A method and system for transmitting gene detection results of non-small cell lung cancer

Abstract

The present invention relates to the technical field of data transmission, and in particular to a method and system for transmitting the results of gene detection of non-small cell lung cancer. The method comprises: obtaining a target gene sequence, dividing the target gene sequence into subsequence segments with different preset lengths, and screening the first subsequence segment by using the size relationship between the repetition degree of a single subsequence segment of each preset length and the repetition degree of all subsequence segments; screening the target subsequence segment by comprehensively considering the repetition conditions between the first subsequence segments of different lengths and the corresponding repetition degrees; constructing a dictionary using the target subsequence segment, and compressing and transmitting the target gene sequence based on the dictionary. The present invention improves the transmission efficiency of the results of gene detection of non-small cell lung cancer.

Description

Technical Field

[0001] The present invention relates to the technical field of data transmission, and in particular to a method and system for transmitting gene detection results of non-small cell lung cancer. Background Art

[0002] Non-small cell lung cancer ctDNA, or circulating tumor DNA, refers to DNA fragments released by tumor cells into the blood circulation system. In solid tumors such as non-small cell lung cancer, ctDNA carries genetic mutation information of the tumor, such as point mutations, gene amplification, gene deletion, gene rearrangement, etc. Therefore, ctDNA gene testing through blood samples can detect lesions in tumor cells. The biological information of the genetic test results contains a large number of biological data indicators, with a large amount of data content and a large amount of redundant information, which makes the transmission of the test results slow.

[0003] The data of non-small cell lung cancer gene detection is large, involving a large number of biological indicators and a lot of data content. Because it is the result of medical detection through professional medical equipment, the related genes detected are relatively important. The existing transmission method is to compress the data and reduce the data capacity to transmit the data to improve the data transmission efficiency. However, because the genes of non-small cell lung cancer are complex and changeable, there are many types of data in the gene detection results, and the amount of test results is large. When the traditional compression algorithm is used to construct the dictionary, the dictionary encoding amount is large, the compression efficiency is reduced, the amount of information transmitted is large, and the transmission efficiency of non-small cell lung cancer gene detection data is low. Summary of the invention

[0004] In order to solve the problem of low transmission efficiency in the existing method for transmitting non-small cell lung cancer gene detection data, the purpose of the present invention is to provide a method and system for transmitting non-small cell lung cancer gene detection results. The technical scheme adopted is as follows:

[0005] In a first aspect, the present invention provides a method for transmitting a non-small cell lung cancer gene detection result, the method comprising the following steps:

[0006] Obtain the non-small cell lung cancer gene detection sequence of the target person;

[0007] The target gene sequence is divided into subsequence segments with different preset lengths respectively, wherein the target gene sequence is extracted from the gene detection sequence based on the arrangement and combination characteristics of base pairs; the repetition degree of each subsequence segment is obtained according to the occurrence of each subsequence segment in the target gene sequence; and the first subsequence segment is selected by using the size relationship between the repetition degree of a single subsequence segment of each preset length and the repetition degree of all subsequence segments;

[0008] The target subsequence segments are screened based on the repetition conditions between the first subsequence segments of different lengths and the corresponding repetition degrees; a dictionary is constructed using the target subsequence segments, and the target gene sequence is compressed and transmitted based on the dictionary.

[0009] Preferably, the acquisition of the target gene sequence includes:

[0010] Extract all bases at odd positions or all bases at even positions in the non-small cell lung cancer gene detection sequence of the target person to form a target gene sequence.

[0011] Preferably, obtaining the repetitiveness of each subsequence segment according to the occurrence of each subsequence segment in the target gene sequence includes:

[0012] The number of times the candidate subsequence segment appears in the target gene sequence is counted; the number is used as the repetition degree of the candidate subsequence segment; the candidate subsequence segment is any subsequence segment among all subsequence segments of all preset lengths.

