Gene fusion detection Panel performance evaluation method and device

Abstract

The invention discloses a gene fusion detection Panel performance evaluation method and a gene fusion detection Panel performance evaluation device, and belongs to the field of information analysis. Based on a pre-constructed fusion gene transcript database, different types of known fusion gene single-stranded DNA (deoxyribonucleic acid) are synthesized and used for simulating an unknown fusion gene combination; amplifying the single-stranded DNA of the fusion gene; transcribing an amplification product; capturing the transcriptome library by using the Panel to be evaluated and detected; the captured transcript is subjected to sequencing; performing data processing on the sequencing data; judging whether the sequencing data pass quality control or not; and if yes, analyzing a target fusion detection condition based on the processed sequencing data. According to the method, a fusion gene bank with comprehensive coverage is constructed, the detection performance of Panel on known fusion genes can be evaluated and detected through a bioinformatics analysis method, and the capacity of detecting unknown fusion genes can be predicted.

Description

Technical Field

[0001] The present invention relates to the field of bioinformatics analysis technology, and more specifically, to a gene fusion detection panel performance evaluation method and device. Background Art

[0002] Gene fusion refers to a form of gene splicing in the genome, which causes two or more gene sequences to merge into a new fusion gene. This fusion may be caused by genetic events such as gene mutation and gene rearrangement. Fusion gene detection plays an important role in the medical field. It can not only play an important role in auxiliary diagnosis, etiology exploration, prognosis assessment, medication guidance and monitoring of minimal residual disease, but also provide valuable resources and data support for scientific research.

[0003] Targeted high-throughput sequencing at both the DNA and RNA levels can detect the presence of fusions in genes. At the DNA level, the fusion breakpoints are usually located in longer intronic regions, and the breakpoints of fusions vary greatly. Therefore, fusion gene detection must cover very long intronic regions that contain a large number of repetitive sequences. Moreover, introns of different genes contain very similar repetitive sequences, which is not conducive to accurate reporting of fusions. RNA-targeted sequencing for detecting fusion genes is highly sensitive and specific, and can detect fusion genes with low expression levels, thereby improving the sensitivity of detection. In addition, targeting specific RNA sequences can reduce false positive results and enhance the specificity of detection. It can also provide quantitative information on gene fusions, which is very important for understanding the role of gene fusions in disease development and treatment response. RNA-targeted sequencing detection can achieve high-throughput detection, and previously unknown gene fusion events can be discovered without prior knowledge of the information of the fusion partner gene.

[0004] In recent years, there have been a variety of RNA fusion detection panels, covering fusion gene combinations ranging from less than 100 to nearly a thousand. The evaluation of the detection performance of fusion detection panels is extremely important for the accuracy of clinical decision-making, the formulation of personalized treatment plans, the promotion of new drug development and clinical trials, the evaluation of disease prognosis, and the improvement of the credibility of detection technology. At present, the detection performance of fusion detection panels is mainly evaluated through commercial standards. However, commercial standards only contain dozens of fusion genes, and cannot comprehensively and objectively evaluate the detection performance of fusion detection panels for all fusion genes. Summary of the invention

[0005] In view of this, the present invention provides a method and device for evaluating the performance of a gene fusion detection panel, which are used to solve the problem that the performance of a gene fusion detection panel cannot be comprehensively and objectively evaluated.

[0006] To achieve the above objectives, the proposed solution is as follows: A gene fusion detection panel performance evaluation method, comprising: Based on the pre-constructed fusion gene transcript database, different types of known fusion gene single-stranded DNAs are synthesized to simulate unknown fusion gene combinations, wherein the fusion gene single-stranded DNA includes a T7 promoter at the 5' end, a fusion gene sequence, and a reverse amplification primer at the 3' end; Amplify the single-stranded DNA of the fusion gene and construct a sequencing library; The single-stranded DNA amplification product of the fusion gene is transcribed to construct a transcriptome library; Use the detection panel to be evaluated to capture the transcriptome library; Sequencing the captured transcripts to obtain sequencing data; Perform data processing on sequencing data; Determine whether the processed sequencing data has passed quality control; If passed, the target fusion detection is analyzed based on the processed sequencing data to obtain the detection performance of the panel to be evaluated for the fusion gene.

