Genetic variation site processing method and system, and model training method

Abstract

The embodiment of the invention provides a heritable variation site processing method and system and a model training method, and relates to the technical field of biological genetics, the heritable variation site processing method comprises the steps that an initial site sequence of a biological sample to be processed is determined, and the initial site sequence comprises a plurality of heritable variation sites arranged in sequence; the initial site sequence is input into a site processing model, processing results corresponding to the multiple genetic variation sites are obtained, the site processing model is used for processing genetic variation site features of the genetic variation sites, the incidence relation between the genetic variation sites is determined, and the processing results are obtained according to the incidence relation. Adjusting the arrangement sequence of the heritable variation sites in the initial site sequence according to the incidence relation to obtain a target site sequence, and processing the target site sequence to obtain a processing result; the problem of low accuracy of the processing result output by the neural network model is avoided.

Claims

1. A method for processing genetic variation sites, comprising: Determining an initial site sequence of a biological sample to be processed, wherein the initial site sequence includes a plurality of genetic variation sites arranged in sequence; The initial site sequence is input into a site processing model to obtain processing results corresponding to the multiple genetic variation sites, wherein the site processing model is used to process the genetic variation site characteristics of each genetic variation site, determine the association relationship between the genetic variation sites, adjust the arrangement order of the genetic variation sites in the initial site sequence according to the association relationship, obtain a target site sequence, and process the target site sequence to obtain the processing result.

2. The method according to claim 1, inputting the initial site sequence into a site processing model to obtain processing results corresponding to the plurality of genetic variation sites, comprising: Inputting the initial site sequence into the site processing model, wherein the site processing model includes a sequence adjustment unit and a sequence processing unit; Using the sequence adjustment unit, the genetic variation site characteristics of each genetic variation site are processed to determine the association relationship between the genetic variation sites, and the arrangement order of each genetic variation site in the initial site sequence is adjusted according to the association relationship to obtain a target site sequence; The target site sequence is processed using the sequence processing unit to obtain the processing result.

3. The method according to claim 2, wherein the sequence adjustment unit is used to process the genetic variation site characteristics of each genetic variation site to determine the association relationship between the genetic variation sites, comprising: Determine the plurality of genetic variation sites in the initial site sequence by using the sequence adjustment unit, and extract features of each genetic variation site to obtain the genetic variation site features corresponding to each genetic variation site; Perform feature analysis on multiple genetic variation site features to obtain correlation information between the features of each genetic variation site; Based on the association information, the association relationship between the genetic variation sites is determined.

4. The method according to claim 3, wherein the feature analysis is performed on a plurality of genetic variation site features to obtain association information between the features of each genetic variation site, comprising: Performing feature cluster analysis on the multiple genetic variation site features to obtain at least two feature sets, determining the genetic variation site features of the same feature set as associated genetic variation site features, determining the genetic variation site features of different feature sets as unassociated genetic variation site features, and determining the association information based on the associated genetic variation site features and the unassociated genetic variation site features; or A similarity calculation is performed based on the plurality of genetic variation site features to determine the similarity between the genetic variation site features, and the similarity is determined as the association information between the genetic variation site features.

5. The method according to claim 2, using the sequence processing unit to process the target site sequence to obtain the processing result, comprising: Inputting the target site sequence into the sequence processing unit, and using the sequence processing unit to determine the multiple genetic variation sites in the target site sequence; Extracting features from each of the genetic variation sites to obtain associated genetic variation site features between associated genetic variation sites; Result prediction is performed based on the characteristics of the associated genetic variation sites to obtain processing results corresponding to the multiple genetic variation sites.

6. The method of claim 1, wherein determining the initial site sequence of the biological sample to be processed comprises: receiving the initial site sequence of the biological sample to be processed sent by a client, wherein the initial site sequence is sent by the client when the user performs an initial site sequence upload operation; After inputting the initial site sequence into the site processing model to obtain the processing results corresponding to the plurality of genetic variation sites, the method further includes: The processing result is sent to the client for display.

7. The method according to any one of claims 1 to 6, wherein the site processing model is a phenotype prediction processing model, and the processing result is a phenotype prediction result; The step of inputting the initial site sequence into a site processing model to obtain processing results corresponding to the plurality of genetic variation sites includes: The initial site sequence is input into the phenotype prediction processing model to obtain the phenotype prediction results corresponding to the multiple genetic variation sites.

8. The method according to any one of claims 1 to 6, further comprising: before inputting the initial site sequence into a site processing model to obtain processing results corresponding to the plurality of genetic variation sites: Determine a site processing model to be trained and training data, wherein the training data includes a sample site sequence and a sample label of a training biological sample, and the sample site sequence includes a plurality of sample genetic variation sites arranged in sequence; Using the to-be-trained site processing model to process the genetic variation site characteristics of each sample genetic variation site, and determining the association relationship between the genetic variation sites; Adjusting the arrangement order of the genetic variation sites of each sample in the sample site sequence according to the association relationship to obtain an adjusted sample site sequence; Processing the adjusted sample site sequence to obtain a sample processing result; The sample processing results and sample labels are used to adjust the model parameters of the site processing model to be trained to obtain the site processing model.

