Gene sequence alignment and variation detection system and method based on cloud computing

Abstract

The invention discloses a gene sequence alignment and variation detection system and method based on cloud computing, and belongs to the technical field of gene detection.The gene sequence alignment and variation detection system comprises a gene collection terminal used for managing users and collecting real-time data of gene sequences of the users; the data communication module is used for transmitting user gene sequence real-time data and establishing data communication between the gene acquisition terminal and the cloud server terminal; and the cloud server terminal is used for processing the user gene sequence real-time data, performing gene sequence comparison and variation detection, and determining a gene sequence comparison result and a gene sequence comparison and variation detection result. The invention solves the problem of poor gene sequence comparison and variation detection effect caused by incapability of effectively comparing the gene sequences and effectively detecting and positioning the variation condition of the gene sequences in the prior art. According to the invention, the gene sequences can be effectively compared, the variation condition of the gene sequences can be effectively detected and positioned, and the gene sequence comparison and variation detection effects can be improved.

Description

Technical Field

[0001] The present invention relates to the field of gene detection technology, and in particular to a gene sequence comparison and variation detection system and method based on cloud computing. Background Art

[0002] With the development of genomics and the continuous advancement of gene sequencing technology, more and more bioinformatics data need to be processed and analyzed; among them, gene sequence alignment and variation detection are two important tasks in bioinformatics.

[0003] The Chinese patent with publication number CN107633158B discloses a method and device for compressing and decompressing a gene sequence. The method for compressing a gene sequence includes: generating a variant reference sequence according to high-frequency variant information and a standard reference sequence; compressing the gene sequence to be processed according to the matching result between the gene sequence to be processed and the variant reference sequence to obtain a compressed gene sequence; the compression rate of the gene sequence can be improved, thereby reducing the storage space of the gene sequence and facilitating the copying and transmission of the gene sequence; however, the patent has the following defects: The existing methods cannot effectively compare gene sequences, and cannot effectively detect and locate gene sequence variations, resulting in poor results in gene sequence comparison and variation detection. Summary of the invention

[0004] The purpose of the present invention is to provide a cloud computing-based gene sequence alignment and variation detection system and method, which can effectively align gene sequences and effectively detect and locate gene sequence variations, thereby improving the gene sequence alignment and variation detection effects and solving the problems raised in the above-mentioned background technology.

[0005] To achieve the above object, the present invention provides the following technical solutions: The cloud computing-based gene sequence alignment and variation detection system includes: Gene collection terminal, used to manage users and collect real-time data of user gene sequences; Data communication module, used to transmit user gene sequence real-time data and establish data communication between gene collection terminal and cloud server terminal; The cloud server terminal is used to process the user's real-time gene sequence data, perform gene sequence comparison and variation detection, and determine the gene sequence comparison results and gene sequence comparison and variation detection results.

[0006] Preferably, the gene collection terminal comprises: User management unit, used to manage user identity registration, login and user rights; The user management interface prompts the user to input the gene sequence, and the user inputs the gene sequence according to the prompt of the user management interface; A gene collection unit, used for real-time collection of gene sequences input by users; After the user inputs the gene sequence, the user management interface collects the gene sequence in real time and automatically converts the gene sequence into a format that can be recognized by the computer to determine the real-time data of the user's gene sequence.

[0007] Preferably, the gene collection terminal further includes: A response time real-time monitoring module is used to monitor in real time the collection response time of the gene collection unit after the gene sequence is input by the user; A duration comparison module, used to compare the collection response duration of the gene collection unit after the gene sequence input by the user with a preset collection response duration threshold; A collection monitoring quantity setting module, used for setting the collection monitoring quantity using the collection response time exceeding the preset collection response time threshold when the collection response time of the gene collection unit after the gene sequence input by the user exceeds the preset collection response time threshold; The collected monitoring quantity is obtained by the following formula: ; Where Q represents the number of collected monitoring; INT[] represents rounding up the function inside the brackets; T represents the collection response time that exceeds the preset collection response time threshold; T th Indicates the preset collection response time threshold; T z represents the maximum allowable acquisition response time corresponding to the minimum sensitivity that satisfies the normal operation of data acquisition; λ represents the adjustment coefficient, and the value range of the adjustment coefficient is 0.13-0.36; t d represents the average time interval for data collection of the gene collection unit; The timeliness anomaly determination module is used to determine whether there is a data collection timeliness anomaly in the gene collection unit by using the collection response time of the real-time collection times of the gene collection unit corresponding to the collection monitoring quantity after the collection response time exceeds a preset collection response time threshold.