[0007] Preferably, the process of synthesizing different types of known fusion gene single-stranded DNA comprises: The fusion breakpoints of each known fusion gene were located at the 3' and 5' ends to simulate the state of the fusion gene transcripts; The fusion core gene and the partner gene were combined with fixed sequences to simulate the first type of unknown fusion gene; The non-hotspot exons of core genes were combined with randomly selected gene exons to simulate the second type of unknown fusion genes; Design of sex-involved gene transcripts.

[0008] Preferably, after amplifying the fusion gene single-stranded DNA, the method further comprises: The single-stranded DNA of the fusion gene in the sequencing library was analyzed based on standard bioinformatics analysis methods, and the number of supporting reads for each fusion gene was counted.

[0009] Preferably, the number of supporting reads for each fusion gene is counted, including: If the fusion gene and the target fusion gene sequence are completely consistent, it is determined as supporting Reads, where the target fusion gene sequence is a preset sequence.

[0010] Preferably, it also includes: Labels were added to the exon regions of the core genes and partner gene hotspots as detection controls.

[0011] Preferably, it also includes: The abundance of fusion gene transcripts in the transcriptome library was detected by high-throughput sequencing; ddPCR was used to absolutely quantify the copy number of the target gene in the transcriptome library to obtain the copy number of each fusion gene transcript.

[0012] Preferably, the process of processing the sequencing data includes: Remove the adapter sequences, low-quality base fragments, and ribosomal RNA in the sequencing data; Mark duplicate reads in sequencing data.

[0013] Preferably, the process of determining whether the processed sequencing data has passed quality control includes: Whether the sequencing data has passed quality control is determined based on the base quality value, housekeeping gene expression level and quality control gene expression level of the sequencing data.

[0014] A gene fusion detection panel performance evaluation device, comprising: A gene sequence storage unit is used to store fusion gene transcript data for synthesizing different types of known fusion gene single-stranded DNA based on a pre-constructed fusion gene transcript database to simulate unknown fusion gene combinations, wherein the fusion gene single-stranded DNA includes a T7 promoter at the 5' end, a fusion gene sequence, and a reverse amplification primer at the 3' end; amplifying the fusion gene single-stranded DNA to construct a sequencing library; transcribing the fusion gene single-stranded DNA amplification product to construct a transcriptome library; and capturing the transcriptome library using the detection panel to be evaluated; A sequencing unit, used to sequence the captured transcripts to obtain sequencing data; A data processing unit, used for processing the sequencing data; Quality control unit, used to determine whether the processed sequencing data has passed quality control; The fusion detection unit is used to analyze the target fusion detection situation based on the processed sequencing data after the sequencing data passes the quality control, and obtain the detection performance of the detection panel to be evaluated for the fusion gene.

[0015] It can be seen from the above technical solution that the present invention synthesizes different types of single-stranded DNA of known fusion genes based on a pre-constructed fusion gene transcript database to simulate unknown fusion gene combinations, so that the evaluation method of the present invention can not only evaluate the detection performance of the detection panel for known fusion genes, but also evaluate the detection performance of the detection panel for unknown fusion genes.

[0016] The present invention constructs a comprehensive fusion gene library, and the detection performance of the detection panel for each fusion gene can be accurately evaluated through bioinformatics analysis methods. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying creative work.