[0013] Preferably, the step of selecting the first subsequence segment by using the magnitude relationship between the repetitiveness of a single subsequence segment of each preset length and the repetitiveness of all subsequence segments comprises:

[0014] For any preset length:

[0015] Calculate the average repetitiveness of all subsequence segments of the preset length;

[0016] For any subsequence segment of the preset length, the difference between the repetition degree of the subsequence segment and the average repetition degree is calculated, and based on the difference, it is determined whether the subsequence segment is the first subsequence segment.

[0017] Preferably, judging whether the subsequence segment is the first subsequence segment based on the difference includes:

[0018] If the difference is greater than a preset difference threshold, the subsequence segment is determined to be the first subsequence segment; the preset difference threshold is greater than or equal to 0.

[0019] Preferably, the step of comprehensively considering the repetition between the first subsequence segments of different lengths and the corresponding repetition degrees to screen the target subsequence segment comprises:

[0020] Calculating a first ratio between the repetitiveness of a reference subsequence segment corresponding to the subsequence segment to be analyzed and the repetitiveness of the subsequence segment to be analyzed; obtaining a retention index of the subsequence segment to be analyzed according to a difference between the repetitiveness of the subsequence segment to be analyzed and the reference subsequence segment to be analyzed, and all first ratios corresponding to the subsequence segment to be analyzed; the subsequence segment to be analyzed is any first subsequence segment;

[0021] The reference subsequence segment is the first subsequence segment of all first subsequence segments that contains the subsequence segment to be analyzed and has a length greater than the subsequence segment to be analyzed;

[0022] Based on the retention index, it is determined whether the subsequence segment to be analyzed is a target subsequence segment; the subsequence segment to be analyzed is any first subsequence segment.

[0023] Preferably, obtaining the retention index of the subsequence segment to be analyzed according to the difference between the repetitiveness of the subsequence segment to be analyzed and its corresponding reference subsequence segment, and all first ratios corresponding to the subsequence segment to be analyzed, comprises:

[0024] Calculate the overall difference between the repetitiveness of the subsequence segment to be analyzed and all corresponding reference subsequence segments;

[0025] Calculate the average of all first ratios corresponding to the subsequence segment to be analyzed;

[0026] The normalized result of the difference between the overall difference and the average value is determined as the retention index of the subsequence segment to be analyzed.

[0027] Preferably, judging whether the subsequence segment to be analyzed is a target subsequence segment based on the retention index includes:

[0028] If the retention index is greater than a preset retention threshold, the subsequence segment to be analyzed is taken as the target subsequence segment.

[0029] Preferably, the LZW algorithm is used to compress the gene detection sequence.

[0030] In a second aspect, the present invention provides a system for transmitting gene detection results of non-small cell lung cancer, the system comprising:

[0031] A data collection module, used to obtain the non-small cell lung cancer gene detection sequence of the target person;

[0032] A first subsequence segment screening module is used to divide the target gene sequence into subsequence segments with different preset lengths, wherein the target gene sequence is extracted from the gene detection sequence based on the arrangement and combination characteristics of base pairs; obtain the repetition degree of each subsequence segment according to the occurrence of each subsequence segment in the target gene sequence; and screen the first subsequence segment by using the size relationship between the repetition degree of a single subsequence segment of each preset length and the repetition degree of all subsequence segments;

[0033] The data transmission module is used to comprehensively analyze the repetition between the first subsequence segments of different lengths and the corresponding repetition degrees to screen the target subsequence segments; construct a dictionary using the target subsequence segments, and compress and transmit the target gene sequence based on the dictionary.

[0034] The present invention has at least the following beneficial effects:

[0035] The present invention first performs non-small cell lung cancer gene testing on the target person to obtain a gene testing sequence, and then extracts the target gene sequence from the gene testing sequence according to the arrangement and combination characteristics of the base pairs. While retaining the important information of the original gene testing sequence, the overall data volume is reduced by half, so that the compression transmission efficiency can be improved. Further, the target gene sequence is divided multiple times with different preset lengths to obtain subsequence segments with different preset lengths, and the occurrence of each subsequence segment in the target gene sequence is analyzed to obtain the repetition of each subsequence segment. The repetition of a single subsequence segment of each preset length is compared with the repetition of all subsequence segments to screen out the target gene sequence. The first subsequence segment has a high selectivity for being included in the dictionary. The repetition between the first subsequence segments of different lengths and the corresponding repetition degree are comprehensively considered, and the target subsequence segment is screened from the first subsequence segment. The target subsequence segment is used to construct the dictionary, and then the target gene sequence is compressed and transmitted. The method provided by the present invention performs differential compression according to different gene fragments, ensures the compression rate, and can also better transmit key DNA data information, thereby improving the transmission efficiency of non-small cell lung cancer gene detection results. By safely and quickly transmitting non-small cell lung cancer gene detection results, clinicians can obtain patients' gene variation information in a timely manner and provide patients with personalized treatment plans. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] In order to more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the drawings required for use in the embodiments or the prior art descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0037] Figure 1 A flow chart of a method for transmitting gene detection results of non-small cell lung cancer provided by an embodiment of the present invention;

[0038] Figure 2 This is a structural block diagram of a system for transmitting gene detection results of non-small cell lung cancer provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0039] In order to further illustrate the technical means and effects adopted by the present invention to achieve the predetermined purpose of the invention, a method and system for transmitting gene detection results of non-small cell lung cancer proposed by the present invention are described in detail below in conjunction with the accompanying drawings and preferred embodiments.

[0040] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.

[0041] The following is a detailed description of a method and system for transmitting gene detection results of non-small cell lung cancer provided by the present invention in conjunction with the accompanying drawings.

[0042] An embodiment of a method for transmitting the results of non-small cell lung cancer gene detection:

[0043] This embodiment proposes a method for transmitting the results of non-small cell lung cancer gene detection, such as Figure 1 As shown, a method for transmitting a non-small cell lung cancer gene detection result in this embodiment includes the following steps:

[0044] Step S1, obtaining the non-small cell lung cancer gene detection sequence of the target person.

[0045] First, the target person is tested for non-small cell lung cancer genes. The raw data generated by high-throughput DNA sequencing technology (such as Illumina, PacBio, Oxford Nanopore, etc.) is usually stored in Fastq format, which contains the sequence information and quality score of the sequencing reads. Each read represents a short fragment captured from the sample DNA, and the length is usually between tens and hundreds of bases. FASTQ files are the basis for subsequent bioinformatics analysis. In biological information, the FASTQ format is a format commonly used to represent nucleotide sequences or protein sequences. A sequence in FASTQ format usually starts with ">", followed by the sequence name, and then the sequence itself. The data in this format of FASTQ files records the position of each read on the genome and other related information. In this embodiment, a sequence composed of bases is first extracted and recorded as a gene detection sequence, which will be analyzed and transmitted later.

[0046] So far, the non-small cell lung cancer gene detection sequence of the target person has been obtained by using the method provided in this embodiment.

[0047] Step S2, dividing the target gene sequence into subsequence segments with different preset lengths, wherein the target gene sequence is extracted from the gene detection sequence based on the arrangement and combination characteristics of base pairs; obtaining the repetition degree of each subsequence segment according to the occurrence of each subsequence segment in the target gene sequence; and selecting the first subsequence segment by using the size relationship between the repetition degree of a single subsequence segment of each preset length and the repetition degree of all subsequence segments.

[0048] The gene detection sequence obtained by DNA sequencing technology is a series of nucleotide sequences, and its nucleotide sequence is composed of the smallest unit of base pairs. The free arrangement and combination of several base pairs form different gene sequences. Each different gene has a certain stability and universality, and these genes will be repeated many times in the entire nucleotide sequence. Therefore, when the gene detection sequence is obtained and compressed for transmission, the specific gene fragment can be first determined according to the characteristics of its gene stability, and the dictionary is constructed based on this gene fragment, which greatly improves the compression efficiency.