[0008] Preferably, the timeliness abnormality determination module includes: A collection parameter monitoring module, used to monitor the real-time collection times of the gene collection unit according to the collection monitoring quantity after the collection response time exceeds a preset collection response time threshold; A collection response duration calling module is used to call the collection response duration corresponding to each data collection in the real-time collection times of the gene collection unit when the real-time collection times of the gene collection unit reaches the collection monitoring number; A data collection sensitivity coefficient acquisition module is used to obtain the data collection sensitivity coefficient corresponding to the gene collection unit by using the collection response time corresponding to each data collection in the real-time collection times of the gene collection unit; The data collection sensitivity coefficient corresponding to the gene collection unit is obtained by the following formula: ; Wherein, K represents the data collection sensitivity coefficient corresponding to the gene collection unit; Q represents the number of collection monitoring; T represents the collection response time exceeding the preset collection response time threshold; T th Indicates the preset collection response time threshold; T z Indicates the maximum allowable acquisition response time corresponding to the minimum sensitivity that satisfies the normal operation of data acquisition; T max and T min represents the maximum and minimum values ​​of the collection response time corresponding to Q data collections of the gene collection unit; T i represents the collection response time corresponding to the i-th data collection of the gene collection unit; A coefficient comparison module, used for comparing the data acquisition sensitivity coefficient with a preset sensitivity coefficient threshold; The abnormal alarm judgment and module is used to judge that there is an abnormality in the timeliness of data collection in the gene collection unit when the data collection sensitivity coefficient is lower than a preset sensitivity coefficient threshold, and to issue an abnormal alarm.

[0009] Preferably, the data communication module comprises: A data sending unit, used to send user gene sequence real-time data; A data receiving unit, used to receive real-time gene sequence data from users; According to the requirements of gene sequence comparison and variation detection based on cloud computing, a data communication link is established between the data sending unit and the data receiving unit; The data sending unit receives the user gene sequence real-time data transmitted from the gene collection terminal, and the data sending unit sends the received user gene sequence real-time data to the data receiving unit; The data receiving unit receives the user gene sequence real-time data transmitted by the data sending unit, and the data receiving unit sends the received user gene sequence real-time data to the cloud server terminal.

[0010] Preferably, the cloud server terminal includes: A data processing module is used to process the real-time data of the user's gene sequence and determine the characteristic data of the user's gene sequence; The comparison and analysis module is used to compare and analyze the user's gene sequence feature data and determine the gene sequence comparison results based on cloud computing; The mutation detection module is used to locate the mutation sites of gene sequences and determine the gene sequence comparison and mutation detection results based on cloud computing; The storage and display module is used to store and display gene sequence comparison and variation detection reports based on cloud computing.

[0011] Preferably, the data processing module includes: A data cleaning unit, used to clean the user's gene sequence real-time data; Obtain real-time data of user gene sequences; Clean the user's real-time gene sequence data; Remove inconsistent data, invalid values ​​and missing values ​​in the user's real-time gene sequence data; Determine the user's real-time gene sequence data that is useful for gene sequence alignment and variation detection; A feature extraction unit, used to extract features from user gene sequence real-time data; Obtain real-time user gene sequence data that is useful for gene sequence alignment and variation detection after cleaning; Extract features from real-time user gene sequence data useful for gene sequence alignment and variation detection; Extract features that can reflect gene sequence alignment and variation detection; Determine the user's gene sequence feature data.

[0012] Preferably, the comparison and analysis module includes: A standard setting unit, used to set user gene sequence standard data; According to the needs of gene sequence comparison and variation detection based on cloud computing, user gene sequence standard data is pre-set, and the user gene sequence standard data is used to provide a reference for gene sequence comparison; Comparison and analysis unit, used to compare and analyze user gene sequence feature data; Obtain user gene sequence characteristic data and user gene sequence standard data; Based on the global comparison algorithm, the user's gene sequence feature data and the user's gene sequence standard data are compared and analyzed to determine the similarities and differences between the user's gene sequence feature data and the user's gene sequence standard data, and determine the gene sequence comparison result based on cloud computing; Wherein, if the user's gene sequence characteristic data is within the user's gene sequence standard data range, the gene sequence comparison result based on cloud computing is that the user's gene sequence is normal; Among them, if the user's gene sequence feature data is not within the user's gene sequence standard data range, the gene sequence comparison result based on cloud computing is the user's gene sequence variation.

[0013] Preferably, the variation detection module comprises: A search and positioning unit is used to search and locate the gene sequence variation site; Obtain gene sequence comparison results based on cloud computing; According to the gene sequence comparison results based on cloud computing, the user's gene sequence feature data is mined and analyzed to find the user's gene sequence variation area; Based on the user's gene sequence variation region, the gene sequence variation site is searched and located to locate the gene sequence variation site; Determine the results of gene sequence alignment and variation detection based on cloud computing.