[0018] Figure 1 A flow chart of a gene fusion detection panel performance evaluation method provided in this embodiment; Figure 2a-2j Statistical graph of the number of reads supported by different types of fusion genes provided in this embodiment; Figure 3 A representative fusion gene transcript copy number statistical graph provided for this embodiment; Figure 4 A corresponding relationship diagram between the copy number of the fusion gene transcript provided in this embodiment and the gene sequencing result; Figure 5 A schematic diagram of the structure of a gene fusion detection panel performance evaluation device provided in this embodiment. DETAILED DESCRIPTION

[0019] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0020] First, combine Figure 1 A gene fusion detection panel performance evaluation method provided by the present invention is introduced. Figure 1 As shown, the process includes: Step S01, based on a pre-constructed fusion gene transcript database, synthesize different types of single-stranded DNA of known fusion genes to simulate unknown fusion gene combinations.

[0021] Specifically, in order to build a more comprehensive fusion gene transcript database, gene data are collected from known databases, such as NCCN, CSCO and other guidelines, as well as tumor fusion driver gene combinations related to tumor occurrence and development, diagnosis and typing included in tumor gene databases such as Catalogue of Somatic Mutations in Cancer (COSMIC) and The Cancer Genome Atlas Program (TCGA).

[0022] The gene sequence of the fusion gene transcript is stored in the fusion gene transcript database, and the known fusion gene single-stranded DNA can be synthesized based on the pre-constructed fusion gene transcript database. In order to better examine the detection ability of the panel to be evaluated for known and unknown fusion genes, the embodiment of the present invention not only synthesizes the known fusion gene, but also synthesizes the fusion gene through a fixed sequence to simulate the unknown fusion gene. The fusion gene single-stranded DNA includes a T7 promoter at the 5' end, a fusion gene sequence, and a reverse amplification primer at the 3' end.

[0023] The present invention simulates unknown fusion genes by synthesizing different types of fusion genes, thereby investigating the ability of different probes to capture unknown fusions. The process of synthesizing different types of fusion genes is as follows: The fusion breakpoints of each known fusion gene were located at the 3' and 5' ends to simulate the state of the fusion gene transcript. The synthetic product was amplified using specific primers designed based on T7 Primer and the 3' end. The primer sequences were: IVT-Rev-B: CACTGAGCCTCCACCTAGCCT; IVT-Fwd-T7: CCAAGCCTTCTAATACGACTCAC.

[0024] The fusion core gene and the partner gene were combined with fixed sequences respectively to simulate the first type of unknown fusion gene, and the ability of the core gene or partner gene probe to capture the unknown fusion gene was examined, wherein the fixed sequence was a gene sequence set according to demand.

[0025] The non-hotspot exons of core genes were combined with randomly selected gene exons to simulate the second type of unknown fusion genes and to examine the ability of core gene transcript probes to capture unknown fusion genes in non-hotspot regions.

[0026] The transcripts of sex-related genes were designed to evaluate the detection ability of the panel to be evaluated for housekeeping genes.

[0027] Step S02, amplifying the single-stranded DNA of the fusion gene to construct a sequencing library.

[0028] Specifically, PCR primers are used to amplify the synthetic products and construct a sequencing library. Single-stranded DNA is amplified and a sequencing library is constructed according to a standard library construction process.

[0029] Step S03, transcribing the single-stranded DNA amplification product of the fusion gene to construct a transcriptome library.

[0030] Specifically, the fusion gene transcripts are synthesized by in vitro transcription, the synthesized fusion gene single-stranded DNA amplification product is transcribed into RNA, the RNA is graded diluted and a transcriptome library is established.

[0031] Step S04: using the detection panel to be evaluated to capture the transcriptome library.

[0032] Specifically, in order to verify the capture performance of the detection panel to be evaluated for the fusion gene, a capture experiment was performed using the constructed transcriptome library. Hybridization capture was performed using the detection panel to be evaluated.

[0033] Step S05: Sequence the captured transcripts to obtain sequencing data.

[0034] Specifically, the captured transcripts are sequenced and analyzed by bioinformatics analysis methods, and if the transcript sequence is completely consistent with the target fusion gene sequence, it is determined to be a supporting read. The target fusion gene sequence is a preset gene sequence designed before synthesizing the fusion gene single-stranded DNA.