[0049] The gene detection sequence is composed of many base pairs, among which some base pairs arranged in a specific order have a certain stability, that is, the arrangement order of this segment of base pairs is stable in the entire nucleotide sequence and appears many times, indicating that this segment of base pairs has a certain stability in arrangement and combination. At the same time, because there are only 4 types of base pairs in the nucleotide sequence, and they always appear in pairs, namely AT, TA, CG, GC, among which A represents adenine, T represents thymine, C represents cytosine, and G represents guanine, therefore, through the analysis of the arrangement rules of the base pairs in the nucleotide sequence, there will always be a base sequence with a certain stable arrangement. Based on this feature, according to the arrangement and combination characteristics of the base pairs, the stable arrangement and combination of the base pairs is determined, that is, the target gene sequence is extracted from the non-small cell lung cancer gene detection sequence of the target person.

[0050] Specifically, for the gene detection sequence, all bases at odd positions in the gene detection sequence are extracted in order, and the target gene sequence is constructed in the order of extraction, that is, the first base, the third base, the fifth base, the seventh base in the gene detection sequence are extracted, and so on, and all the extracted bases constitute the target gene sequence; as another embodiment, all bases at even positions in the gene detection sequence can also be extracted in order, and the target gene sequence is constructed in the order of extraction, that is, the second base, the fourth base, the sixth base, the eighth base in the gene detection sequence are extracted, and so on, and all the extracted bases constitute the target gene sequence. The target gene sequence extracted by the above method retains the important information of the original gene detection sequence while reducing the overall data volume by half, and the efficiency of subsequent compression and transmission can be improved.

[0051] Furthermore, a plurality of different preset lengths are set, and each preset length is used to divide the target gene sequence. In this embodiment, the preset lengths are set to 2, 3, 4, 5, ..., , where N represents the number of bases in the target gene sequence, Indicates the rounding down symbol. For any preset length, the target gene sequence is divided into multiple subsequence segments of the preset length, that is, the number of bases in each subsequence segment of the preset length is the preset length. It should be noted that when the target gene sequence is divided by the preset length, the number of bases in the last subsequence segment may be less than the preset length. In this case, the last subsequence segment is still regarded as a subsequence segment of the preset length. In specific applications, the implementer can set different preset lengths according to specific circumstances.

[0052] The target gene sequence was divided multiple times using the above method to obtain multiple subsequence segments of each preset length.

[0053] Next, any subsequence segment is used as an example for explanation, and the method provided in this embodiment can be used to process other subsequence segments. Specifically, any subsequence segment among all subsequence segments of all preset lengths is recorded as a candidate subsequence segment. The more times the candidate subsequence segment appears in the target gene sequence, the higher the repetition rate of the candidate subsequence segment in the target gene sequence. Therefore, the number of times the candidate subsequence segment appears in the target gene sequence is counted; the number is used as the repetition degree of the candidate subsequence segment. Using this method, the repetition degree of each subsequence segment can be obtained.

[0054] For any preset length:

[0055] According to the repetition of each subsequence segment of the preset length, the average repetition of all subsequence segments of the preset length is calculated. For any subsequence segment of the preset length, the difference between the repetition of the subsequence segment and the average repetition is calculated. The larger the difference, the more repetitions of the subsequence segment in the target gene sequence is than the average repetitions of all subsequence segments of the preset length in the target gene sequence, and the subsequence segment has a higher selectivity, that is, the selectivity of the subsequence segment as a benchmark for inclusion in the dictionary is higher. Therefore, if the difference is greater than the preset difference threshold, the subsequence segment is determined to be the first subsequence segment; if the difference is less than or equal to the preset difference threshold, the subsequence segment is determined not to be the first subsequence segment; the preset difference threshold is greater than or equal to 0. In this embodiment, the preset difference threshold is 0. In specific applications, the implementer can set it according to specific circumstances.

[0056] So far, the above method provided by this embodiment can be used to screen out multiple first subsequence segments from all subsequence segments.

[0057] Step S3, comprehensively considering the repetition between the first subsequence segments of different lengths and the corresponding repetition degrees, screening the target subsequence segments; constructing a dictionary using the target subsequence segments, and compressing and transmitting the target gene sequence based on the dictionary.