[0014] Preferably, the storage display module includes: A distributed database for storing cloud-based gene sequence alignment and mutation detection reports; Obtain user gene sequence feature data, gene sequence comparison results, and gene sequence comparison and variation detection results; Analyze and integrate user gene sequence feature data, gene sequence comparison results, and gene sequence comparison and variation detection results to form a gene sequence comparison and variation detection report based on cloud computing; Store cloud-based gene sequence alignment and mutation detection reports; The display sharing unit is used to display the gene sequence alignment and variation detection report based on cloud computing in a visual form, and to share the gene sequence alignment and variation detection report based on cloud computing.

[0015] According to another aspect of the present invention, a cloud computing-based gene sequence alignment and variation detection method is provided, which is implemented based on the above-mentioned cloud computing-based gene sequence alignment and variation detection system, and includes the following steps: S1: Manage user identity registration, login and user rights through the gene collection terminal, collect user gene sequence real-time data, transmit user gene sequence real-time data through the data communication module, and establish data communication between the gene collection terminal and the cloud server terminal; S2: Process the user's gene sequence real-time data through the cloud server terminal, compare and analyze the user's gene sequence feature data and the user's gene sequence standard data based on the global comparison algorithm, determine the gene sequence comparison result, search and locate the gene sequence variation site, and determine the gene sequence comparison and variation detection results.

[0016] Compared with the prior art, the present invention has the following beneficial effects: The present invention manages users, collects real-time gene sequence data of users, processes the real-time gene sequence data of users, determines gene sequence feature data of users, compares and analyzes the gene sequence feature data of users and standard gene sequence data of users based on a global comparison algorithm, judges the similarity and difference between the gene sequence feature data of users and standard gene sequence data of users, determines gene sequence comparison results based on cloud computing, searches and locates gene sequence variation sites, determines gene sequence comparison and variation detection results based on cloud computing, can effectively compare gene sequences, can effectively detect and locate gene sequence variation situations, and can improve gene sequence comparison and variation detection effects. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 It is a framework diagram of the gene sequence alignment and variation detection system based on cloud computing of the present invention; Figure 2 The present invention is a flowchart of the gene sequence alignment and variation detection method based on cloud computing. DETAILED DESCRIPTION

[0018] 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.

[0019] In order to solve the existing problem that gene sequences cannot be effectively compared and gene sequence variations cannot be effectively detected and located, resulting in poor gene sequence comparison and variation detection effects, please refer to Figure 1-Figure 2 , this embodiment provides the following technical solutions: The cloud computing-based gene sequence alignment and variation detection system includes: The gene collection terminal is used to manage users and collect real-time data of users' gene sequences.

[0020] In this embodiment, the gene collection terminal includes: User management unit, used to manage user identity registration, login and user rights; Specifically, according to the requirements of gene sequence comparison and variation detection based on cloud computing, the user management interface displays user registration requirements, and the user enters user identity information according to the user registration requirements to complete user identity registration; Among them, user identity information includes name, gender, age, address, phone number, account number and password; Specifically, after the user identity registration is completed, the user logs in based on the account and password, and the account and password entered by the user are automatically authenticated. After the identity authentication is qualified, the user logs in successfully; Specifically, after the user successfully logs in, the user exercises the authority of gene sequence comparison and variation detection, and the user management interface prompts the user to input the gene sequence, and the user inputs the gene sequence according to the prompt of the user management interface; A gene collection unit, used for real-time collection of gene sequences input by users; After the user inputs the gene sequence, the user management interface collects the gene sequence in real time and automatically converts the gene sequence into a format that can be recognized by the computer, determines the user's real-time gene sequence data, and provides data support for subsequent gene sequence comparison and variation detection.

[0021] It should be noted that the real-time collection of user identity information and gene sequences input by users has been based on the user's consent in advance, and the user identity information and real-time gene sequence data are collected, analyzed and used after obtaining the user's consent; the user identity information and real-time gene sequence data are collected legally, and used legally.

[0022] The data communication module is used to transmit the user's real-time gene sequence data and establish data communication between the gene collection terminal and the cloud server terminal.

