WO2024124402A1 - 基因测序方法及系统、基因图像获取方法及装置 - Google Patents

基因测序方法及系统、基因图像获取方法及装置 Download PDF

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Publication number
WO2024124402A1
WO2024124402A1 PCT/CN2022/138731 CN2022138731W WO2024124402A1 WO 2024124402 A1 WO2024124402 A1 WO 2024124402A1 CN 2022138731 W CN2022138731 W CN 2022138731W WO 2024124402 A1 WO2024124402 A1 WO 2024124402A1
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Prior art keywords
gene
image
target
feature
sequencing
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English (en)
French (fr)
Inventor
温欣
杨斌
罗滨
王忠海
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MGI Tech Co Ltd
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MGI Tech Co Ltd
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Priority to PCT/CN2022/138731 priority Critical patent/WO2024124402A1/zh
Priority to CN202280102219.5A priority patent/CN120303701A/zh
Publication of WO2024124402A1 publication Critical patent/WO2024124402A1/zh
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    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/80—Analysis of captured images to determine intrinsic or extrinsic camera parameters, i.e. camera calibration

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  • the present invention relates to the field of gene testing technology, and in particular to a gene sequencing method and system, and a gene image acquisition method and device.
  • the second generation gene sequencing technology is completed by using different dyes to label and track different bases, lasers to excite the samples to be sequenced to produce fluorescence, and the imaging system to detect and analyze the fluorescence signal value of each base. Therefore, the fluorescence signal value of each base will directly affect the quality and accuracy of sequencing. Too high a fluorescence signal will increase fluorescence crosstalk, and too low a fluorescence signal will make the base unrecognizable.
  • the main purpose of this application is to provide a gene sequencing method and system, a gene image acquisition method and device, an electronic device and a storage medium to improve the above-mentioned defects in the prior art.
  • a method for obtaining a gene image comprising:
  • the camera is triggered to re-photograph the sample to be sequenced with the target parameter value, so that the image features of the gene image obtained by the re-photographing meet the preset feature conditions.
  • the number of the image features is at least two, and the preset feature condition includes a feature value range of each image feature;
  • Determining whether the image features of the gene image meet the preset feature conditions includes:
  • the image feature includes a median of a grayscale value
  • the preset feature condition includes a first feature value range
  • judging whether the image feature of the gene image meets the preset feature condition includes: judging whether the median of the grayscale value falls within the first feature value range
  • the image feature includes an average value of grayscale values
  • the preset feature includes a second feature value range
  • judging whether the image feature of the gene image meets the preset feature condition includes: judging whether the average value of the grayscale value falls within the second feature value range
  • the image feature includes a grayscale value of a target pixel
  • the preset feature includes a third feature value range
  • determining whether the image feature of the gene image meets the preset feature condition includes: determining whether the grayscale value of the target pixel falls within the third feature value range.
  • the characteristic value range is determined based on experimental data
  • the experimental data includes: data on the impact of different shooting parameters on the image features, data on the relationship between the number of exposure points contained in the gene image and the image features, and signal strength that does not affect image quality.
  • the shooting parameters include camera gain
  • Triggering the camera to re-photograph the sample to be sequenced with the target parameter value comprising:
  • the camera is triggered to re-photograph the sample to be sequenced with the target parameter value of the camera gain.
  • the shooting parameters include camera gain
  • a target camera gain matching the current shooting scene is determined.
  • a gene sequencing method comprising:
  • a gene image acquisition device comprising:
  • An acquisition module is used to acquire a gene image obtained by taking a camera of a sample to be sequenced
  • a judging module used to judge whether the image features of the gene image meet the preset feature conditions, and if the judgment result is no, call the determining module;
  • the determination module is used to determine a target parameter value of a shooting parameter that matches the current shooting scene
  • the trigger module is used to trigger the camera to re-photograph the sample to be sequenced with the target parameter value, so that the image features of the gene image obtained by the re-photographing meet the preset feature conditions.
  • a gene sequencing system comprising: a sequencing device and a gene image acquisition device;
  • the gene image acquisition device is used to acquire a gene image by executing the gene image acquisition method according to any one of the first aspects
  • the sequencing device is used to perform gene sequencing on the sequencing sample according to the gene image.
  • an electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements any of the above-described methods when executing the computer program.
  • a computer-readable storage medium on which a computer program is stored, and when the computer program is executed by a processor, any of the methods described above is implemented.
  • the gene image acquisition method provided by the present invention can provide gene images with good quality that meet the requirements of gene sequencing for gene sequencing, avoid sequencing interruption caused by poor image quality during the gene sequencing test, avoid data loss and data unavailability, thereby realizing effective gene sequencing and improving the efficiency and accuracy of gene sequencing as a whole.
  • FIG. 1a is a flow chart of a gene image acquisition method provided by an exemplary embodiment of the present invention.
  • FIG1b is a flow chart of another gene image acquisition method provided by an exemplary embodiment of the present invention.
  • FIG2a is a schematic diagram showing the influence of different camera gains on the grayscale value of a gene image provided by an exemplary embodiment of the present invention
  • FIG2b is a schematic diagram showing the relationship between the number of exposure points and the median of grayscale values included in a gene image provided by an exemplary embodiment of the present invention.
  • FIG3 is a flow chart of a gene sequencing method provided by an exemplary embodiment of the present invention.
  • FIG4a is a comparison diagram of effects provided by an exemplary embodiment of the present invention.
  • FIG4b is another effect comparison diagram provided by an exemplary embodiment of the present invention.
  • FIG5 is a schematic diagram of a module of a gene image acquisition device provided by an exemplary embodiment of the present invention.
  • FIG. 6 is a schematic diagram of a module of an electronic device provided by an exemplary embodiment of the present invention.
  • FIG. 1a is a flow chart of a gene image acquisition method provided by an exemplary embodiment of the present invention.
  • the gene image acquisition method comprises the following steps:
  • Step 101a Acquire a gene image obtained by photographing the sample to be sequenced with a camera.
  • the sample to be sequenced includes a detection ball DNB wrapped with a target, a cluster wrapped with a target, etc.
  • the target is, for example, a cell, a biological tissue or a bacterium and its reactants, etc.; a DNB (DNA nanoball) is a DNA nanoball molecule (a DNB includes multiple identical DNA sequences), which belongs to a DNA molecule.
  • the number of DNAs in a DNB can be one or more, which is not particularly limited in the embodiments of the present disclosure.
  • the cluster of the target is obtained by clustering the target.
  • the sample to be sequenced is generally placed in a sequencing chip, and the starting position of the shooting is found based on the pattern feature points on the sequencing chip. This position can ensure that the image algorithm locates the corresponding point of the sample to be sequenced.
  • the resolution of the captured gene image is about 20 million pixels. Taking DNA as an example, the gene image includes more than 4 million DNAs (or DNBs). Each bright spot represents the base information of a sequence position in a DNA fragment, and the interval between two DNAs is about 2 pixels. In addition, there are obvious dividing lines with different intervals on each gene image, and the distance between the DNA on the dividing line is different. By identifying the distance, the shooting position is determined, and the camera positioning shooting is realized.
  • One image corresponds to an area of the sequencing chip.
  • four images are taken for each area at the same time.
  • the four images are separated by different wavelengths of light by the optical filtering system.
  • the four bases have different luminescent wavelengths, so the grayscale values of the four images in the same area are different, and the positions of the bright spots are also different.
  • step 101a the genetic image obtained by taking a camera of the sample to be sequenced can be directly obtained; the genetic image obtained in step 101a can also be a genetic image used for alignment determined from the genetic image of the sample to be sequenced taken by the camera during the genetic testing process, without the need for additional, special taking of genetic images.
  • the initial parameter value of the shooting parameter used by the camera can be determined based on experience.
  • the captured gene image is used for gene sequencing.
  • the shooting parameters include at least one of light source intensity, transmittance, exposure time, detector quantum efficiency, and camera gain.
  • Step 102a determine whether the image features of the gene image meet the preset feature conditions.
  • Image features characterize the image quality of gene images and determine whether the image features meet preset feature conditions, that is, whether the image quality of gene images meets the requirements and whether effective gene sequencing can be achieved.
  • step 103a and step 104a are executed.
  • the number of image features may be one or more.
  • the preset feature conditions include the feature value ranges of the corresponding number of image features, and step 102a determines whether the feature values of each image feature fall within the corresponding feature value range.