[0035] The detection of supporting reads for different types of fusion genes was counted separately. Each fusion gene detection required more than 2 supporting reads.

[0036] Step S06, performing data processing on the sequencing data.

[0037] Specifically, the software is used to remove the adapter sequences and low-quality base fragments in the sequencing data. At the same time, the sequencing data is aligned to the ribosomal RNA database to remove the ribosomal RNA in the sequencing data.

[0038] The processed sequencing data are aligned to the human reference genome, and duplicate reads in the sequencing data are marked.

[0039] Step S07, determining whether the processed sequencing data has passed quality control.

[0040] Specifically, whether the data passes the quality control is determined based on the base quality value of the sequencing data, the expression level of the housekeeping gene, and the expression level of the quality control gene. The quality control standards are shown in Table 1.

[0041]

[0042] If passed, execute the following step S08; Step S08, analyzing the detection of the target fusion based on the processed sequencing data to obtain the detection performance of the panel to be evaluated for the fusion gene.

[0043] Specifically, the fusion map and arriba software were used to detect gene fusions respectively, and the fusion genes detected by the two softwares were combined, and the final fusion genes were obtained through further filtering. Based on the final fusion genes, the detection performance of the panel to be evaluated was evaluated.

[0044] The embodiments of the present invention synthesize different types of single-stranded DNA of known fusion genes based on a pre-constructed fusion gene transcript database to simulate unknown fusion gene combinations, so that the evaluation method of the present invention can not only evaluate the detection performance of the detection panel for known fusion genes, but also evaluate the detection performance of the detection panel for unknown fusion genes.

[0045] The embodiment of the present invention constructs a comprehensive fusion gene library, and the detection performance of the detection panel for each fusion gene can be accurately evaluated through bioinformatics analysis methods.

[0046] In order to avoid the influence of the quality of the fusion gene single-stranded DNA and transcript on the evaluation accuracy of the detection panel, in step S02, after amplifying the fusion gene single-stranded DNA, the embodiment of the present invention may further perform the following steps: The integrity and copy number uniformity of the synthesized fusion gene single-stranded DNA sequence are detected by a high-throughput sequencing platform. The fusion gene single-stranded DNA in the sequencing library is analyzed based on standard bioinformatics analysis methods, and the number of supporting reads for each fusion gene is counted. If the fusion gene single-stranded DNA is completely consistent with the target fusion gene sequence, it will be recorded as a supporting read. Among them, the target fusion gene sequence is the preset gene sequence designed before synthesizing the fusion gene single-stranded DNA. That is, the fusion gene single-stranded DNA is synthesized according to the target fusion gene sequence. Therefore, when the sequence of the fusion gene single-stranded DNA is consistent with the target fusion gene sequence, it proves that the synthesized fusion gene single-stranded DNA is correct. If it is inconsistent, it proves that there is a problem in the synthesis process.

[0047] In order to avoid errors in the transcript sequence obtained by transcription, which may lead to errors in the subsequent analysis results, the following steps may be performed after constructing the transcriptome library in the embodiment of the present invention: The abundance of fusion gene transcripts in the transcriptome library was detected by high-throughput sequencing. The number of supporting reads in the fusion gene transcripts was detected to obtain the proportion of fusion gene transcripts.

[0048] ddPCR was used to absolutely quantify the target gene copy number in the transcriptome library to obtain the copy number of each fusion gene transcript. In order to determine the copy number of the fusion gene transcript, the Digital droplet PCR method was used to absolutely quantify the selected N representative gene transcripts, and then the copy number of each fusion gene transcript was evaluated based on the copy number of the representative gene transcript and the sequencing results.

[0049] The embodiment of the present invention verifies the sequence of the transcript, which can further ensure the accuracy of the evaluation results of the detection panel.

[0050] Considering the possible problems in the methodology of the design process of the test panel to be evaluated, the embodiment of the present invention also adds tags in the exon region of the core gene and the partner gene hotspot region as a detection control. If the test panel to be evaluated cannot capture the wild gene, it proves that the design of the test panel to be evaluated is unreasonable in methodology.