[0058] In step S2, a plurality of first subsequence segments are screened out, the number of first subsequence segments is relatively large, and there are cases where shorter first subsequence segments are included in longer first subsequence segments, such as: if the first subsequence segment With the first subsequence segment The options are all higher, and the first subsequence segment Contained in the first subsequence segment In order to reduce the capacity of the dictionary, we need to discuss the different situations. The repetition degree is large, which is different from the first subsequence segment The repetition degree is similar, indicating that the first subsequence segment Contains a large number of first subsequence segments , that is, when The greater probability of occurrence is For the combination, consider The first subsequence segment of the combination is selected; if the first subsequence segment The repetition is small, and the first subsequence segment The repetition degree of the first subsequence segment is It also appears many times in other combinations. The combination appears more scattered, for the first subsequence segment The combination is retained.

[0059] A first subsequence segment is taken as an example for description below, and other first subsequence segments can be processed by the method provided in this embodiment.

[0060] Specifically, any first subsequence segment is recorded as the subsequence segment to be analyzed, and all first subsequence segments that contain the subsequence segment to be analyzed and whose length is greater than the subsequence segment to be analyzed are taken as reference subsequence segments corresponding to the subsequence segment to be analyzed. For example, if the first subsequence segments are , , , , , for one of the first subsequence segments ,because The first subsequence segment is included , The first subsequence segment is not included , The first subsequence segment is included , The first subsequence segment is not included , so the first subsequence segment The corresponding reference subsequence segment is and .

[0061] Next, a first ratio between the repetitiveness of the reference subsequence segment corresponding to the subsequence segment to be analyzed and the repetitiveness of the subsequence segment to be analyzed is calculated; a retention index of the subsequence segment to be analyzed is obtained according to the difference between the repetitiveness of the subsequence segment to be analyzed and the reference subsequence segment to be analyzed, and all the first ratios corresponding to the subsequence segment to be analyzed. Specifically, the overall difference between the repetitiveness of the subsequence segment to be analyzed and all the reference subsequence segments to be analyzed is calculated; an average value of all the first ratios corresponding to the subsequence segment to be analyzed is calculated; and a normalized result of the difference between the overall difference and the average value is determined as the retention index of the subsequence segment to be analyzed.

[0062] In this embodiment, a specific calculation formula for the retention index is given, and the retention index of the subsequence segment to be analyzed can be expressed as:

[0063]

[0064] Where W represents the retention index of the subsequence segment to be analyzed, Z represents the number of reference subsequence segments corresponding to the subsequence segment to be analyzed, Indicates the repetitiveness of the zth reference subsequence segment corresponding to the subsequence segment to be analyzed, Indicates the repetitiveness of the subsequence segment to be analyzed, represents the normalization function, Indicates the absolute value sign.

[0065] It is used to characterize the difference between the repetitiveness of the subsequence segment to be analyzed and the repetitiveness of the zth reference subsequence segment corresponding to the subsequence segment to be analyzed. The smaller the difference between the repetitiveness of the subsequence segment to be analyzed and the repetitiveness of the zth reference subsequence segment corresponding to the subsequence segment to be analyzed, the The closer the value of is to 1, The closer it is to 0, the less likely the subsequence segment to be analyzed should be retained; represents the first ratio between the repetitiveness of the zth reference subsequence segment corresponding to the subsequence segment to be analyzed and the repetitiveness of the subsequence segment to be analyzed, It represents the average value of all first ratios corresponding to the subsequence segment to be analyzed. The smaller the average value is, the more likely the subsequence segment to be analyzed should be retained, that is, the larger the retention index is.

[0066] By adopting the above method, the retention index of the first subsequence segment can be obtained. It should be noted that: for the first subsequence segment without a reference subsequence segment, its corresponding retention index is not calculated, that is, such first subsequence segment does not participate in the screening of subsequent target subsequence segments.

[0067] If the retention index of the first subsequence segment is greater than the preset retention threshold, it is used as the target subsequence segment; if the retention index of the first subsequence segment is less than or equal to the preset retention threshold, it is not used as the target subsequence segment. In this embodiment, the preset retention threshold is 0.5, and in specific applications, the implementer can set it according to specific circumstances.