  • the image quality of the gene image can be evaluated in multiple dimensions to ensure that the image quality of the gene image meets the requirements of subsequent gene sequencing.
  • Image features may include, but are not limited to, at least one of the following feature parameters: the median of grayscale values, the average of grayscale values, the grayscale value of target pixels, etc.
  • the median of grayscale values is the median of the grayscale values of each pixel in the gene image.
  • the average of grayscale values is the average of the grayscale values of each pixel in the gene image.
  • the target pixel can be determined according to actual needs, for example, the pixel at the center of the gene image is determined as the target pixel.
  • the target pixel can be set according to actual conditions, for example, all pixel grayscale values are sorted from high to low, and the pixel corresponding to the nth grayscale value after sorting is determined as the target pixel; wherein n can be set according to actual conditions.
  • n/number of pixels*100% is its percentile point; for example, the median can also be called the 50% point.
  • the image feature includes the median of the grayscale value
  • the preset feature condition includes the first feature value range.
  • the area corresponding to the shooting may have abnormal bright spots or dark spots.
  • the median of the grayscale value is used to characterize the image features of the entire image, which can eliminate abnormal interference from individual pixels.
  • the image feature includes an average value of grayscale values
  • the preset feature condition includes a second feature value range.
  • the average value of the grayscale value can reflect the overall state of the gene image, and the average value can well reflect the image characteristics of the gene image.
  • the image feature includes the gray value of the target pixel
  • the preset feature condition includes the third feature value range.
  • step 102a it is determined whether the gray value of the target pixel falls within the third feature value range; if the determination result is yes, it means that the image quality of the gene image meets the gene sequencing requirements and can be directly used for gene sequencing; if the determination result is no, it means that the image quality of the gene image does not meet the image sequencing requirements, and the camera shooting parameters need to be adjusted and the gene image needs to be re-acquired.
  • more than two image features are used as a basis for judging the image quality.
  • the median of the grayscale value and the average of the grayscale value are simultaneously used to evaluate the image quality.
  • the first characteristic value range, the second characteristic value range, and the third characteristic value range included in the preset characteristic conditions are determined based on experimental data, and the experimental data include: data on the impact of different shooting parameters on the image characteristics, data on the relationship between the number of exposure points contained in the gene image and the image characteristics, and signal strength that does not affect the image quality.
  • the historical gene image in S1a may be a historical gene image of a target wavelength range selected from a database.
  • the database pre-stores historical gene images based on various wavelength ranges of light.
  • S2a Determine the correlation between the characteristic value of the historical gene image and the number of exposure points of the historical gene image.
  • the association relationship can be obtained by fitting the historical gene images in the database.
  • S3a select target historical gene images that meet sequencing quality conditions from historical gene images.
  • the sequencing quality conditions can be determined according to actual needs.
  • the target historical gene image is determined to be a gene image with good quality.
  • the characteristic value of the gene image has a reference significance for evaluating the image quality.
  • the first eigenvalue range, the second eigenvalue range, and the third eigenvalue range mentioned above can all be determined through S1a to S5a.
  • the characteristic value range is determined according to the target historical gene image that meets the sequencing quality condition, and the determined characteristic value range has practical reference significance and high accuracy.
  • the following takes the image feature as the median of the gray value and the shooting parameter as the camera gain as an example to introduce the implementation method of determining the first characteristic value range (preset characteristic condition).
  • the fluctuation range of brightness of gene images obtained in the statistical experiment phase (including different DNA libraries and preparation, sequencing phase (SE/PE/barcode), see Figure 2a
  • the brightness fluctuation of different camera gains is up to 10 times.
  • Brightness fluctuation is the root cause of image overexposure or low brightness signal. If you want to stabilize the image grayscale value within a certain range, you need to know how large the target fluctuation range is before you can formulate corresponding adjustment parameters and plans.
  • the correlation between the number of overexposure points and the brightness of the gene image is statistically shown in Figure 2b.
  • the horizontal axis in the figure is the median of the grayscale value of the gene image of the different samples to be sequenced, and the vertical axis is the number of pixels with saturated grayscale values.
  • the trends of different bases are basically the same, and the correlation between the two after linear fitting is more than 80%.
  • the four bases ACGT are each combined with a dye of a different wavelength.
  • the different wavelengths of light are optically imaged onto different cameras, and the four images of the same position are named ACGT with the corresponding wavelengths.
  • the wavelength bands of the dye emission have overlapping areas, and only the A base is not interfered with. Therefore, the gene image corresponding to A and the gene image corresponding to CGT need to calculate and analyze the exposure points separately.
  • the signal strength that does not affect the sequencing quality is counted to obtain the signal range that needs to be reached.
  • a large amount of normal sequencing data is taken.
  • the statistics record the corresponding images that have passed the sequencing FQC.
  • the indicators of FQC shipment include the amount of data off the machine, quality value, error rate, split rate, etc.
  • the images of more than a dozen instruments shipped recently are counted.
  • the signal strength can be represented by the gray value and/or overexposure point number of each pixel in the gene image; among them, the overexposure point number is the number of pixels with a gray value exceeding 65472.
  • the following table shows, in order, the average of the medians of the grayscale values of all corresponding images, the average of the averages of the grayscale values, the average of the grayscale saturation points (exposure points), the difference between the first and second numbers, the standard deviation of the grayscale saturation points of the images participating in the statistics, and the sum of the third and fifth numbers.
  • the quantitative range of the gray value saturation points of the normal gene image can be obtained, thereby deducing the first eigenvalue range.
  • the second eigenvalue range and the third eigenvalue range are determined in a manner similar to the first eigenvalue range, and are not described in detail here.
  • the characteristic value range is determined in advance, and there is no need to repeatedly collect experimental data to formulate the characteristic value range in the actual gene sequencing stage or the gene image acquisition stage, thereby improving the efficiency of gene image acquisition and further improving the efficiency of gene sequencing.
  • Step 103a Determine a target parameter value of a shooting parameter that matches the current shooting scene.
  • the target parameter value is a parameter value of a shooting parameter that matches the current shooting scene, including a parameter value of at least one of the shooting parameters such as light source intensity, system transmittance, exposure time, detector quantum efficiency, and camera gain.
  • the shooting scene can be characterized by at least one of the following parameters, but is not limited to: the material of the sequencing chip, the ambient brightness, the type of samples to be sequenced, the number of samples to be sequenced, etc.
  • the camera uses the re-determined target parameter values to shoot the samples to be sequenced, and can obtain gene images with image quality that meets the requirements of gene sequencing.
  • the parameter value of the camera gain that matches the current shooting scene is re-determined without determining the parameter values of other shooting parameters.
  • the change of the camera gain will not affect the number of photons emitted by the fluorescence, will not change the signal-to-noise ratio of the gene image, and can ensure that the brightness signal can be adjusted linearly, so the implementation difficulty is low and more stable, and will not prolong the shooting time. Therefore, by adjusting the camera gain of the camera, the purpose of not affecting the image acquisition time and improving the image quality is achieved.
  • the target shooting parameters matching the current shooting scene are determined. Specifically, experimental data obtained when determining the preset characteristic conditions are obtained, and the correspondence is obtained by fitting the experimental data.
  • the target shooting parameters matching the current shooting scene are determined according to a pre-trained shooting parameter determination model.
  • the shooting parameter determination model is obtained by training a neural network according to experimental data (training samples) obtained when determining preset feature conditions.
  • the input parameters of the shooting parameter determination model include parameters related to the shooting scene, and the output parameters are shooting parameters.
  • the target parameter value the parameter value of the parameter related to the current shooting scene contained in the experimental data is input into the shooting parameter determination model, and the target parameter value of the shooting parameter matching the current shooting scene can be determined according to the shooting parameter determination model.
  • the following uses the median of grayscale values as an example to introduce a method for determining camera gain.
  • the median of the grayscale value of the image can be kept from being overexposed if it is below 23,000.
  • the scheme of the camera gain of one chain is set to be adjusted between 3/2; that is, when sequencing on one chain, take pictures with a camera gain of 3, when the corresponding image median is less than 23,000, the camera gain is set to 3, and when it is greater than 23,000, the camera gain is set to 2.
  • the two cameras corresponding to the AT wavelength use the same configuration, whichever has the lower camera gain.
  • the two cameras corresponding to the CG wavelength use the same configuration, whichever has the lower camera gain.