9. A model training method, applied to a cloud-side device, comprising: Determine a site processing model to be trained and training data, wherein the training data includes a sample site sequence and a sample label of a training biological sample, and the sample site sequence includes a plurality of sample genetic variation sites arranged in sequence; Using the site processing model to be trained, the genetic variation site characteristics of each sample genetic variation site are processed to determine the association relationship between the genetic variation sites, and the arrangement order of the genetic variation sites of each sample in the sample site sequence is adjusted according to the association relationship to obtain an adjusted sample site sequence; Processing the adjusted sample site sequence to obtain a sample processing result; The sample processing results and the sample labels are used to adjust the model parameters of the site processing model to be trained to obtain a trained site processing model.

10. The method according to claim 9, using the site processing model to be trained to process the genetic variation site characteristics of each sample genetic variation site, determine the association relationship between the genetic variation sites, and adjust the arrangement order of the genetic variation sites of each sample in the sample site sequence according to the association relationship to obtain the adjusted sample site sequence, comprising: Using the sequence adjustment unit in the training site processing model, the genetic variation site characteristics of each sample genetic variation site are processed to determine the association relationship between the genetic variation sites, and the arrangement order of the genetic variation sites of each sample in the sample site sequence is adjusted according to the association relationship to obtain an adjusted sample site sequence; The step of processing the adjusted sample site sequence to obtain a sample processing result includes: The adjusted sample site sequence is processed using a sequence processing unit in the site processing model to be trained to obtain a sample processing result.

11. The method according to claim 10, using the sample processing result and the sample label to adjust the model parameters of the site processing model to be trained to obtain a trained site processing model, comprising: Calculating a loss function for the sequence processing unit using the sample processing result and the sample label; Determine a reward value for the sequence adjustment unit by using the sample processing result and the similarity between the sample labels; The loss function is used to optimize the model parameters of the sequence processing unit, and the reward value is used to perform reinforcement learning processing on the sequence adjustment unit, and the site processing model to be trained is continued to be trained until the model training stop condition is reached, thereby obtaining the trained site processing model.

12. A method for processing genetic variation sites, applied to a cloud-side device, comprising: A processing request for a genetic variation site sent by a receiving end-side device, wherein the processing request carries an initial site sequence of a biological sample to be processed, and the initial site sequence includes a plurality of genetic variation sites arranged in sequence; In response to the processing request, the initial site sequence is input into a site processing model to obtain processing results corresponding to the plurality of genetic variation sites, wherein the site processing model is used to process genetic variation site characteristics of each genetic variation site, determine the association relationship between the genetic variation sites, adjust the arrangement order of the genetic variation sites in the initial site sequence according to the association relationship, obtain a target site sequence, and process the target site sequence to obtain the processing result; The processing result is sent to the terminal side device.

13. A phenotype prediction method, comprising: Determining an initial site sequence of a biological sample to be processed, wherein the initial site sequence includes a plurality of genetic variation sites arranged in sequence; The initial site sequence is input into a phenotype prediction processing model to obtain phenotype prediction results corresponding to the multiple genetic variation sites, wherein the phenotype prediction processing model is used to process the genetic variation site characteristics of each genetic variation site, determine the association relationship between the genetic variation sites, adjust the arrangement order of the genetic variation sites in the initial site sequence according to the association relationship, obtain a target site sequence, and process the target site sequence to obtain the phenotype prediction result.

14. A genetic variation site processing system, comprising a client and a server, wherein: The client is configured to send an initial site sequence of a biological sample to be processed to the server, wherein the initial site sequence includes a plurality of genetic variation sites arranged in sequence; The server is configured to receive the initial site sequence of the biological sample to be processed sent by the client, input the initial site sequence into a site processing model, and obtain processing results corresponding to the multiple genetic variation sites, wherein the site processing model is used to process the genetic variation site characteristics of each genetic variation site, determine the association relationship between the genetic variation sites, adjust the arrangement order of the genetic variation sites in the initial site sequence according to the association relationship, obtain a target site sequence, and process the target site sequence to obtain the processing result.

15. A computing device comprising: Memory and processor; The memory is used to store computer programs / instructions, and the processor is used to execute the computer programs / instructions. When the computer programs / instructions are executed by the processor, the steps of the method described in any one of claims 1 to 13 are implemented.

16. A computer-readable storage medium storing a computer program / instruction, wherein the computer program / instruction, when executed by a processor, implements the steps of the method according to any one of claims 1 to 13.

17. A computer program product, comprising a computer program / instruction, which, when executed by a processor, implements the steps of the method according to any one of claims 1 to 13.

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