[0068] So far, multiple target subsequence segments have been screened out from the first subsequence segment using the above method. The purpose of this step is to merge the shorter base sequence combinations in order to simplify the dictionary fields when there are more and more concentrated shorter base sequence combinations in the longer base sequence. This can not only simplify the dictionary, but also better compress the data and improve the compression efficiency.

[0069] After the target subsequence segment is screened, the gene detection sequence is compressed using the lossless compression (Lempel-Ziv-Welch Encoding, LZW) algorithm, that is, the dictionary is constructed using the screened target subsequence segment, and then the gene detection sequence is compressed. Finally, the compressed data is transmitted using the SSL / TLS protocol, VPN technology, etc. to ensure the confidentiality and integrity of the data during transmission. The construction of the dictionary and the LZW algorithm are prior arts and will not be described in detail here. The decompression process is reversely corresponding to the encryption process, and reverse decompression is performed according to the result of the compressed characters. During decompression, the system reads the compressed file and converts the code back to the original character data according to the coding table. Specifically, the system first reads the coding table stored in the compressed file. This coding table is composed of a dynamic dictionary formed during the compression process and a selected base sequence dictionary. According to the coding table, the system reads the coded data in the compressed file and converts it back to the original character data; if the code exists in the coding table, the corresponding character is directly output; if the code is not in the table, the prefix and the current character need to be combined into a new string, and it is added to the coding table, and the combination of the prefix and the current character is output at the same time. At the same time, base replacement is performed at the replacement position. When the maximum value of the coding table is reached, it is reset to continue processing subsequent data, and eventually the target gene sequence can be restored. Finally, based on the correspondence principle of base pairs, the non-small cell lung cancer gene detection sequence of the target person can be obtained, achieving the effect of lossless compression.

[0070] So far, the transmission process of the non-small cell lung cancer gene detection result has been completed by using the method provided in this embodiment.

[0071] In this embodiment, a non-small cell lung cancer gene test is first performed on the target person to obtain a gene test sequence, and then a target gene sequence is extracted from the gene test sequence according to the arrangement and combination characteristics of base pairs. While retaining important information of the original gene test sequence, the overall data volume is reduced by half, so that the compression transmission efficiency can be improved. Furthermore, the target gene sequence is divided multiple times with different preset lengths to obtain subsequence segments with different preset lengths, and the occurrence of each subsequence segment in the target gene sequence is analyzed to obtain the repetition of each subsequence segment. The repetition of a single subsequence segment of each preset length is compared with the repetition of all subsequence segments to screen out. The first subsequence segment has a high selectivity for being included in the dictionary. The repetition between the first subsequence segments of different lengths and the corresponding repetition degree are comprehensively considered, and the target subsequence segment is selected from the first subsequence segment. The target subsequence segment is used to construct the dictionary, and then the target gene sequence is compressed and transmitted. The method provided in this embodiment performs differential compression according to different gene fragments, ensures the compression rate, and can also better transmit key DNA data information, thereby improving the transmission efficiency of non-small cell lung cancer gene detection results. By safely and quickly transmitting non-small cell lung cancer gene detection results, clinicians can obtain patients' gene variation information in a timely manner and provide patients with personalized treatment plans.

[0072] An embodiment of a transmission system for non-small cell lung cancer gene detection results:

[0073] See also Figure 2 , which shows a structural block diagram of a transmission system for non-small cell lung cancer gene detection results provided by an embodiment of the present invention. The system may include a data acquisition module, a first subsequence segment screening module and a data transmission module.