  • the two-chain camera gain is set to 2 to meet most application data.
  • the two-chain camera gain is set to be adjusted between 2/1; that is, during two-chain sequencing, the image is taken with a camera gain of 2.
  • the camera gain is set to 2.
  • the camera gain is set to 1.
  • the two cameras corresponding to the AT wavelength use the same configuration, whichever has the lower camera gain.
  • the two cameras corresponding to the CG wavelength use the same configuration, whichever has the lower camera gain.
  • the target camera gain is less than the camera gain used to take the gene image in step 101a. That is, there is a situation where the target camera gain is merged to a low value, such as AT corresponding to the low value merge, CG merge to a low value merge; or similar wavelengths merge to a low value.
  • a low value such as AT corresponding to the low value merge, CG merge to a low value merge; or similar wavelengths merge to a low value.
  • Step 104a triggering the camera to re-photograph the sample to be sequenced with the target parameter value, so that the re-photographed gene image matches the preset feature.
  • the camera is triggered to re-shoot the sample to be sequenced with a camera gain that matches the current shooting scene, so that the re-shot gene image matches the preset features.
  • the gene image acquisition method provided in the embodiment of the present invention can provide gene images with good quality that meet the requirements of gene sequencing for gene sequencing, avoid sequencing interruptions due to poor image quality during the gene sequencing test (for example, the inability to perform image alignment or the inability to automatically find the focus plane), avoid data loss and data unavailability, thereby achieving effective gene sequencing and improving the efficiency and accuracy of gene sequencing as a whole.
  • the fluorescence signal generated by the sample to be sequenced will be uncontrollable, which will in turn make the brightness of the gene image uncontrollable, making it difficult to obtain a gene image of good quality.
  • the camera gain that matches the current shooting scene can be determined, which is easy to operate, and the gene image captured based on the camera gain has moderate brightness and good image quality.
  • different camera gains can be used in different areas of the same gene image, so that the gene image can achieve an overall moderate brightness effect.
  • FIG. 1b is a flow chart of another gene sequencing method provided by an exemplary embodiment of the present invention, the gene sequencing method comprising the following steps:
  • Step 101b acquiring a first gene image of the sequencing sample by photographing the camera based on the target wavelength range of light.
  • the target wavelength range of light can be determined according to actual conditions.
  • Step 102b Obtain preset characteristic conditions corresponding to the target wavelength range.
  • step 102b includes:
  • S3b selecting target historical gene images that meet sequencing quality conditions from historical gene images
  • steps S1b to S5b is the same as that of steps S1a to S5a, and will not be repeated here.
  • Step 103b determining target parameter values of the shooting parameters according to the image features of the first gene image and preset feature conditions.
  • step 103b includes: determining a target camera gain according to a correspondence between predetermined image features, preset feature conditions and parameter values of shooting parameters.
  • the corresponding relationship can be obtained by fitting the image features, preset feature conditions and parameter values of the shooting parameters in advance. According to the corresponding relationship, the target parameter value of the shooting parameter matching the image features and preset feature conditions of the first gene image can be determined.
  • Step 104b triggering the camera to re-photograph the sample to be sequenced with the target parameter value, so that the image features of the re-photographed second gene image meet the preset feature conditions.
  • the gene image acquisition method provided in the embodiment of the present invention can provide gene images with good quality that meet the requirements of gene sequencing for gene sequencing, avoid sequencing interruptions due to poor image quality during the gene sequencing test (for example, the inability to perform image alignment or the inability to automatically find the focus plane), avoid data loss and data unavailability, thereby achieving effective gene sequencing and improving the efficiency and accuracy of gene sequencing as a whole.
  • FIG3 is a flow chart of a gene sequencing method provided by an exemplary embodiment of the present invention, the gene sequencing method comprising:
  • Step 301 Obtain a gene image of a sample to be sequenced.
  • the gene image is obtained by using the gene image acquisition method provided in any of the above embodiments.
  • Step 303 perform gene sequencing on the sequencing sample according to the gene image.
  • the gene images obtained by the embodiments of the present invention all meet the requirements of gene sequencing. According to the gene images, effective sequencing of sequencing samples can be achieved with high accuracy and efficiency.
  • a biochemical excision synthesis reaction will be performed to wash away the dye bound to the base that has been imaged, allowing the next base in the chain to bind to the new dye. Therefore, the wavelength of light emitted by the same DNA point may be different.
  • the base type is determined by the grayscale value obtained on different images each time the chip is photographed, and the sequence of the DNA chain is finally combined.
  • the automatic adjustment result of the test gain is 3333 for the first strand ATGC and 1122 for the second strand, that is, the first strand AT gain is 3, the GC gain is 3, the second strand AT gain is 1, the CG gain is 2, and the gains of the four barcode channels are all 1.
  • the base AT is a complementary pair, and the base CG is a complementary pair. In theory, the base content of AT is consistent, and the base content of CG is consistent.
  • the horizontal axis of the figure above is the number of sequencing cycles, and the vertical axis is the difference between AT and CG content. The closer the data is to 0, the better. However, if all configuration results are consistent, it means that other reasons have caused the base separation. This test is for comparison to show that the result after automatic gain adjustment is relatively the best.
  • the base distribution of the automatic adjustment result is normal, and the error rate and mapping rate are both good.
  • the present invention also provides embodiments of a gene sequencing device and a gene image acquisition device.
  • FIG5 is a schematic diagram of a module of a gene image acquisition device provided by an exemplary embodiment of the present invention, wherein the gene image acquisition device comprises:
  • An acquisition module 51 is used to acquire a gene image obtained by taking a camera of a sample to be sequenced;
  • the judging module 52 is used to judge whether the image features of the gene image meet the preset feature conditions, and if the judgment result is no, call the determination module;
  • the determination module 53 is used to determine the target parameter value of the shooting parameter that matches the current shooting scene
  • the trigger module 54 is used to trigger the camera to re-photograph the sample to be sequenced with the target parameter value, so that the image features of the gene image obtained by the re-photographing meet the preset feature conditions.
  • the number of the image features is at least two, and the preset feature condition includes a feature value range of each image feature;
  • the judgment module is specifically used for:
  • the image feature includes a median of a grayscale value
  • the preset feature condition includes a first feature value range
  • the judgment module is specifically used to: judge whether the median of the grayscale value falls within the first feature value range
  • the image feature includes an average value of grayscale values
  • the preset feature includes a second characteristic value range
  • the judgment module is specifically used to: judge whether the average value of the grayscale value falls within the second characteristic value range
  • the image feature includes a grayscale value of a target pixel
  • the preset feature includes a third characteristic value range
  • the judgment module is specifically used to: judge whether the grayscale value of the target pixel falls within the third characteristic value range.
  • the characteristic value range is determined based on experimental data
  • the experimental data includes: data on the impact of different shooting parameters on the image features, data on the relationship between the number of exposure points contained in the gene image and the image features, and signal strength that does not affect image quality.
  • the shooting parameters include camera gain
  • the trigger module is specifically used for:
  • the camera is triggered to re-photograph the sample to be sequenced with the target parameter value of the camera gain.
  • the shooting parameters include camera gain
  • a target camera gain matching the current shooting scene is determined.
  • the embodiment of the present invention further provides a gene image acquisition device, the device comprising:
  • An acquisition module used to acquire a first gene image obtained by photographing a sequencing sample by a camera based on a target wavelength range of light, and to acquire a preset characteristic condition corresponding to the target wavelength range;
  • a determination module used to determine a target parameter value of a shooting parameter according to the image feature of the first gene image and the preset feature condition
  • the trigger module is used to trigger the camera to re-shoot the sample to be sequenced with the target parameter value, so that the image characteristics of the second gene image obtained by the re-shooting meet the preset characteristic conditions.
  • the preset characteristic condition includes a characteristic value range
  • the acquisition modules include:
  • An acquisition unit used for acquiring a historical gene image corresponding to a target wavelength range
  • a first determining unit configured to determine a correlation between a feature value of a historical gene image and a number of exposure points of the historical gene image
  • a screening unit used to screen target historical gene images that meet sequencing quality conditions from the historical gene images
  • a second determination unit configured to determine a target exposure point range according to the target historical gene image
  • the third determining unit is used to determine the characteristic value range according to the target exposure point range and the association relationship.
  • the determination module is specifically used to determine the target camera gain according to a correspondence between predetermined image features, preset feature conditions and parameter values of shooting parameters.