[0023] Specifically, the gene collection terminal also includes: A response time real-time monitoring module is used to monitor in real time the collection response time of the gene collection unit after the gene sequence is input by the user; A duration comparison module, used to compare the collection response duration of the gene collection unit after the gene sequence input by the user with a preset collection response duration threshold; A collection monitoring quantity setting module, used for setting the collection monitoring quantity using the collection response time exceeding the preset collection response time threshold when the collection response time of the gene collection unit after the gene sequence input by the user exceeds the preset collection response time threshold; The collected monitoring quantity is obtained by the following formula: ; Where Q represents the number of collected monitoring; INT[] represents rounding up the function inside the brackets; T represents the collection response time that exceeds the preset collection response time threshold; T th Indicates the preset collection response time threshold; T z represents the maximum allowable acquisition response time corresponding to the minimum sensitivity that satisfies the normal operation of data acquisition; λ represents the adjustment coefficient, and the value range of the adjustment coefficient is 0.13-0.36; td represents the average time interval for data collection of the gene collection unit; The timeliness anomaly determination module is used to determine whether there is a data collection timeliness anomaly in the gene collection unit by using the collection response time of the real-time collection times of the gene collection unit corresponding to the collection monitoring quantity after the collection response time exceeds a preset collection response time threshold.

[0024] The technical effect of the above technical solution is: through the real-time monitoring module of the response time, the gene collection terminal can monitor the collection response time of the gene collection unit after the user inputs the gene sequence in real time. This helps to timely discover delays or lags in the collection process and ensure the timeliness of data collection. The time comparison module compares the real-time monitored collection response time with the preset collection response time threshold. Once the threshold is exceeded, the abnormal response mechanism is triggered, which helps to timely identify and deal with potential collection problems. When the collection response time exceeds the preset threshold, the collection monitoring quantity setting module dynamically sets the collection monitoring quantity according to the collection response time exceeding the threshold. This mechanism is calculated by formula, taking into account multiple factors (such as the collection response time exceeding the threshold, the preset threshold, the maximum allowed collection response time, the adjustment coefficient and the average time interval of data collection), making the setting of the monitoring quantity more reasonable and scientific. After the collection response time exceeds the preset threshold, the timeliness abnormality judgment module uses the collection response time of the real-time collection times of the gene collection unit corresponding to the collection monitoring quantity to determine whether there is an abnormality in the timeliness of data collection. This judgment helps to further confirm whether there are problems in the collection process and take corresponding measures to correct them. Overall, this technical solution works together in the gene collection process through multiple links such as real-time monitoring, intelligent comparison, dynamic adjustment and abnormality judgment, which helps to improve the efficiency and accuracy of data collection. At the same time, by dynamically adjusting the number of collection monitoring, it can also respond more flexibly to different collection scenarios and needs. Through real-time monitoring and abnormality handling mechanisms, this technical solution can promptly discover and handle problems in the collection process, thereby enhancing the reliability and stability of the entire gene collection system. This is of great significance for ensuring the integrity and accuracy of genetic data.

[0025] In summary, this technical solution realizes comprehensive monitoring and management of the gene collection process through a series of intelligent monitoring and processing mechanisms, improves the efficiency and accuracy of data collection, and enhances the reliability and stability of the system.

[0026] Specifically, the timeliness abnormality determination module includes: A collection parameter monitoring module, used to monitor the real-time collection times of the gene collection unit according to the collection monitoring quantity after the collection response time exceeds a preset collection response time threshold; A collection response duration calling module is used to call the collection response duration corresponding to each data collection in the real-time collection times of the gene collection unit when the real-time collection times of the gene collection unit reaches the collection monitoring number; A data collection sensitivity coefficient acquisition module is used to obtain the data collection sensitivity coefficient corresponding to the gene collection unit by using the collection response time corresponding to each data collection in the real-time collection times of the gene collection unit; The data collection sensitivity coefficient corresponding to the gene collection unit is obtained by the following formula: ; Wherein, K represents the data collection sensitivity coefficient corresponding to the gene collection unit; Q represents the number of collection monitoring; T represents the collection response time exceeding the preset collection response time threshold; T th represents the preset collection response time threshold; c represents the maximum allowable collection response time corresponding to the minimum sensitivity that satisfies the normal operation of data collection; T max and T min represents the maximum and minimum values ​​of the collection response time corresponding to Q data collections of the gene collection unit; T i represents the collection response time corresponding to the i-th data collection of the gene collection unit; A coefficient comparison module, used for comparing the data acquisition sensitivity coefficient with a preset sensitivity coefficient threshold; The abnormal alarm judgment and module is used to judge that there is an abnormality in the timeliness of data collection in the gene collection unit when the data collection sensitivity coefficient is lower than a preset sensitivity coefficient threshold, and to issue an abnormal alarm.