[0074] Among them, the data acquisition module is used to obtain the non-small cell lung cancer gene detection sequence of the target person;

[0075] A first subsequence segment screening module is used to divide the target gene sequence into subsequence segments with different preset lengths, wherein the target gene sequence is extracted from the gene detection sequence based on the arrangement and combination characteristics of base pairs; obtain the repetition degree of each subsequence segment according to the occurrence of each subsequence segment in the target gene sequence; and screen the first subsequence segment by using the size relationship between the repetition degree of a single subsequence segment of each preset length and the repetition degree of all subsequence segments;

[0076] The data transmission module is used to comprehensively analyze the repetition between the first subsequence segments of different lengths and the corresponding repetition degrees to screen the target subsequence segments; construct a dictionary using the target subsequence segments, and compress and transmit the target gene sequence based on the dictionary.

[0077] It should be understood that Figure 2 The structural block diagram of the transmission system of the non-small cell lung cancer gene detection result shown and its modules can be implemented in various ways. For example, in some embodiments, the system and its modules can be implemented by hardware, software, or a combination of software and hardware. Among them, the hardware part can be implemented using dedicated logic; the software part can be stored in a memory and executed by an appropriate instruction execution system, such as a microprocessor or a dedicated design hardware. Those skilled in the art can understand that the above-mentioned methods and systems can be implemented using computer executable instructions and / or included in processor control codes, such as carrier media such as disks, CDs or DVD-ROMs, programmable memories such as read-only memories (firmware), or data carriers such as optical or electronic signal carriers. Such codes are provided on. The system and its modules of this specification can not only be implemented by hardware circuits such as ultra-large-scale integrated circuits or gate arrays, semiconductors such as logic chips, transistors, etc., or programmable hardware devices such as field programmable gate arrays, programmable logic devices, etc., but can also be implemented by software executed by various types of processors, and can also be implemented by a combination of the above-mentioned hardware circuits and software (for example, firmware).

[0078] For more details about the above modules, please refer to other places in this manual and will not be repeated here.

[0079] In other embodiments, a transmission device for non-small cell lung cancer gene test results is also provided, including a memory and a processor. The memory is used to store executable program code, and the processor is used to call and run the executable program code from the memory, so that the device executes the above-mentioned method for transmitting the non-small cell lung cancer gene test results. The device can be specifically a chip, a component or a module, and the chip may include a connected processor and a memory; wherein the memory is used to store instructions, and when the processor calls and executes the instructions, the chip can execute the method for transmitting the non-small cell lung cancer gene test results provided in the above-mentioned embodiment.

[0080] In other embodiments, a computer program product is also provided. When the computer program product is run on a computer, the computer is caused to execute the above-mentioned related steps to implement the method for transmitting the non-small cell lung cancer gene detection result provided in the above-mentioned embodiment.

[0081] In other embodiments, a computer-readable storage medium is also provided, in which a computer program code is stored. When the computer program code is executed on a computer, the computer executes the above-mentioned related method steps to implement the method for transmitting the non-small cell lung cancer gene detection results provided in the above-mentioned embodiment.

[0082] Among them, the provided system, electronic device, computer program product, and computer-readable storage medium are all used to execute the corresponding methods provided above. Therefore, the beneficial effects that can be achieved can refer to the beneficial effects in the corresponding methods provided above, and will not be repeated here.