[0051] The embodiment of the present invention sets a detection control group to verify the methodological rationality of the detection panel, thereby avoiding inaccurate data analysis results caused by the unreasonable detection panel itself.

[0052] Next, the present invention verifies the feasibility of the provided gene fusion detection panel performance evaluation method, and synthesizes different types of fusion gene single-stranded DNA based on a pre-constructed fusion gene transcript database, wherein the synthesis length of the fusion gene single-stranded DNA is 232nt. Three repeat groups are designed for each fusion gene, wherein the structures of different types of fusion genes are shown in Table 2, the gene structures of known fusion genes are shown in the first and second rows of Table 2, the first type of unknown fusion genes are shown in the second and third rows of Table 2, and the second type of unknown fusion genes are shown in the seventh and eighth rows of Table 2. The numbers in brackets are the base numbers of the gene fragments.

[0053]

[0054] Single-stranded DNA amplification was performed according to the AMPLIFYING TWIST OLIGO POOLS method, using KAPA HiFiHotStart DNA Polymerase, with 12 cycles, and a sequencing library was constructed based on the amplified product. The KAPA DNA HyperPrep / KK8505 kit was used to construct a sequencing library according to the standard library construction process, with 4 cycles.

[0055] After constructing the sequencing library, the integrity and copy number uniformity of the synthetic fusion gene single-stranded DNA sequence were detected by the BGI-T7 high-throughput sequencing platform. The data volume was 2M Reads. The theoretical coverage depth of each fusion gene single-stranded DNA was 600X. Standard bioinformatics analysis methods were used for analysis. If 100% was consistent with the target fusion gene sequence, it would be recorded as a supporting Read. The statistical results of each type of fusion gene are as follows: Figure 2a-2j As shown, the number of supporting reads for each fusion gene was counted, and the analysis results are shown in Table 3. Figure 2a-2j It can be seen that the supporting reads of 3376 fusion genes are normally distributed, the supporting reads of 3363 fusion genes are higher than the Average-2SD value; at least one supporting read was detected for 3373 fusion genes; and no supporting reads were detected for 3 fusion genes.

[0056]

[0057] The fusion gene transcript was synthesized by in vitro transcription, and the expected transcript length was 200 nt. The synthesized fusion gene single-stranded DNA amplification product was subjected to agarose gel electrophoresis to cut the expected size of the nucleic acid fragment. Then, it was purified using QIAquickPCR & Gel Cleanup Kit (Cat. No. / ID: 28506) to obtain double-stranded DNA; then the MEGAshortscript™ T7 transcription kit of Thermo Company was used for transcription, and the experimental method was referred to the instruction manual. The transcript product was quantified by Qubit, 1ng of transcript was diluted 2500 times, 5000 times and 10000 times, 1ul was taken and spiked with 50ng of the interrupted negative RNA reference (NC12878), and the copy number of the fusion gene was expected to be 400Copy / 50ng, 200Copy / 50ng and 100Copy / 50ng, and the transcriptome library was constructed using the Abclonal transcriptome library construction kit.

[0058] After constructing the transcriptome library, three intra-group replicates were set up, and the abundance of the fusion gene transcripts in the transcriptome library was detected by high-throughput sequencing. The abundance of different types of transcripts is shown in Table 4, and the analysis results are shown in Table 5. Each replicate has 0.35M, 0.55M, and 0.45M PE Reads that can completely match the fusion gene, and the proportion of detected fusion gene transcripts is more than 90%.

[0059]

[0060]

[0061] In order to determine the copy number of the fusion gene transcript, the Digital droplet PCR method was used to absolutely quantify the transcripts of 10 representative genes. The transcription products were diluted to 2*10^-6 times and absolutely quantified according to the instructions of the kit. The average copy value of the 10 representative gene transcripts after dilution was obtained as follows: Figure 3 Then, according to Figure 4 The relationship between the copy number of the 10 representative gene transcripts and the sequencing results (supporting reads number) is shown to evaluate the copy number of each fusion gene transcript, and the average copy number of the original sample RNA is 1.4*10^6.