[0027] The technical effect of the above technical solution is: through the acquisition parameter monitoring module, the module can monitor the real-time acquisition times of the gene acquisition unit in real time according to the set acquisition monitoring number after the acquisition response time exceeds the preset threshold. This ensures the continuity and integrity of data acquisition and provides a basis for subsequent data analysis. The acquisition response time retrieval module can accurately retrieve the acquisition response time corresponding to each data acquisition when the real-time acquisition times of the gene acquisition unit reach the monitoring number. This step is crucial for the subsequent calculation of the data acquisition sensitivity coefficient. The data acquisition sensitivity coefficient acquisition module uses the collected response time to calculate the data acquisition sensitivity coefficient of the gene acquisition unit through the above formula. This coefficient combines multiple factors, such as the number of acquisition monitoring, the acquisition response time exceeding the threshold, the preset threshold, the maximum allowable acquisition response time, and the maximum and minimum values ​​of the actual acquisition response time, so as to more accurately reflect the sensitivity and response speed of the gene acquisition unit. The coefficient comparison module compares the calculated data acquisition sensitivity coefficient with the preset sensitivity coefficient threshold. Once the sensitivity coefficient is lower than the threshold, the abnormal alarm determination module will immediately determine that there is an abnormality in the timeliness of data acquisition in the gene acquisition unit and trigger an abnormal alarm. This mechanism ensures that problems can be discovered and handled in a timely manner, avoiding delays or failures in data collection. Overall, this technical solution works together in the gene collection process through multiple links such as real-time monitoring, precise analysis, scientific calculations, and intelligent judgment, significantly improving the quality and efficiency of data collection. It can not only detect and handle problems in the collection process in a timely manner, but also ensure the accuracy and integrity of the data, providing strong support for subsequent gene analysis and research. This technical solution enhances the reliability and stability of the gene collection system through a series of intelligent monitoring and judgment mechanisms. It can operate stably in various complex and changing environments, ensuring the continuity and accuracy of data collection, thereby improving the performance and availability of the entire system.

[0028] In summary, this technical solution realizes comprehensive monitoring and management of the gene collection process through precise monitoring, scientific calculation and intelligent judgment, significantly improves the quality and efficiency of data collection, and enhances the reliability and stability of the system.

[0029] In this embodiment, the data communication module includes: A data sending unit, used to send user gene sequence real-time data; A data receiving unit, used to receive real-time gene sequence data from users; According to the requirements of gene sequence comparison and variation detection based on cloud computing, a data communication link is established between the data sending unit and the data receiving unit; Wherein, the data sending unit transmits an instruction requesting to establish a data communication link to the data receiving unit; The data receiving unit receives the instruction transmitted by the data sending unit requesting to establish a data communication link, and the data receiving unit checks the data communication channel according to the data communication requirement to check whether there is an idle data communication channel for transmitting the real-time data of the user gene sequence; When the data receiving unit does not have an idle data communication channel for transmitting the real-time data of the user's gene sequence, the data receiving unit transmits an instruction to the data sending unit not to agree to establish a data communication link, and at this time, the data sending unit queues and waits; When the data receiving unit has an idle data communication channel for transmitting the real-time data of the user's gene sequence, the data receiving unit transmits an instruction to agree to establish a data communication link to the data sending unit; The data sending unit receives the instruction of agreeing to establish the data communication link transmitted by the data receiving unit, and the data sending unit establishes the data communication link with the data receiving unit according to the instruction of agreeing to establish the data communication link transmitted by the data receiving unit; Specifically, the data sending unit receives the user gene sequence real-time data transmitted from the gene collection terminal, and the data sending unit sends the received user gene sequence real-time data to the data receiving unit; Specifically, the data receiving unit receives the user gene sequence real-time data transmitted from the data sending unit, and the data receiving unit sends the received user gene sequence real-time data to the cloud server terminal.

[0030] The cloud server terminal is used to process the user's real-time gene sequence data, perform gene sequence comparison and variation detection, and determine the gene sequence comparison results and gene sequence comparison and variation detection results.

[0031] In this embodiment, the cloud server terminal includes: The data processing module is used to process the real-time data of the user's gene sequence and determine the user's gene sequence feature data.

[0032] In this embodiment, the data processing module includes: A data cleaning unit, used to clean the user's gene sequence real-time data; Obtain real-time data of user gene sequences; Clean the user's real-time gene sequence data, including: Perform consistency check on user gene sequence real-time data; Check whether the user's real-time gene sequence data meets the requirements based on the reasonable value range and mutual relationship of each parameter in the user's real-time gene sequence data; Remove inconsistent data that is beyond the normal range, logically unreasonable or contradictory in the user's real-time gene sequence data; Process invalid and missing values ​​of user gene sequence real-time data; According to the requirements of data validity and integrity, check whether the user's real-time gene sequence data contains invalid values ​​and missing values; Remove invalid values ​​and missing values ​​in the user's real-time gene sequence data that are useless for gene sequence alignment and variation detection; Determine the user's real-time gene sequence data that is useful for gene sequence alignment and variation detection; It should be noted that data cleaning refers to the process of processing and organizing the user's real-time gene sequence data during the data analysis process to improve the quality and availability of the user's real-time gene sequence data.