  • the target camera gain for shooting the second gene image is smaller than the camera gain for shooting the first gene image. That is, there is a situation where the parameter value (camera gain) is merged toward a low value, such as AT corresponding to a low value merge, CG merge toward a low value merge; or wavelengths similar to a low value merge.
  • a low value such as AT corresponding to a low value merge, CG merge toward a low value merge; or wavelengths similar to a low value merge.
  • An embodiment of the present invention also provides a gene sequencing system, comprising: a sequencing device and a gene image acquisition device; the gene image acquisition device is used to acquire a gene image through the gene image acquisition method provided by any of the above embodiments; the sequencing device is used to perform gene sequencing on the sequencing sample according to the gene image.
  • the relevant parts can refer to the partial description of the method embodiments.
  • the device and system embodiments described above are only schematic, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of the present invention. Ordinary technicians in this field can understand and implement it without paying creative work.
  • FIG6 is a schematic diagram of an electronic device according to an exemplary embodiment of the present invention, showing a block diagram of an exemplary electronic device 60 suitable for implementing the present invention.
  • the electronic device 60 shown in FIG6 is only an example and should not limit the functions and scope of use of the present invention.
  • the electronic device 60 may be in the form of a general-purpose computing device, for example, it may be a server device.
  • the components of the electronic device 60 may include, but are not limited to: at least one processor 61, at least one memory 62, and a bus 63 connecting different system components (including the memory 62 and the processor 61).
  • the bus 63 includes a data bus, an address bus, and a control bus.
  • the memory 62 may include a volatile memory, such as a random access memory (RAM) 621 and/or a cache memory 622 , and may further include a read-only memory (ROM) 623 .
  • RAM random access memory
  • ROM read-only memory
  • the memory 62 may also include a program tool 625 (or utility) having a set (at least one) of program modules 624, such program modules 624 including but not limited to: an operating system, one or more application programs, other program modules, and program data, each of which or some combination may include an implementation of a network environment.
  • program tool 625 or utility
  • program modules 624 including but not limited to: an operating system, one or more application programs, other program modules, and program data, each of which or some combination may include an implementation of a network environment.
  • the processor 61 executes various functional applications and data processing by running the computer program stored in the memory 62, such as the method provided in any of the above embodiments.
  • the electronic device 60 may also communicate with one or more external devices 64 (e.g., keyboards, pointing devices, etc.). Such communication may be performed via an input/output (I/O) interface 65.
  • the model-generated electronic device 60 may also communicate with one or more networks (e.g., a local area network (LAN), a wide area network (WAN), and/or a public network, such as the Internet) via a network adapter 66. As shown, the network adapter 66 communicates with other modules of the model-generated electronic device 60 via a bus 63.
  • networks e.g., a local area network (LAN), a wide area network (WAN), and/or a public network, such as the Internet
  • model-generated electronic device 60 including but not limited to: microcode, device drivers, redundant processors, external disk drive arrays, RAID (disk array) systems, tape drives, and data backup storage systems, etc.
