a microsatellite instability detection method based on single-sample high-throughput sequencing for microsatellite site micro-offset, and relates to the technical field of bioinformatics, and the microsatellite instability detection method comprises the following steps: processing a sequencing sequence of a to-be-detected sample obtained by a high-throughput sequencing technology to obtain a comparison file; according to the method, selection and quality control of microsatellite sites are strictly controlled, a microsatellite instability detection method based on single-tumor sample high-throughput sequencing can be used for analyzing the repetition times of candidate microsatellite site repetition units without depending on a control sample, and meanwhile, the method has very good sensitivity to a sample with relatively large offset, so that the accuracy of the microsatellite instability detection is greatly improved. The method can also be applied to other cancer species with MSI characteristics, and can adapt to detection requirements of different cancer species by adjusting candidate microsatellite loci no matter whether a micro-migration condition exists or not, provide visualization, assist in seeing the degree of microsatellite migration, facilitate manual recheck and reduce misjudgment.

The invention relates to the technical field of sequencing, in particular to a Tn5 transposase-based next-generation sequencing method and a DNA library rapid construction kit, and particularly provides a Tn5 transposase-based next-generation sequencing DNA library rapid construction kit, a next-generation sequencing method and a next-generation sequencing DNA library construction method, and the kit comprises a reagent for constructing a next-generation sequencing DNA library. The Tn5 transposase is adopted for double-end Index library building sequencing, the library building process can be simplified, high efficiency and accuracy of high-throughput sequencing can be ensured, DNA fragmentation and linker addition are achieved in a single step by means of the unique characteristics of the Tn5 transposase, the sequencing efficiency and data management flexibility are improved by introducing the double-end Index, and the method is suitable for large-scale popularization and application. Each Index sequence ensures high specificity and traceability, meanwhile, the sequencing method can effectively work under the condition of low initial template quantity, and the application range is expanded.

The invention relates to a construction method of a nanometer antibody coding DNA library. The method comprises the following steps: screening animal peripheral blood mononuclear cells (PBMC) by using immunogen to obtain positive cells specifically bound with the immunogen; and amplifying a nucleic acid sample derived from the positive cells so as to obtain a coding DNA library of the nano-antibody, wherein the nano antibody is a nano antibody specifically binding to the immunogen, and wherein the amplification comprises the use of one or more groups of primer pairs, each group of primer pairs of the one or more groups of primer pairs comprising one or more forward primers and one or more reverse primers. A large number of diversified DNA sequences covering a large number of low-abundance sequences are obtained. According to the technical route for rapidly preparing the VHH antibody based on high-throughput sequencing, the high-affinity and high-specificity VHH antibody can be efficiently and rapidly obtained, and the raw material requirement of a high-quality diagnostic reagent is met.

The invention discloses a method and a device suitable for CUAMP. The invention discloses a method for extracting liriodendron tulipifera cell nucleuses by a Tag technology and application of the liriodendron tulipifera cell nucleuses. Hybridized liriodendron tulipifera calluses are used as materials, and protoplasts are released through enzymolysis solution vacuumizing and mild enzymolysis for 1.5 h; the method comprises the following steps: sequentially purifying by using a W5 solution and mannitol, detecting the activity by FDA, cracking by using an NE buffer solution, and washing by using a Wash buffer solution in two steps, thereby obtaining 2 * 10 < 6 >-3 * 10 < 6 > high-purity and high-integrity cell nucleuses. The obtained core is clean in background and complete in membrane structure, and can be directly used for CUTamp; tag is used for building a library, so that the magnetic bead capturing efficiency is improved by 46%, and protein-DNA interaction high-throughput sequencing under the condition of low sample size is realized. The method disclosed by the invention is simple and convenient to operate and good in repeatability, and provides key technical support for epigenetic research of rare tree species such as liriodendron tulipifera.

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.

The invention provides a cactus plant species identification method based on high-throughput sequencing data. A specific variation region in a cactus chloroplast genome is screened based on a high-throughput sequencing data system, and a standardized cactus plant species rapid identification process is developed by combining Pi value screening and specific variation region marking. Compared with a traditional DNA bar code fragment, the identification precision of the targeted specific variation region is remarkably improved, so that species with highly overlapped forms can be effectively distinguished, and the identification accuracy is improved. Meanwhile, the method greatly reduces the technical threshold and cost, PCR amplification is performed on the DNA of the sample to be detected by designing a specific primer of a targeted specific variation region, whole genome sequencing and assembly are avoided, the detection cost and detection period of a single sample are reduced, and the method is compatible with a conventional PCR platform and has high practicability. And on-site rapid detection of scenes such as a medicinal material market and a customs port becomes possible.

The invention discloses a whole genome methylation detection method based on MeDIP-MSRE, and belongs to the technical field of epigenetics detection. According to the method, methylation immunoprecipitation sequencing and a methylation sensitive restriction enzyme technology are innovatively combined, firstly, a methylation specific antibody is used for conducting immunoprecipitation on sample DNA, and whole genome methylation fragments are enriched; then carrying out enzyme digestion on the enriched product by adopting methylation sensitive restriction enzyme, specifically removing an unmethylated DNA region, and reserving a complete methylation sequence; and finally, constructing a methylation map through high-throughput sequencing. According to the method, traditional hydrosulfite chemical conversion is not needed, DNA damage and base conversion deviation caused by the traditional hydrosulfite chemical conversion are avoided, meanwhile, high sensitivity of MeDIP and high specificity of methylation sensitive restriction endonuclease are fused, and the fidelity, sensitivity and specificity of detection are remarkably improved.

This invention discloses an efficient RNA data preprocessing method to address the problems of low processing efficiency and low information density in high-throughput sequencing data. Its core steps include: (1) introducing a parallel processing scheme for high-throughput sequence data, rapidly mapping RNA-seq data to a reference genome to generate a BAM file; (2) extracting base sequences and expression levels and storing them as compact PKL format files; (3) extracting all exon position information by parsing the genome annotation file; (4) combining multi-sample expression level data to screen for highly variable exons and constructing a high-information-density feature list based on the sample set; and (5) accurately extracting target sequences from the preprocessed file based on this list. Compared to traditional methods, this innovative approach achieves triple optimization: full-process parallel processing for accelerated computation, high-compression data storage, and adaptive feature selection. Processing speed is increased by 3-5 times, and data volume is reduced by more than 90%, making it suitable for high-throughput RNA-seq data analysis with large sample sizes.

The invention discloses a specific primer group for simultaneously detecting 54 urinary tract infection-related pathogens and 26 drug-resistant genes and a related detection method thereof, which is characterized in that the specific primer group aiming at the 54 urinary tract infection-related pathogens and 26 key drug-resistant genes is designed and is combined with an ultra-multiplex PCR (Polymerase Chain Reaction) and high-throughput sequencing technology, so that the specific primer group can be used for simultaneously detecting the 54 urinary tract infection-related pathogens and 26 key drug-resistant genes, and the specific primer group can be used for simultaneously detecting the 54 urinary tract infection-related pathogens and 26 key drug-resistant genes. One-stop synchronous detection is achieved, the limitation that traditional pathogen culture is long in period and difficult to culture and the detection rate of pathogens is low is broken through, and the defects that in an existing molecular detection technology, target spot coverage is small, and pathogens and drug-resistant genes cannot be analyzed synchronously are overcome. The method provides key technical support for clinically and rapidly formulating a precise anti-infection treatment scheme, reducing blind medication and delaying development of drug resistance, meanwhile, reduces diagnosis and treatment cost and time cost caused by multiple times of detection, and has extremely high clinical application value.