[0033] Among them, data cleaning includes checking data consistency, processing invalid values ​​and missing values. When checking the consistency of user gene sequence real-time data, check whether the user gene sequence real-time data meets the requirements according to the reasonable value range and mutual relationship of each parameter in the user gene sequence real-time data, and remove inconsistent data in the user gene sequence real-time data that exceeds the normal range, is logically unreasonable or contradictory. For example, a variable measured by a 1-7 scale has a value of 0, and a negative number appears in the weight, which should be regarded as exceeding the normal value range. Computer software such as SPSS, SAS, and Excel can automatically identify each variable value that exceeds the range according to the defined value range. Logically inconsistent answers may appear in various forms: for example, many respondents said that they drove to work, but reported that they did not have a car; or the respondents reported that they were heavy buyers and users of a certain brand, but at the same time gave a very low score on the familiarity scale; when inconsistencies are found, the questionnaire number, record number, variable name, error category, etc. should be listed to facilitate further verification and correction.

[0034] At the same time, due to investigation, coding and entry errors, there may be some invalid values ​​and missing values ​​in the user's gene sequence real-time data, which need to be processed to improve the subsequent processing accuracy and efficiency of the user's gene sequence real-time data.

[0035] A feature extraction unit, used to extract features from user gene sequence real-time data; Obtain real-time user gene sequence data that is useful for gene sequence alignment and variation detection after cleaning; Extract features from real-time user gene sequence data useful for gene sequence alignment and variation detection; Extract features that can reflect gene sequence alignment and variation detection; Determine the user's gene sequence feature data.

[0036] The comparison and analysis module is used to compare and analyze the user's gene sequence feature data and determine the gene sequence comparison results based on cloud computing.

[0037] In this embodiment, the comparison and analysis module includes: A standard setting unit, used to set user gene sequence standard data; According to the needs of gene sequence comparison and variation detection based on cloud computing, user gene sequence standard data is pre-set, and the user gene sequence standard data is used to provide a reference for gene sequence comparison; Comparison and analysis unit, used to compare and analyze user gene sequence feature data; Obtain user gene sequence characteristic data and user gene sequence standard data; Based on the global comparison algorithm, the user's gene sequence feature data and the user's gene sequence standard data are compared and analyzed to determine the similarities and differences between the user's gene sequence feature data and the user's gene sequence standard data, and determine the gene sequence comparison result based on cloud computing; Wherein, if the user's gene sequence characteristic data is within the user's gene sequence standard data range, the gene sequence comparison result based on cloud computing is that the user's gene sequence is normal; Among them, if the user's gene sequence feature data is not within the user's gene sequence standard data range, the gene sequence comparison result based on cloud computing is the user's gene sequence variation.

[0038] It should be noted that the global alignment algorithm is a method that compares a given sequence from beginning to end so that as many characters as possible match in the same column; this algorithm is suitable for sequences with high similarity and similar length. The global alignment algorithm usually uses a dynamic programming algorithm, such as the Needleman-Wunsch algorithm and the Smith-Waterman algorithm.

[0039] The variation detection module is used to locate the variation sites of gene sequences and determine the gene sequence comparison and variation detection results based on cloud computing.

[0040] In this embodiment, the variation detection module includes: A search and positioning unit is used to search and locate the gene sequence variation site; Obtain gene sequence comparison results based on cloud computing; According to the gene sequence comparison results based on cloud computing, the user's gene sequence feature data is mined and analyzed to find the user's gene sequence variation area; Based on the user's gene sequence variation region, the gene sequence variation site is searched and located to locate the gene sequence variation site; Determine the results of gene sequence alignment and variation detection based on cloud computing.

[0041] The storage and display module is used to store and display gene sequence comparison and variation detection reports based on cloud computing.

[0042] In this embodiment, the storage display module includes: A distributed database for storing cloud-based gene sequence alignment and mutation detection reports; Obtain user gene sequence feature data, gene sequence comparison results, and gene sequence comparison and variation detection results; Analyze and integrate user gene sequence feature data, gene sequence comparison results, and gene sequence comparison and variation detection results to form a gene sequence comparison and variation detection report based on cloud computing; Store cloud-based gene sequence alignment and mutation detection reports; The display sharing unit is used to display the gene sequence alignment and variation detection report based on cloud computing in a visual form, and to share the gene sequence alignment and variation detection report based on cloud computing.