  • An embodiment of the present invention further provides a computer-readable storage medium having a computer program stored thereon, and when the program is executed by a processor, the method provided by any of the above embodiments is implemented.
  • the readable storage medium may include but is not limited to: a portable disk, a hard disk, a random access memory, a read-only memory, an erasable programmable read-only memory, an optical storage device, a magnetic storage device or any suitable combination of the above.
  • the embodiment of the present invention may also be implemented in the form of a program product, which includes a program code.
  • the program product runs on a terminal device, the program code is used to enable the terminal device to execute a method for implementing any of the above embodiments.
  • the program code for executing the present invention may be written in any combination of one or more programming languages, and may be executed entirely on a user device, partially on a user device, as an independent software package, partially on a user device and partially on a remote device, or entirely on a remote device.

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Abstract

本发明涉及一种基因测序方法及系统、基因图像获取方法及装置一种基因图像获取方法，其中基因图像获取方法包括：获取相机对待测序样本进行拍摄得到的基因图像；判断所述基因图像的图像特征是否符合预设特征条件；在判断结果为否的情况下，确定与当前拍摄场景相匹配的拍摄参数的目标参数值；触发所述相机以所述目标参数值对所述待测序样本进行重新拍摄，以使所述重新拍摄得到的基因图像的图像特征符合预设特征条件。从而能够为基因测序提供符合基因测序需求的基因图像，进而能够实现有效的基因测序，整体提高基因测序的效率和准确性。

Description

基因测序方法及系统、基因图像获取方法及装置 技术领域
本发明涉及基因测试技术领域，尤其涉及一种基因测序方法及系统、基因图像获取方法及装置。
背景技术
二代基因测序技术是通过不同染料标记追踪不同碱基，由激光激发待测序样品产生荧光，经由成像系统检测分析各碱基的荧光信号值来完成的。因此每个碱基的荧光信号值会直接影响测序的质量和准确度，荧光信号过高会增加荧光串扰，荧光信号过低会使碱基无法识别。
发明内容
本申请的主要目的在于，提供一种基因测序方法及系统、基因图像获取方法及装置、电子设备和存储介质，以改善现有技术中存在的上述缺陷。
第一方面，提供一种基因图像获取方法，包括：
获取相机对待测序样本进行拍摄得到的基因图像；
判断所述基因图像的图像特征是否符合预设特征条件；
在判断结果为否的情况下，确定与当前拍摄场景相匹配的拍摄参数的目标参数值；
触发所述相机以所述目标参数值对所述待测序样本进行重新拍摄，以使所述重新拍摄得到的基因图像的图像特征符合预设特征条件。
可选地，所述图像特征的数量为至少两个，所述预设特征条件包括各个图像特征的特征值范围；
判断所述基因图像的图像特征是否符合预设特征条件，包括：
判断各个图像特征的特征值是否均落入对应的特征值范围。
可选地，所述图像特征包括灰度值的中位数，预设特征条件包括第一特征值范围；判断所述基因图像的图像特征是否符合预设特征条件，包括：判断所述灰度值的中位数是否落入第一特征值范围；
和/或，所述图像特征包括灰度值的平均值，预设特征包括第二特征值范围；判断所述基因图像的图像特征是否符合预设特征条件，包括：判断所述灰度值的平均值是否落入第二特征值范围；
和/或，所述图像特征包括目标像素点的灰度值，预设特征包括第三特征值范围；判断所述基因图像的图像特征是否符合预设特征条件，包括：判断所述目标像素点的灰度值是否落入第三特征值范围。
可选地，特征值范围根据实验数据确定，所述实验数据包括：不同的拍摄参数对所述图像特征的影响数据、基因图像包含的曝光点数与所述图像特征的关系数据、不影响图像质量的信号强度。
可选地，所述拍摄参数包括相机增益；
触发所述相机以所述目标参数值对所述待测序样本进行重新拍摄，包括：
触发所述相机以所述相机增益的目标参数值对所述待测序样本进行重新拍摄。
可选地，所述拍摄参数包括相机增益；述
确定与当前拍摄场景相匹配的拍摄参数的目标参数值，包括：
根据预先确定的拍摄场景与相机增益的对应关系，确定与当前拍摄场景相匹配的目标相机增益。
第二方面，提供一种基因测序方法，包括：
获取待测序样本的基因图像，所述基因图像采用第一方面任一项所述的基因图像获取方法获取；
根据所述基因图像对所述测序样本进行基因测序。
第三方面，提供一种基因图像获取装置，包括：
获取模块，用于获取相机对待测序样本进行拍摄得到的基因图像；
判断模块，用于判断所述基因图像的图像特征是否符合预设特征条件，并在判断结果为否的情况下，调用确定模块；
所述确定模块，用于确定与当前拍摄场景相匹配的拍摄参数的目标参数值；
触发模块，用于触发所述相机以所述目标参数值对所述待测序样本进行重新拍摄，以使所述重新拍摄得到的基因图像的图像特征符合预设特征条件。
第四方面，提供一种基因测序系统，包括：测序装置以及基因图像获取装置；
所述基因图像获取装置，用于通过执行第一方面任一项所述的基因图像获取方法获取基因图像；
所述测序装置，用于根据所述基因图像对所述测序样本进行基因测序。
第五方面，提供一种电子设备，包括存储器、处理器及存储在存储器上并可在处理器上运行的计算机程序，所述处理器执行所述计算机程序时实现上述任一项所述的方法。
第六方面，提供一种计算机可读存储介质，其上存储有计算机程序，所述计算机程序被处理器执行时实现上述任一项所述的方法。
本申请的积极进步效果在于：
本发明提供的基因图像获取方法，能够为基因测序提供质量较好，符合基因测序需求的基因图像，避免基因测序测试过程中因图像质量不佳导致的测序中断，避免数据量的损失以及数据不可用，从而能够实现有效的基因测序，整体提高基因测序的效率和准确性。
附图说明
图1a为本发明一示例实施例提供的一种基因图像获取方法的流程图；
图1b为本发明一示例实施例提供的另一种基因图像获取方法的流程图；
图2a为本发明一示例实施例提供的一种不同的相机增益对基因图像的 灰度值的影响示意图；
图2b为本发明一示例实施例提供的一种基因图像包含的曝光点数与灰度值的中位数的关系示意图；
图3为本发明一示例实施例提供的一种基因测序方法的流程图；
图4a为本发明一示例实施例提供的一种效果对比图；
图4b为本发明一示例实施例提供的另一种效果对比图；
图5为本发明一示例性实施例提供的一种基因图像获取装置的模块示意图；
图6为本发明一示例性实施例提供的一种电子设备的模块示意图。
具体实施方式
图1a为本发明一示例性实施例提供的一种基因图像获取方法的流程图，该基因图像获取方法包括以下步骤：
步骤101a、获取相机对待测序样本进行拍摄得到的基因图像。
待测序样本包括包裹有目标物的检测球DNB、包裹有目标物的簇等。目标物例如细胞、生物组织或细菌及其反应物等；DNB(DNAnanoball)是DNA纳米球分子(一个DNB中包括多个相同的DNA序列)，属于一种DNA分子，DNB中DNA的数量可以是1个也可以是多个，本公开实施例对此不作特别限定。目标物的簇通过对目标物聚类得到。
获取基因图像时，一般将待测序样本置于测序芯片中，依据测序芯片上的图案特征点找到拍摄的起始位置，该位置能确保图像算法定位待测序样本的对应点位。拍摄得到的基因图像的分辨率大约2千万个像素，以待测序样本为DNA为例，基因图像包括了4百多万个DNA(或DNB)，每个亮点代表一个DNA片段中一个序列位置的碱基信息，两个DNA之间间隔约为2个像素；另外每张基因图像上有明显的间隔不同的分界线，分界线上的DNA距离不同，通过识别距离，确定拍摄位置，实现相机定位拍摄。一张图像对 应测序芯片的一个区域，为了识别出四种碱基，每个区域同时拍四张图像，四张图像由光学滤光系统分出不同波长的光，四种碱基发光波长不同，所以同一个区域的四张图像灰度值大小不同，亮点位置也不同。
需要说明的是，步骤101a中可以直接获取相机对待测序样本进行拍摄得到的基因图像；步骤101a中所获取的基因图像，也可是在基因测试过程中，从相机对待测序样本进行拍摄得到的基因图像中确定出的用于配准的基因图像，而无需额外、专门拍摄基因图像。
