Quality detection method, device and equipment for space-time group positioning chip and storage medium

Abstract

The invention provides a quality detection method and device for a space-time group positioning chip, equipment and a storage medium, and the method comprises the steps: obtaining a sequencing result of a to-be-detected chip, and generating a basic group quality distribution diagram of the to-be-detected chip according to the sequencing result of the to-be-detected chip; performing quality detection on the to-be-detected chip according to the basic group quality distribution diagram to obtain a quality index of the to-be-detected chip; the quality index comprises at least one of a low quality sequence proportion, a maximum hot spot area, a hot spot number, a hot spot area standard deviation and a hot spot total area; and determining a quality detection result of the to-be-detected chip according to the quality index of the to-be-detected chip and a preset quality index threshold. According to the scheme, all the quality indexes of the chip to be detected are obtained by analyzing the basic group quality distribution diagram of the chip to be detected, then the quality detection result is determined according to the quality indexes, obviously, the quality detection result obtained through image analysis has higher accuracy than a result recognized by naked eyes, and the detection efficiency of the detection mode is higher.

Description

Quality detection method, device, equipment and storage medium of spatiotemporal group positioning chip Technical Field

[0001] The present application relates to the technical field of spatiotemporal group positioning chips, and in particular to a quality detection method, apparatus, device and storage medium for a spatiotemporal group positioning chip. Background Art

[0002] Spatial transcriptomics is a commonly used sequencing technology in the field of gene sequencing. Spatiotemporal mapping chips play a crucial role in the sequencing process based on spatial transcriptomics. Therefore, the quality of these chips is directly related to the accuracy of the sequencing results. However, there is no technical solution for detecting the quality of spatiotemporal mapping chips in the relevant technical field. Currently, the quality of spatiotemporal mapping chips mainly relies on visual inspection.

[0003] Therefore, the quality detection of spatiotemporal group positioning chips has become an urgent problem to be solved in the process of developing spatial transcriptome technology.

[0004] Summary of the Invention

[0005] The present application provides a method, apparatus, device and storage medium for detecting the quality of a spatiotemporal group positioning chip to solve the problem of detecting the quality of a spatiotemporal group positioning chip.

[0006] In a first aspect, the present application provides a method for detecting the quality of a spatiotemporal group positioning chip, comprising:

[0007] Obtaining sequencing results of the chip to be tested, and generating a base quality distribution map of the chip to be tested according to the sequencing results of the chip to be tested;

[0008] Performing a quality test on the chip to be tested according to the base quality distribution map to obtain a quality index of the chip to be tested; wherein the quality index of the chip to be tested includes at least one of the proportion of low-quality sequences, the maximum bright spot area, the number of bright spots, the standard deviation of the bright spot area, and the total bright spot area;

[0009] A quality inspection result of the chip to be tested is determined according to the quality index of the chip to be tested and a preset quality index threshold.

[0010] A second aspect of the present application provides a quality detection device for a spatiotemporal group positioning chip, comprising:

[0011] an obtaining unit, configured to obtain a sequencing result of the chip to be tested, and generate a base quality distribution map of the chip to be tested according to the sequencing result of the chip to be tested;

[0012] a detection unit, configured to perform a quality detection on the chip to be tested according to the base quality distribution map to obtain a quality index of the chip to be tested; wherein the quality index of the chip to be tested includes at least one of the proportion of low-quality sequences, the maximum bright spot area, the number of bright spots, the standard deviation of the bright spot area, and the total bright spot area;

[0013] The determining unit is configured to determine a quality detection result of the chip to be tested based on a quality index of the chip to be tested and a preset quality index threshold.

[0014] A third aspect of the present application provides an electronic device, including a memory and a processor;

[0015] Wherein, the memory is used to store computer programs;

[0016] The processor is used to execute the computer program, and when the computer program is executed, it is specifically used to implement the quality detection method of the spatiotemporal group positioning chip provided by any one of the first aspects of the present application.

[0017] The fourth aspect of the present application provides a computer storage medium for storing a computer program. When the computer program is executed, it is specifically used to implement the quality detection method of the spatiotemporal group positioning chip provided in any one of the first aspects of the present application.