[0043] In order to better demonstrate the gene sequence alignment and variation detection process based on cloud computing, this embodiment now provides a gene sequence alignment and variation detection method based on cloud computing, which is implemented based on the above-mentioned gene sequence alignment and variation detection system based on cloud computing, and includes the following steps: S1: Manage user identity registration, login and user rights through the gene collection terminal, collect user gene sequence real-time data, transmit user gene sequence real-time data through the data communication module, and establish data communication between the gene collection terminal and the cloud server terminal; S2: Process the user's gene sequence real-time data through the cloud server terminal, compare and analyze the user's gene sequence feature data and the user's gene sequence standard data based on the global comparison algorithm, determine the gene sequence comparison result, search and locate the gene sequence variation site, and determine the gene sequence comparison and variation detection results.

[0044] 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.

[0045] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A gene sequence alignment and variation detection system based on cloud computing, characterized in that: include: Gene collection terminal, used to manage users and collect real-time data of user gene sequences; Data communication module, used to transmit user gene sequence real-time data and establish data communication between gene collection terminal and cloud server terminal; The cloud server terminal is used to process the user's real-time gene sequence data, perform gene sequence comparison and variation detection, and determine the gene sequence comparison results and gene sequence comparison and variation detection results; The gene collection terminal comprises: User management unit, used to manage user identity registration, login and user rights; The user management interface prompts the user to input the gene sequence, and the user inputs the gene sequence according to the prompt of the user management interface; A gene collection unit, used for real-time collection of gene sequences input by users; After the user inputs the gene sequence, the user management interface collects the gene sequence in real time and automatically converts the gene sequence into a format that can be recognized by the computer to determine the real-time data of the user's gene sequence; The gene collection terminal further includes: A response time real-time monitoring module is used to monitor in real time the collection response time of the gene collection unit after the gene sequence is input by the user; A duration comparison module, used to compare the collection response duration of the gene collection unit after the gene sequence input by the user with a preset collection response duration threshold; A collection monitoring quantity setting module, used for setting the collection monitoring quantity using the collection response time exceeding the preset collection response time threshold when the collection response time of the gene collection unit after the gene sequence input by the user exceeds the preset collection response time threshold; The collected monitoring quantity is obtained by the following formula: ; Where Q represents the number of collected monitoring; INT[] represents rounding up the function inside the brackets; T represents the collection response time that exceeds the preset collection response time threshold; T th Indicates the preset collection response time threshold; T z represents the maximum allowable acquisition response time corresponding to the minimum sensitivity that satisfies the normal operation of data acquisition; λ represents the adjustment coefficient, and the value range of the adjustment coefficient is 0.13-0.36; t d represents the average time interval for data collection of the gene collection unit; A timeliness abnormality determination module is used to determine whether there is a data collection timeliness abnormality in the gene collection unit by using the collection response time of the real-time collection times of the gene collection unit corresponding to the collection monitoring quantity after the collection response time exceeds a preset collection response time threshold; The timeliness abnormality determination module includes: A collection parameter monitoring module, used to monitor the real-time collection times of the gene collection unit according to the collection monitoring quantity after the collection response time exceeds a preset collection response time threshold; A collection response duration calling module is used to call the collection response duration corresponding to each data collection in the real-time collection times of the gene collection unit when the real-time collection times of the gene collection unit reaches the collection monitoring number; A data collection sensitivity coefficient acquisition module is used to obtain the data collection sensitivity coefficient corresponding to the gene collection unit by using the collection response time corresponding to each data collection in the real-time collection times of the gene collection unit; The data collection sensitivity coefficient corresponding to the gene collection unit is obtained by the following formula: ; Wherein, K represents the data collection sensitivity coefficient corresponding to the gene collection unit; Q represents the number of collection monitoring; T represents the collection response time exceeding the preset collection response time threshold; T th Indicates the preset collection response time threshold; T z Indicates the maximum allowable acquisition response time corresponding to the minimum sensitivity that satisfies the normal operation of data acquisition; T max and T min represents the maximum and minimum collection response time corresponding to Q data collections of the gene collection unit; T i represents the collection response time corresponding to the i-th data collection of the gene collection unit; A coefficient comparison module, used for comparing the data acquisition sensitivity coefficient with a preset sensitivity coefficient threshold; The abnormal alarm judgment and module is used to judge that there is an abnormality in the timeliness of data collection in the gene collection unit when the data collection sensitivity coefficient is lower than a preset sensitivity coefficient threshold, and to issue an abnormal alarm.