在一个实施例中，相机采用的拍摄参数的初始参数值可以根据经验确定。拍摄得到的基因图像用于基因测序。拍摄参数包括光源强度、透过率、曝光时间、检测器量子效率和相机增益等中的至少一项。
步骤102a、判断基因图像的图像特征是否符合预设特征条件。
图像特征表征基因图像的图像质量，判断图像特征是否符合预设特征条件，也即判断基因图像的图像质量是否符合要求，是否能实现有效的基因测序。
若判断结果为是，说明以相机当前的拍摄参数的参数值拍摄得到的基因图像的图像质量符合要求，可直接用于基因测序，无需对参数值进行调整后，也即无需执行步骤103a和步骤104a。
若判断结果为否，说明以相机当前的拍摄参数的参数值拍摄得到的基因图像的图像质量不符合要求，无法用于基因测序，进而说明当前的拍摄参数的参数值不适宜，需要重新确定参数值，则执行步骤103a和步骤104a。
需要说明的是，图像特征的数量可以为一个，也可以为多个。
当图像特征的数量为至少两个时，相对应的，预设特征条件包括对应数量的图像特征的特征值范围，步骤102a中则判断各个图像特征的特征值是否均落入对应的特征值范围。通过多个图像特征，能够对基因图像的图像质量作出多维度的评估，确保基因图像的图像质量符合后续基因测序的要求。
图像特征可以但不限于包括以下特征参数中的至少一种：灰度值的中位 数、灰度值的平均值、目标像素点的灰度值等。灰度值的中位数为基因图像中各像素点的灰度值的中位数。灰度值的平均值为基因图像中各像素点的灰度值的平均值。目标像素点可以根据实际需求自行确定，例如将基因图像的中心位置的像素点确定为目标像素点。目标像素点可以根据实际情况自行设置，例如对所有的像素点灰度值按照从高至低的顺序进行排序，取排序后的第n个灰度值对应的像素点确定为目标像素点；其中，n可以根据实际情况自行设置。n/像素数*100％即为其百分位点；例如，中位数也可称为50％位点。
在一个实施例中，图像特征包括灰度值的中位数，预设特征条件包括第一特征值范围。步骤102a中则判断灰度值的中位数是否落入第一特征值范围；若判断结果为是，说明基因图像的图像质量符合基因测序要求，可直接用于基因测序；若判断结果为否，说明基因图像的图像质量不符合图像测序要求，需要对拍摄参数的参数值进行调整，并重新获取基因图像。
拍摄对应的区域可能本身会有异常的亮斑或黑斑，通过灰度值的中位数来表征整张图像的图像特征，可以排除个别像素点的异常干扰。
在一个实施例中，图像特征包括灰度值的平均值，预设特征条件包括第二特征值范围。步骤102a中则判断灰度值的平均值是否落入第二特征值范围；若判断结果为是，说明基因图像的图像质量符合基因测序要求，可直接用于基因测序；若判断结果为否，说明基因图像的图像质量不符合图像测序要求，需要对拍摄参数的参数值进行调整，并重新获取基因图像。
灰度值的平均值能够反映基因图像的整体状态，平均值能够很好的反映基因图像的图像特征。
在一个实施例中，图像特征包括目标像素点的灰度值，预设特征条件包括第三特征值范围。步骤102a中则判断目标像素点的灰度值是否落入第三特征值范围；若判断结果为是，说明基因图像的图像质量符合基因测序要求，可直接用于基因测序；若判断结果为否，说明基因图像的图像质量不符合图 像测序要求，需要对相机的拍摄参数进行调整，并重新获取基因图像。
在一个实施例中，将两个以上的图像特征作为图像质量好坏的判断依据，例如将灰度值的中位数和灰度值的平均值同时用来评价图像质量好坏，通过多个图像特征，能够对基因图像的图像质量作出多维度的评估，确保基因图像的图像质量符合后续基因测序的要求。
预设特征条件包含的第一特征值范围、第二特征值范围、第三特征值范围根据实验数据确定，实验数据包括：不同的拍摄参数对所述图像特征的影响数据、基因图像包含的曝光点数与图像特征的关系数据、不影响图像质量的信号强度。
下面介绍确定特征值范围的一种实现方式：
S1a、获取目标波长范围对应的历史基因图像。
S1a中的历史基因图像可以是从数据库中筛选出的目标波长范围的历史基因图像。数据库中预先存储有基于光的各类波长范围的历史基因图像。
S2a、确定历史基因图像的特征值与历史基因图像的曝光点数的关联关系。
该关联关系可以是对数据库中的历史基因图像拟合得到。
S3a、从历史基因图像中筛选符合测序质量条件的目标历史基因图像。
测序质量条件可以根据实际需求自行确定，确定出的目标历史基因图像为质量较好的基因图像，该基因图像的特征值对评价图像质量具有参考意义。
S4a、根据目标历史基因图像确定目标曝光点数范围。
S5a、根据目标曝光点数范围和关联关系确定特征值范围。
上述第一特征值范围、第二特征值范围、第三特征值范围均可通过S1a～S5a确定。
本发明实施例中，根据符合测序质量条件的目标历史基因图像确定特征值范围，所确定的特征值范围具有实际的参考意义，准确性高。下面以图像特征为灰度值的中位数，拍摄参数为相机增益为例，介绍确定第一特征值范 围(预设特征条件)的实现方式。
a.确定不同的相机增益对基因图像的灰度值的影响
统计实验阶段获取的基因图像的亮度的波动范围(包括不同DNA文库和制备，测序阶段(SE/PE/barcode)，参见图2a，不同相机增益亮度波动高达10倍。亮度波动是导致图像过曝或亮度信号过低的根本原因，想要将图像灰度值稳定在某个范围内，需要先知道目标波动范围有多大，才能制定对应的调节参数和方案。
测试不同的相机增益对同一个待测样本的图像灰度值的影响，然后以同一个相机增益去拍或者换算了不同待测样本的亮度的波动范围。
b.确定基因图像包含的曝光点数与灰度值的中位数的关系
统计过曝点数和基因图像的亮度的相关性，参见图2b，图中横坐标为该不同待测序样本的基因图像的灰度值的中位数，纵坐标为灰度值饱和的像素数，不同碱基的趋势基本一致，两者线性拟合后相关性80％以上。
测序过程中ACGT四种碱基各自结合了不同波长的染料，通过光学将不同波长的光成像到不同的相机上，同一个位置的四张图像分别以对应的波长命名为ACGT；但是染料发光的波长段是有重叠区域的，只有A碱基不被干扰，所以A对应的基因图像和CGT对应的基因图像需分别计算分析曝光点数。
c.确定不影响图像质量的信号强度
统计不影响测序质量的信号强度，得到需要达到的信号范围，取大量正常测序数据，该统计记录的是测序FQC合格的对应图像，FQC出货的指标包括了下机数据量、质量值、错误率、拆分率等，统计了近期出货的十几台仪器的图像。该信号强度可以通过基因图像各像素点的灰度值和/或过曝点数表征；其中，过曝点数为灰度值超过65472的像素点的数量。
下表按顺序分别为所有对应图像灰度值的中位数的平均值、灰度值的平均数的平均值、灰度值饱和点数(曝光点数)的平均值、第一个数和第二个 数的差值、参加统计的图像的灰度值饱和点数的标准差、第三个数和第五个数的和。
Figure PCTCN2022138731-appb-000001
根据上述实验数据可以得到正常基因图像的灰度值饱和点数的数量范围，从而倒推第一特征值范围。
第二特征值范围与第三特征值范围的确定方式与第一特征值范围类似，此处不再赘述。
本发明实施例中，预先确定特征值范围，在实际基因测序阶段或者基因图像获取阶段无需重复收集实验数据制定特征值范围，从而可以提高基因图像获取的效率，进而提高基因测序的效率。
步骤103a、确定与当前拍摄场景相匹配的拍摄参数的目标参数值。
目标参数值为与当前拍摄场景相匹配的拍摄参数的参数值，包括光源强度、系统透过率、曝光时间、检测器量子效率和相机增益等拍摄参数中的至少一种参数的参数值。
经实验可知，测序芯片的材质、环境亮度、待测序样本的种类、待测序样本的数量、染料材质、光源强度等均与基因图像的亮度有关，因此拍摄场景可以但不限于通过以下参数中的至少一种表征：测序芯片的材质、环境亮度、待测序样本的种类、待测序样本的数量等。
相机采用重新确定的目标参数值中对待测序样本进行拍摄，能够得到图像质量符合基因测序需求的基因图像。
在一个实施例中，重新确定与当前拍摄场景相匹配的相机增益的参数值，而无需确定其他拍摄参数的参数值。相机增益的改变不会影响荧光发射的光子数，不会改变基因图像的信噪比，且能确保亮度信号可以线性调节，因此实施难度较低且较稳定，也不会延长拍摄时间，因此通过调节相机的相机增益，来达到不影响图像获取时间以及提高图像质量的目的。
在一个实施例中，根据预先确定的拍摄场景与拍摄参数的对应关系，确定与当前拍摄场景相匹配的目标拍摄参数。具体的，获取确定预设特征条件时得到的实验数据，通过对该实验数据进行拟合得到对应关系。
在一个实施例中，根据预先训练的拍摄参数确定模型确定与当前拍摄场景相匹配的目标拍摄参数。拍摄参数确定模型根据获取确定预设特征条件时得到的实验数据(训练样本)对神经网络训练得到，拍摄参数确定模型的输入参数包括与拍摄场景相关的参数，输出参数为拍摄参数。确定目标参数值时，将实验数据包含的与当前拍摄场景相关的参数的参数值输入拍摄参数确定模型，即可根据拍摄参数确定模型确定与当前拍摄场景相匹配的拍摄参数的目标参数值。
下面以图像特征为灰度值的中位数为例，介绍确定相机增益的一种实现方式。
根据上述实验数据可得到，图像的灰度值的中位数在23000以下可以使图像不过曝。而基于PE150(双端测序)的一链自动调相机增益的一般结果，大部分调节后仍为3，只有极少数样本在一链调节为2，所以一链相机增益的方案定为在3/2之间调节；即在一链测序时，以相机增益为3拍图，当对应的图像中位数小于23000时，相机增益设置为3，大于23000时，相机增益设置为2，AT波长对应的两个相机使用同样的配置，以相机增益较低的为准，CG波长对应的两个相机使用同样的配置，以相机增益较低的为准。