[0062] In order to verify the Panel's capture performance for fusion genes, the fusion gene transcript library described above was used for capture experiments. A panel containing 437 fusion genes was used for hybridization capture, and the panel contained all genes in the transcript library. Two technical replicates were set for each capture, and the amount of sequencing data for each capture was 80M Reads; bioinformatics analysis was used to analyze the data, and those that were completely consistent with the target fusion gene were determined to be supporting Reads. The detection of supporting Reads for different types of fusion genes was counted separately, and each fusion detection required more than 2 supporting Reads.

[0063] Trimmomatic v0.36 software was used to remove adapter sequences and low-quality base fragments in the sequencing data, and then bowtie2 was used to align the data to the ribosomal RNA database to remove ribosomal RNA in the data.

[0064] The processed sequencing data were aligned to the hg19 (GRCh37) human reference genome using STAR software, and then duplicate reads were marked using picard software to generate the sortAligned.sortedByCoord.out.mkdup.bam file.

[0065] Whether the sequencing data has passed quality control is determined based on the base quality value, housekeeping gene expression level, and quality control gene expression level of the processed sequencing data.

[0066] Fusionmap and arriba were used to detect fusions respectively, and the union of the fusions detected by the two softwares was taken, and the final fusion was obtained through further filtering. The detection rates of different types of fusion genes by the statistical detection panel are shown in Table 6.

[0067]

[0068] According to the contents of Table 4, in the 400copy test group, the average detection rate of known fusion genes was higher than 90%; for unknown fusions composed of fixed sequences, the detection rate was also about 90%. The performance of capturing unknown fusions by single-end binding is similar to that of capturing known fusions. It is significantly higher than unknown fusions in non-hotspot regions and wild-type transcripts, indicating that specific probes designed near breakpoints have a better benefit for fusion detection. For unknown fusions in non-hotspot regions, since no special probes for fusion genes were designed, only transcript probes were covered, but 40% of fusion genes could also be detected.

[0069] The following is a description of a gene fusion detection panel performance evaluation device provided in an embodiment of the present invention. The gene fusion detection panel performance evaluation device described below and the gene fusion detection panel performance evaluation method described above can be referenced to each other.

[0070] First combine Figure 5 , introduce the performance evaluation device of gene fusion detection panel, such as Figure 5 As shown, the gene fusion detection panel performance evaluation device may include: The gene sequence storage unit 100 is used to store fusion gene transcript data for synthesizing different types of known fusion gene single-stranded DNAs based on a pre-constructed fusion gene transcript database to simulate unknown fusion gene combinations, wherein the fusion gene single-stranded DNA includes a T7 promoter at the 5' end, a fusion gene sequence, and a reverse amplification primer at the 3' end; amplifying the fusion gene single-stranded DNA to construct a sequencing library; transcribing the fusion gene single-stranded DNA amplification product to construct a transcriptome library; and capturing the transcriptome library using the detection panel to be evaluated; A sequencing unit 200 is used to sequence the captured transcripts to obtain sequencing data; A data processing unit 300 is used to process the sequencing data; The quality control unit 400 is used to determine whether the processed sequencing data has passed the quality control; The fusion detection unit 500 is used to analyze the target fusion detection situation based on the processed sequencing data after the sequencing data passes the quality control, and obtain the detection performance of the detection panel to be evaluated for the fusion gene.

[0071] Finally, it should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprise a ..." do not exclude the presence of other identical elements in the process, method, article or device including the elements.

[0072] The various embodiments in this specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the various embodiments can be referenced to each other.