2. The cloud computing-based gene sequence alignment and variation detection system according to claim 1, characterized in that: The data communication module comprises: A data sending unit, used to send user gene sequence real-time data; A data receiving unit, used to receive real-time gene sequence data from users; According to the requirements of gene sequence comparison and variation detection based on cloud computing, a data communication link is established between the data sending unit and the data receiving unit; The data sending unit receives the user gene sequence real-time data transmitted from the gene collection terminal, and the data sending unit sends the received user gene sequence real-time data to the data receiving unit; The data receiving unit receives the user gene sequence real-time data transmitted by the data sending unit, and the data receiving unit sends the received user gene sequence real-time data to the cloud server terminal.

3. The cloud computing-based gene sequence alignment and variation detection system according to claim 2, characterized in that: The cloud server terminal comprises: A data processing module is used to process the real-time data of the user's gene sequence and determine the characteristic data of the user's gene sequence; The comparison and analysis module is used to compare and analyze the user's gene sequence feature data and determine the gene sequence comparison results based on cloud computing; The mutation detection module is used to locate the mutation sites of gene sequences and determine the gene sequence comparison and mutation detection results based on cloud computing; Storage and display module, used to store and display gene sequence comparison and mutation detection reports based on cloud computing; The data processing module comprises: A data cleaning unit, used to clean the user's gene sequence real-time data; Obtain real-time data of user gene sequences; Clean the user's real-time gene sequence data; Remove inconsistent data, invalid values ​​and missing values ​​in the user's real-time gene sequence data; Determine the user's real-time gene sequence data that is useful for gene sequence alignment and variation detection; A feature extraction unit, used to extract features from user gene sequence real-time data; Obtain real-time user gene sequence data that is useful for gene sequence alignment and variation detection after cleaning; Extract features from real-time user gene sequence data useful for gene sequence alignment and variation detection; Extract features that can reflect gene sequence alignment and variation detection; Determine the user's gene sequence feature data.

4. The cloud computing-based gene sequence alignment and variation detection system according to claim 3, characterized in that: The comparison and analysis module comprises: A standard setting unit, used to set user gene sequence standard data; According to the needs of gene sequence comparison and variation detection based on cloud computing, user gene sequence standard data is pre-set, and the user gene sequence standard data is used to provide a reference for gene sequence comparison; Comparison and analysis unit, used to compare and analyze user gene sequence feature data; Obtain user gene sequence characteristic data and user gene sequence standard data; Based on the global comparison algorithm, the user's gene sequence feature data and the user's gene sequence standard data are compared and analyzed to determine the similarities and differences between the user's gene sequence feature data and the user's gene sequence standard data, and determine the gene sequence comparison result based on cloud computing; Wherein, if the user's gene sequence characteristic data is within the user's gene sequence standard data range, the gene sequence comparison result based on cloud computing is that the user's gene sequence is normal; Among them, if the user's gene sequence feature data is not within the user's gene sequence standard data range, the gene sequence comparison result based on cloud computing is the user's gene sequence variation.

5. The cloud computing-based gene sequence alignment and variation detection system according to claim 4, characterized in that: The variation detection module comprises: A search and positioning unit is used to search and locate the gene sequence variation site; Obtain gene sequence comparison results based on cloud computing; According to the gene sequence comparison results based on cloud computing, the user's gene sequence feature data is mined and analyzed to find the user's gene sequence variation area; Based on the user's gene sequence variation region, the gene sequence variation site is searched and located to locate the gene sequence variation site; Determine the results of gene sequence alignment and variation detection based on cloud computing.

6. The cloud computing-based gene sequence alignment and variation detection system according to claim 5, characterized in that: The storage display module includes: A distributed database for storing cloud-based gene sequence alignment and mutation detection reports; Obtain user gene sequence feature data, gene sequence comparison results, and gene sequence comparison and variation detection results; Analyze and integrate user gene sequence feature data, gene sequence comparison results, and gene sequence comparison and variation detection results to form a gene sequence comparison and variation detection report based on cloud computing; Store cloud-based gene sequence alignment and mutation detection reports; The display sharing unit is used to display the gene sequence alignment and variation detection report based on cloud computing in a visual form, and to share the gene sequence alignment and variation detection report based on cloud computing.

7. A method for gene sequence alignment and variation detection based on cloud computing, implemented based on the gene sequence alignment and variation detection system based on cloud computing according to claim 6, characterized in that: The steps include: S1: Manage user identity registration, login and user rights through the gene collection terminal, collect user gene sequence real-time data, transmit user gene sequence real-time data through the data communication module, and establish data communication between the gene collection terminal and the cloud server terminal; S2: Process the user's gene sequence real-time data through the cloud server terminal, compare and analyze the user's gene sequence feature data and the user's gene sequence standard data based on the global comparison algorithm, determine the gene sequence comparison result, search and locate the gene sequence variation site, and determine the gene sequence comparison and variation detection results.

Images