Claims

1. A method for transmitting gene detection results of non-small cell lung cancer, characterized in that: The method comprises the following steps: Obtain the non-small cell lung cancer gene detection sequence of the target person; The target gene sequence is divided into subsequence segments with different preset lengths respectively, wherein the target gene sequence is extracted from the gene detection sequence based on the arrangement and combination characteristics of base pairs; the repetition degree of each subsequence segment is obtained according to the occurrence of each subsequence segment in the target gene sequence; and the first subsequence segment is selected by using the size relationship between the repetition degree of a single subsequence segment of each preset length and the repetition degree of all subsequence segments; Comprehensively analyzing the repetition between first subsequence segments of different lengths and the corresponding repetition degrees, selecting target subsequence segments; constructing a dictionary using the target subsequence segments, and compressing and transmitting the target gene sequence based on the dictionary; The acquisition of the target gene sequence includes: Extracting all bases at odd positions or all bases at even positions in the non-small cell lung cancer gene detection sequence of the target person to form a target gene sequence; The step of selecting the first subsequence segment by using the magnitude relationship between the repetition degree of a single subsequence segment of each preset length and the repetition degree of all subsequence segments comprises: For any preset length: Calculate the average repetitiveness of all subsequence segments of the preset length; For any subsequence segment of the preset length, calculating the difference between the repetition degree of the subsequence segment and the average repetition degree, and determining whether the subsequence segment is the first subsequence segment based on the difference; The step of comprehensively analyzing the repetition between the first subsequence segments of different lengths and the corresponding repetition degrees to select the target subsequence segment includes: Calculating a first ratio between the repetitiveness of a reference subsequence segment corresponding to the subsequence segment to be analyzed and the repetitiveness of the subsequence segment to be analyzed; obtaining a retention index of the subsequence segment to be analyzed according to the difference between the repetitiveness of the subsequence segment to be analyzed and the reference subsequence segment to be analyzed, and all first ratios corresponding to the subsequence segment to be analyzed; the subsequence segment to be analyzed is any first subsequence segment; the reference subsequence segment is a first subsequence segment among all first subsequence segments that contains the subsequence segment to be analyzed and has a length greater than the subsequence segment to be analyzed; It is determined whether the subsequence segment to be analyzed is a target subsequence segment based on the retention index.

2. A method for transmitting non-small cell lung cancer gene detection results according to claim 1, characterized in that: The step of obtaining the repetitiveness of each subsequence segment according to the occurrence of each subsequence segment in the target gene sequence includes: The number of times the candidate subsequence segment appears in the target gene sequence is counted; the number is used as the repetition degree of the candidate subsequence segment; the candidate subsequence segment is any subsequence segment among all subsequence segments of all preset lengths.

3. The method for transmitting the results of non-small cell lung cancer gene detection according to claim 1, characterized in that: The determining, based on the difference, whether the subsequence segment is the first subsequence segment comprises: If the difference is greater than a preset difference threshold, the subsequence segment is determined to be the first subsequence segment; the preset difference threshold is greater than or equal to 0.

4. The method for transmitting the results of non-small cell lung cancer gene detection according to claim 1, characterized in that: The step of obtaining the retention index of the subsequence segment to be analyzed according to the difference between the repetitiveness of the subsequence segment to be analyzed and the corresponding reference subsequence segment and all the first ratios corresponding to the subsequence segment to be analyzed includes: Calculate the overall difference between the repetitiveness of the subsequence segment to be analyzed and all corresponding reference subsequence segments; Calculate the average of all first ratios corresponding to the subsequence segment to be analyzed; The normalized result of the difference between the overall difference and the average value is determined as the retention index of the subsequence segment to be analyzed.

5. The method for transmitting the results of non-small cell lung cancer gene detection according to claim 1, characterized in that: The determining whether the subsequence segment to be analyzed is a target subsequence segment based on the retention index includes: If the retention index is greater than a preset retention threshold, the subsequence segment to be analyzed is taken as the target subsequence segment.

6. The method for transmitting the results of non-small cell lung cancer gene detection according to claim 1, characterized in that: The LZW algorithm is used to compress the gene detection sequence.

7. A transmission system for non-small cell lung cancer gene detection results, characterized in that: The system is used to implement the method described in any one of claims 1 to 6, and the system comprises: A data collection module, used to obtain the non-small cell lung cancer gene detection sequence of the target person; A first subsequence segment screening module is used to divide the target gene sequence into subsequence segments with different preset lengths, wherein the target gene sequence is extracted from the gene detection sequence based on the arrangement and combination characteristics of base pairs; obtain the repetition degree of each subsequence segment according to the occurrence of each subsequence segment in the target gene sequence; and screen the first subsequence segment by using the size relationship between the repetition degree of a single subsequence segment of each preset length and the repetition degree of all subsequence segments; The data transmission module is used to comprehensively analyze the repetition between the first subsequence segments of different lengths and the corresponding repetition degrees to screen the target subsequence segments; construct a dictionary using the target subsequence segments, and compress and transmit the target gene sequence based on the dictionary.

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