基于PE150的二链自动调相机增益的一般结果，以及一般过曝后设固定值为2的临时操作来看，二链翻倍相机增益设为2是符合大部分应用数据 的，但也有小部分应用在相机增益为2的时候也有过曝的风险，所以二链相机增益的方案定为在2/1之间调节；即在二链测序时，以相机增益为2拍图，当判定的图像中位数小于23000时，相机增益设置为2，大于23000时，相机增益设置为1，AT波长对应的两个相机使用同样的配置，以相机增益较低的为准，CG波长对应的两个相机使用同样的配置，以相机增益较低的为准。
基于部分barcode标签与二链共用相机增益过曝的现象，以及此前测试中不同相机增益barcode部分的质量数据表现，将PE(双端测序)的barcode相机增益固定为1，SE(单端测序)的barcode相机增益固定为2。
由上可知目标相机增益小于步骤101a中拍摄基因图像的相机增益。也即存在目标相机增益向低值合并的情况，如AT对应向低值合并，CG向低值合并；或波长相近的向低值合并。
步骤104a、触发相机以目标参数值对待测序样本进行重新拍摄，以使重新拍摄的基因图像与预设特征相匹配。
当拍摄参数包括相机增益时，则触发相机以与当前拍摄场景相匹配的相机增益对待测序样本进行重新拍摄，以使重新拍摄的基因图像与预设特征相匹配。
本发明实施例提供过的基因图像获取方法，能够为基因测序提供质量较好，符合基因测序需求的基因图像，避免基因测序测试过程中因图像质量不佳导致的测序中断(例如无法进行图像配准或无法自动找焦面)，避免数据量的损失以及数据不可用，从而能够实现有效的基因测序，整体提高基因测序的效率和准确性。
因拍摄场景不可控，会导致待测序样本产生的荧光信号不可控，进而导致基因图像的亮度不可控，较难获取质量较好的基因图像，通过对相机增益的线性调节，即可确定与当前拍摄场景相匹配的相机增益，操作便捷，且基于该相机增益拍摄得到的基因图像亮度适中，图像质量较好。本发明实施例中还能实现同一张基因图像不同区域分别使用不同的相机增益，使基因图片 达到整体亮度适中的效果。
图1b为本发明一示例性实施例提供的另一种基因测序方法的流程图，该基因测序方法包括以下步骤：
步骤101b、基于光的目标波长范围获取相机对测序样本进行拍摄得到的第一基因图像。
其中，光的目标波长范围可以根据实际情况自行确定。
步骤102b、获取目标波长范围对应的预设特征条件。
在一个实施例中，步骤102b包括：
S1b、获取目标波长范围对应的历史基因图像；
S2b、确定历史基因图像的特征值与历史基因图像的曝光点数的关联关系；
S3b、从历史基因图像中筛选符合测序质量条件的目标历史基因图像；
S4b、根据目标历史基因图像确定目标曝光点数范围；
S5b、根据目标曝光点数范围和关联关系确定特征值范围。
步骤S1b～S5b的具体实现方式与S1a～S5a相同，此处不再赘述。
步骤103b、根据第一基因图像的图像特征和预设特征条件确定拍摄参数的目标参数值。
在一个实施例中，步骤103b包括：根据预先确定的图像特征、预设特征条件与拍摄参数的参数值的对应关系，确定目标相机增益。
该对应关系可预先对图像特征、预设特征条件与拍摄参数的参数值拟合得到，根据该对应关系，即可确定与第一基因图像的图像特征和预设特征条件相匹配的拍摄参数的目标参数值。
步骤104b、触发相机以目标参数值对待测序样本进行重新拍摄，以使重新拍摄得到的第二基因图像的图像特征符合预设特征条件。
本发明实施例提供过的基因图像获取方法，能够为基因测序提供质量较好，符合基因测序需求的基因图像，避免基因测序测试过程中因图像质量不 佳导致的测序中断(例如无法进行图像配准或无法自动找焦面)，避免数据量的损失以及数据不可用，从而能够实现有效的基因测序，整体提高基因测序的效率和准确性。
图3为本发明一示例实施例提供的一种基因测序方法的流程图，该基因测序方法包括：
步骤301、获取待测序样本的基因图像。
其中，该基因图像采用上述任一实施例提供的基因图像获取方法获取得到。
步骤303、根据基因图像对测序样本进行基因测序。
本发明实施例获取的基因图像均符合基因测序需求，根据该基因图像能够实现对测序样本的有效测序，且准确率和效率均较高。
在把一张芯片都拍摄完成之后，会做生化切除合成反应，把已经拍过图像的碱基结合的染料洗掉，让这条链的下一个碱基结合新的染料，所以之后同一个DNA点位发出光的波长可能会不同，通过每次拍摄在不同的图像上得到的灰度值来判断其碱基类型，从而最终组合得出这一条DNA链的序列。
参见图4a和图4b，图中一部分设置为自动调增益，一部分设置为其他条件的默认参数。该测试增益的自动调节结果一链ATGC为3333，二链为1122，即一链AT增益为3，GC增益为3，二链AT增益为1，CG增益为2，barcode四个通道增益都为1。碱基AT是互补对，碱基CG是互补对，理论上AT的碱基含量一致，CG的碱基含量一致，上图横轴为测序的cycle数，纵轴分别为AT和CG含量的差值，数据越接近于0越好，但如果所有配置结果一致的话，说明是别的原因导致了碱基分离，此测试是为了对比说明自动调节增益之后的结果相对最好。自动调节的结果碱基分布正常，且下机错误率和比对率mappingrate均较好。
与前述基因测序方法、基因图像获取方法实施例相对应，本发明还提供了基因测序装置、基因图像获取装置的实施例。
图5为本发明一示例性实施例提供的一种基因图像获取装置的模块示意图，该基因图像获取装置包括：
获取模块51，用于获取相机对待测序样本进行拍摄得到的基因图像；
判断模块52，用于判断所述基因图像的图像特征是否符合预设特征条件，并在判断结果为否的情况下，调用确定模块；
所述确定模块53，用于确定与当前拍摄场景相匹配的拍摄参数的目标参数值；
触发模块54，用于触发所述相机以所述目标参数值对所述待测序样本进行重新拍摄，以使所述重新拍摄得到的基因图像的图像特征符合预设特征条件。
可选地，所述图像特征的数量为至少两个，所述预设特征条件包括各个图像特征的特征值范围；
判断模块具体用于：
判断各个图像特征的特征值是否均落入对应的特征值范围。
可选地，所述图像特征包括灰度值的中位数，预设特征条件包括第一特征值范围；判断模块具体用于：判断所述灰度值的中位数是否落入第一特征值范围；
和/或，所述图像特征包括灰度值的平均值，预设特征包括第二特征值范围；判断模块具体用：判断所述灰度值的平均值是否落入第二特征值范围；
和/或，所述图像特征包括目标像素点的灰度值，预设特征包括第三特征值范围；判断模块具体用：判断所述目标像素点的灰度值是否落入第三特征值范围。
可选地，特征值范围根据实验数据确定，所述实验数据包括：不同的拍摄参数对所述图像特征的影响数据、基因图像包含的曝光点数与所述图像特征的关系数据、不影响图像质量的信号强度。
可选地，所述拍摄参数包括相机增益；
触发模块具体用于：
触发所述相机以所述相机增益的目标参数值对所述待测序样本进行重新拍摄。
可选地，所述拍摄参数包括相机增益；
确定模块具体用于：
根据预先确定的拍摄场景与相机增益的对应关系，确定与当前拍摄场景相匹配的目标相机增益。
本发明实施例还提供一种基因图像获取装置，该装置包括：
获取模块，用于基于光的目标波长范围获取相机对测序样本进行拍摄得到的第一基因图像，并获取所述目标波长范围对应的预设特征条件；
确定模块，用于根据所述第一基因图像的图像特征和所述预设特征条件确定拍摄参数的目标参数值；
触发模块，用于触发所述相机以所述目标参数值对所述待测序样本进行重新拍摄，以使所述重新拍摄得到的第二基因图像的图像特征符合所述预设特征条件。
可选地，所述预设特征条件包括特征值范围；
获取模块包括：
获取单元，用于获取目标波长范围对应的历史基因图像；
第一确定单元，用于确定历史基因图像的特征值与所述历史基因图像的曝光点数的关联关系；
筛选单元，用于从所述历史基因图像中筛选符合测序质量条件的目标历史基因图像；
第二确定单元，用于根据所述目标历史基因图像确定目标曝光点数范围；
第三确定单元，用于根据所述目标曝光点数范围和所述关联关系确定所述特征值范围。
可选地，所述确定模块具体用于：根据预先确定的图像特征、预设特征 条件与拍摄参数的参数值的对应关系，确定所述目标相机增益。
可选地，拍摄第二基因图像的目标相机增益小于拍摄第一基因图像的相机增益。也即存在参数值(相机增益)向低值合并的情况，如AT对应向低值合并，CG向低值合并；或波长相近的向低值合并。
本发明实施例还提供一种基因测序系统，包括：测序装置以及基因图像获取装置；所述基因图像获取装置用于通过上述任一实施例提供的基因图像获取方法获取基因图像；所述测序装置用于根据所述基因图像对所述测序样本进行基因测序。
对于装置、系统实施例而言，由于其基本对应于方法实施例，所以相关之处参见方法实施例的部分说明即可。以上所描述的装置、系统实施例仅仅是示意性的，其中所述作为分离部件说明的单元可以是或者也可以不是物理上分开的，作为单元显示的部件可以是或者也可以不是物理单元，即可以位于一个地方，或者也可以分布到多个网络单元上。可以根据实际的需要选择其中的部分或者全部模块来实现本发明方案的目的。本领域普通技术人员在不付出创造性劳动的情况下，即可以理解并实施。
图6为本发明一示例实施例示出的一种电子设备的结构示意图，示出了适于用来实现本发明实施方式的示例性电子设备60的框图。图6显示的电子设备60仅仅是一个示例，不应对本发明实施例的功能和使用范围带来任何限制。
如图6所示，电子设备60可以以通用计算设备的形式表现，例如其可以为服务器设备。电子设备60的组件可以包括但不限于：上述至少一个处理器61、上述至少一个存储器62、连接不同系统组件(包括存储器62和处理器61)的总线63。
总线63包括数据总线、地址总线和控制总线。