[0073] The above description of the disclosed embodiments enables one skilled in the art to implement or use the present invention. Various modifications to these embodiments will be apparent to one skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but rather to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for evaluating the performance of a gene fusion detection panel, characterized in that: include: Based on the pre-constructed fusion gene transcript database, different types of known fusion gene single-stranded DNAs are synthesized to simulate unknown fusion gene combinations, wherein the fusion gene single-stranded DNA includes a T7 promoter at the 5' end, a fusion gene sequence, and a reverse amplification primer at the 3' end; Amplify the single-stranded DNA of the fusion gene and construct a sequencing library; The single-stranded DNA amplification product of the fusion gene is transcribed to construct a transcriptome library; Use the detection panel to be evaluated to capture the transcriptome library; Sequencing the captured transcripts to obtain sequencing data; Perform data processing on sequencing data; Determine whether the processed sequencing data has passed quality control; If passed, the target fusion detection is analyzed based on the processed sequencing data to obtain the detection performance of the panel to be evaluated for the fusion gene.

2. The gene fusion detection panel performance evaluation method according to claim 1, characterized in that: The process of synthesizing single-stranded DNA of different types of known fusion genes, including: The fusion breakpoints of each known fusion gene were located at the 3' and 5' ends to simulate the state of the fusion gene transcripts; The fusion core gene and the partner gene were combined with fixed sequences to simulate the first type of unknown fusion gene; The non-hotspot exons of core genes were combined with randomly selected gene exons to simulate the second type of unknown fusion genes; Design of sex-involved gene transcripts.

3. The gene fusion detection panel performance evaluation method according to claim 1, characterized in that: After amplifying the fusion gene single-stranded DNA, the following steps are also included: The single-stranded DNA of the fusion gene in the sequencing library was analyzed based on standard bioinformatics analysis methods, and the number of supporting reads for each fusion gene was counted.

4. The gene fusion detection panel performance evaluation method according to claim 3, characterized in that: Count the number of supporting reads for each fusion gene, including: If the fusion gene and the target fusion gene sequence are completely consistent, it is determined as supporting Reads, where the target fusion gene sequence is a preset sequence.

5. The gene fusion detection panel performance evaluation method according to claim 1, characterized in that: Also includes: Labels were added to the exon regions of the core genes and partner gene hotspots as detection controls.

6. The gene fusion detection panel performance evaluation method according to claim 1, characterized in that: Also includes: The abundance of fusion gene transcripts in the transcriptome library was detected by high-throughput sequencing; ddPCR was used to absolutely quantify the copy number of the target gene in the transcriptome library to obtain the copy number of each fusion gene transcript.

7. The method for evaluating the performance of a gene fusion detection panel according to any one of claims 1 to 6, characterized in that: The process of data processing for sequencing data includes: Remove the adapter sequences, low-quality base fragments, and ribosomal RNA in the sequencing data; Mark duplicate reads in sequencing data.

8. The gene fusion detection panel performance evaluation method according to claim 7, characterized in that: The process of determining whether the processed sequencing data has passed quality control includes: Whether the sequencing data has passed quality control is determined based on the base quality value, housekeeping gene expression level and quality control gene expression level of the sequencing data.

9. A gene fusion detection panel performance evaluation device, characterized in that: include: A gene sequence storage unit is used to store fusion gene transcript data for synthesizing different types of known fusion gene single-stranded DNA based on a pre-constructed fusion gene transcript database to simulate unknown fusion gene combinations, wherein the fusion gene single-stranded DNA includes a T7 promoter at the 5' end, a fusion gene sequence, and a reverse amplification primer at the 3' end; amplifying the fusion gene single-stranded DNA to construct a sequencing library; transcribing the fusion gene single-stranded DNA amplification product to construct a transcriptome library; and capturing the transcriptome library using the detection panel to be evaluated; A sequencing unit, used to sequence the captured transcripts to obtain sequencing data; A data processing unit, used for processing the sequencing data; Quality control unit, used to determine whether the processed sequencing data has passed quality control; The fusion detection unit is used to analyze the target fusion detection situation based on the processed sequencing data after the sequencing data passes the quality control, and obtain the detection performance of the detection panel to be evaluated for the fusion gene.

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