存储器62可以包括易失性存储器，例如随机存取存储器(RAM)621和/或高速缓存存储器622，还可以进一步包括只读存储器(ROM)623。
存储器62还可以包括具有一组(至少一个)程序模块624的程序工具625(或实用工具)，这样的程序模块624包括但不限于：操作系统、一个或者多个应用程序、其它程序模块以及程序数据，这些示例中的每一个或某种组合中可能包括网络环境的实现。
处理器61通过运行存储在存储器62中的计算机程序，从而执行各种功能应用以及数据处理，例如上述任一实施例所提供的方法。
电子设备60也可以与一个或多个外部设备64(例如键盘、指向设备等)通信。这种通信可以通过输入/输出(I/O)接口65进行。并且，模型生成的电子设备60还可以通过网络适配器66与一个或者多个网络(例如局域网(LAN)，广域网(WAN)和/或公共网络，例如因特网)通信。如图所示，网络适配器66通过总线63与模型生成的电子设备60的其它模块通信。应当明白，尽管图中未示出，可以结合模型生成的电子设备60使用其它硬件和/或软件模块，包括但不限于：微代码、设备驱动器、冗余处理器、外部磁盘驱动阵列、RAID(磁盘阵列)系统、磁带驱动器以及数据备份存储系统等。
应当注意，尽管在上文详细描述中提及了电子设备的若干单元/模块或子单元/模块，但是这种划分仅仅是示例性的并非强制性的。实际上，根据本发明的实施方式，上文描述的两个或更多单元/模块的特征和功能可以在一个单元/模块中具体化。反之，上文描述的一个单元/模块的特征和功能可以进一步划分为由多个单元/模块来具体化。
本发明实施例还提供一种计算机可读存储介质，其上存储有计算机程序，所述程序被处理器执行时实现上述任一实施例所提供的方法。
其中，可读存储介质可以采用的更具体可以包括但不限于：便携式盘、硬盘、随机存取存储器、只读存储器、可擦拭可编程只读存储器、光存储器件、磁存储器件或上述的任意合适的组合。
在可能的实施方式中，本发明实施例还可以实现为一种程序产品的形式，其包括程序代码，当所述程序产品在终端设备上运行时，所述程序代码用于 使所述终端设备执行实现上述任一实施例的方法。
其中，可以以一种或多种程序设计语言的任意组合来编写用于执行本发明的程序代码，所述程序代码可以完全地在用户设备上执行、部分地在用户设备上执行、作为一个独立的软件包执行、部分在用户设备上部分在远程设备上执行或完全在远程设备上执行。
虽然以上描述了本发明的具体实施方式，但是本领域的技术人员应当理解，这些仅是举例说明，在不背离本发明的原理和实质的前提下，可以对这些实施方式做出多种变更或修改。因此，本发明的保护范围由所附权利要求书限定。

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  1. 一种基因图像获取方法，其特征在于，包括：
    获取相机对待测序样本进行拍摄得到的基因图像；
    判断所述基因图像的图像特征是否符合预设特征条件；
    在判断结果为否的情况下，确定与当前拍摄场景相匹配的拍摄参数的目标参数值；
    触发所述相机以所述目标参数值对所述待测序样本进行重新拍摄，以使所述重新拍摄得到的基因图像的图像特征符合预设特征条件。
  2. 根据权利要求1所述的基因图像获取方法，其特征在于，所述图像特征的数量为至少两个，所述预设特征条件包括各个图像特征的特征值范围；
    判断所述基因图像的图像特征是否符合预设特征条件，包括：
    判断各个图像特征的特征值是否均落入对应的特征值范围。
  3. 根据权利要求1所述的基因图像获取方法，其特征在于，所述图像特征包括灰度值的中位数，预设特征条件包括第一特征值范围；判断所述基因图像的图像特征是否符合预设特征条件，包括：判断所述灰度值的中位数是否落入第一特征值范围；
    和/或，所述图像特征包括灰度值的平均值，预设特征包括第二特征值范围；判断所述基因图像的图像特征是否符合预设特征条件，包括：判断所述灰度值的平均值是否落入第二特征值范围；
    和/或，所述图像特征包括目标像素点的灰度值，预设特征包括第三特征值范围；判断所述基因图像的图像特征是否符合预设特征条件，包括：判断所述目标像素点的灰度值是否落入第三特征值范围。
  4. 根据权利要求2所述的基因图像获取方法，其特征在于，特征值范围根据实验数据确定，所述实验数据包括：不同的拍摄参数对所述图像特征的影响数据、基因图像包含的曝光点数与所述图像特征的关系数据、不影响图 像质量的信号强度。
  5. 根据权利要求1所述的基因图像获取方法，其特征在于，所述拍摄参数包括相机增益；
    触发所述相机以所述目标参数值对所述待测序样本进行重新拍摄，包括：
    触发所述相机以所述相机增益的目标参数值对所述待测序样本进行重新拍摄。
  6. 根据权利要求1-5中任一项所述的基因图像获取方法，其特征在于，所述拍摄参数包括相机增益；
    确定与当前拍摄场景相匹配的拍摄参数的目标参数值，包括：
    根据预先确定的拍摄场景与相机增益的对应关系，确定与当前拍摄场景相匹配的目标相机增益。
  7. 根据权利要求1-5中任一项所述的基因图像获取方法，其特征在于，所述预设特征条件包括特征值范围；所述基因图像获取方法还包括：
    确定历史基因图像的特征值与所述历史基因图像的曝光点数的关联关系；所述历史基因图像为基于光的目标波长范围获取的基因图像；
    从所述历史基因图像中筛选符合测序质量条件的目标历史基因图像；
    根据所述目标历史基因图像确定目标曝光点数范围；
    根据所述目标曝光点数范围和所述关联关系确定所述特征值范围。
  8. 一种基因图像获取方法，其特征在于，包括：
    基于光的目标波长范围获取相机对测序样本进行拍摄得到的第一基因图像；
    获取所述目标波长范围对应的预设特征条件；
    根据所述第一基因图像的图像特征和所述预设特征条件确定拍摄参数的目标参数值；
    触发所述相机以所述目标参数值对待测序样本进行重新拍摄，以使所述重新拍摄得到的第二基因图像的图像特征符合所述预设特征条件。
  9. 根据权利要求8所述的基因图像获取方法，其特征在于，所述预设特征条件包括特征值范围；
    所述获取所述目标波长范围对应的预设特征条件包括：
    获取目标波长范围对应的历史基因图像；
    确定历史基因图像的特征值与所述历史基因图像的曝光点数的关联关系；
    从所述历史基因图像中筛选符合测序质量条件的目标历史基因图像；
    根据所述目标历史基因图像确定目标曝光点数范围；
    根据所述目标曝光点数范围和所述关联关系确定所述特征值范围。
  10. 根据权利要求8或9所述的基因图像获取方法，其特征在于，所述拍摄参数包括相机增益；所述根据所述第一基因图像的图像特征和所述预设特征条件确定拍摄参数的目标参数值包括：
    根据预先确定的图像特征、预设特征条件与拍摄参数的参数值的对应关系，确定目标相机增益。
  11. 根据权利要求10所述的基因图像获取方法，其特征在于，拍摄第二基因图像的目标相机增益小于拍摄第一基因图像的相机增益。
  12. 一种基因测序方法，其特征在于，包括：
    获取待测序样本的基因图像，所述基因图像采用权利要求1-11中任一项所述的基因图像获取方法获取；
    根据所述基因图像对所述测序样本进行基因测序。
  13. 一种基因图像获取装置，其特征在于，包括：
    获取模块，用于获取相机对待测序样本进行拍摄得到的基因图像；
    判断模块，用于判断所述基因图像的图像特征是否符合预设特征条件，并在判断结果为否的情况下，调用确定模块；
    所述确定模块，用于确定与当前拍摄场景相匹配的拍摄参数的目标参数值；
    触发模块，用于触发所述相机以所述目标参数值对所述待测序样本进行重新拍摄，以使所述重新拍摄得到的基因图像的图像特征符合预设特征条件。
  14. 一种基因图像获取装置，其特征在于，包括：
    获取模块，用于基于光的目标波长范围获取相机对测序样本进行拍摄得到的第一基因图像，并获取所述目标波长范围对应的预设特征条件；
    确定模块，用于根据所述第一基因图像的图像特征和所述预设特征条件确定拍摄参数的目标参数值；
    触发模块，用于触发所述相机以所述目标参数值对待测序样本进行重新拍摄，以使所述重新拍摄得到的第二基因图像的图像特征符合所述预设特征条件。
  15. 一种基因测序系统，其特征在于，包括：测序装置以及基因图像获取装置；
    所述基因图像获取装置，用于通过执行权利要求1-11中任一项所述的基因图像获取方法获取基因图像；
    所述测序装置，用于根据所述基因图像对所述测序样本进行基因测序。
  16. 一种电子设备，包括存储器、处理器及存储在存储器上并可在处理器上运行的计算机程序，其特征在于，所述处理器执行所述计算机程序时实现权利要求1至12任一项所述的方法。
  17. 一种计算机可读存储介质，其上存储有计算机程序，其特征在于，所述计算机程序被处理器执行时实现权利要求1至12任一项所述的方法。
PCT/CN2022/138731 2022-12-13 2022-12-13 基因测序方法及系统、基因图像获取方法及装置 Ceased WO2024124402A1 (zh)

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CN105629780A (zh) * 2014-12-01 2016-06-01 深圳华大基因研究院 基因测序仪的控制装置、方法和基因测序仪
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