[0018] The present application provides a method, apparatus, device, and storage medium for quality detection of a spatiotemporal group positioning chip. The method includes obtaining sequencing results of a chip to be tested and generating a base quality distribution map of the chip to be tested based on the sequencing results of the chip to be tested; performing a quality detection on the chip to be tested based on the base quality distribution map to obtain a quality index of the chip to be tested; the quality index includes at least one of the proportion of low-quality sequences, maximum bright spot area, number of bright spots, standard deviation of bright spot area, and total bright spot area; and determining a quality detection result of the chip to be tested based on the quality index of the chip to be tested and a preset quality index threshold. This solution obtains various quality indexes of the chip to be tested by analyzing the base quality distribution map of the chip to be tested, and then determines a quality detection result based on the quality index. It is clear that the quality detection results obtained through image analysis have higher accuracy than those obtained by visual recognition, and this detection method also has higher detection efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] FIG1 is a flow chart of a quality detection method for a spatiotemporal group positioning chip provided in an embodiment of the present application;

[0020] FIG2 is an example diagram of a Q10 heat map generated based on sequencing data of a chip to be tested, provided in an embodiment of the present application;

[0021] FIG3 is a partially enlarged schematic diagram of a Q10 heat map generated based on sequencing data of a chip to be tested, provided in an embodiment of the present application;

[0022] FIG4 is a flow chart of a method for performing quality inspection on a chip to be tested based on a Q10 heat map according to an embodiment of the present application;

[0023] FIG5 is a schematic diagram of a white edge in a preprocessing heat map provided in an embodiment of the present application;

[0024] FIG6 is a schematic diagram of a highlighted area in a preprocessed heat map provided in an embodiment of the present application;

[0025] FIG7 is a schematic diagram of a field of view missing area in a pre-processed heat map provided in an embodiment of the present application;

[0026] FIG8 is a schematic diagram of the distribution of bright spots in a pre-processed heat map provided in an embodiment of the present application;

[0027] FIG9 is a schematic diagram of the distribution of bright spots in another pre-processed heat map provided in an embodiment of the present application;

[0028] FIG10 is a diagram illustrating an example of cutting a chip to be tested provided in an embodiment of the present application;

[0029] FIG11 is a schematic diagram showing the relationship between the matching ratio and quality value of a sequencing result provided in an embodiment of the present application;

[0030] FIG12 is a schematic diagram showing the distribution of the maximum defect area of ​​a spatiotemporal group positioning chip provided by an embodiment of the present application;

[0031] FIG13 is a schematic diagram showing the distribution of the total defect area of ​​a spatiotemporal group positioning chip according to an embodiment of the present application;

[0032] FIG14 is a schematic structural diagram of a quality detection device for a spatiotemporal group positioning chip provided in an embodiment of the present application;

[0033] FIG15 is a schematic structural diagram of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0034] The terms "first," "second," "third," "fourth," and the like (if any) in the specification and claims of this application and in the accompanying drawings are used to distinguish similar objects and are not necessarily used to describe a particular order or sequential sequence. It should be understood that the terms used in this manner are interchangeable where appropriate so that the embodiments described herein can be implemented in an order other than that illustrated or described herein. In addition, the terms "including" and "having," and any variations thereof, are intended to cover non-exclusive inclusions, e.g., a process, method, system, product, or apparatus comprising a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0035] In order to facilitate understanding of the technical solution provided by this application, the structure and working principle of the spatiotemporal group positioning chip are first briefly described.

[0036] The surface of the spatiotemporal positioning chip is covered with a large number of DNA nanoball (DNB) binding sites arranged in a regular array. These sites are connected to probes with a specific tag sequence (barcode). Probes connected to the same DNB binding site have the same barcode sequence, while probes connected to different DNB binding sites have different barcode sequences. When producing the spatiotemporal positioning chip, the barcode sequence of the probe connected to each DNB binding site on the produced spatiotemporal positioning chip needs to be sequenced. This results in a DNA sequence being measured for each DNB binding site.

[0037] In the present embodiment, a DNA sequence measured at a DNB binding site in the spatiotemporal group localization chip can be recorded as a barcode sequence. Alternatively, since the DNA sequence measured by the spatiotemporal group localization chip can be stored in a fastq format file, a barcode sequence can also be recorded as a read sequence.

[0038] In the field of gene sequencing, base quality scores (BQSs) can be used to assess the quality of a barcode sequence. A biophysics term first introduced in 2018, BQS measures the probability of base misidentification within a DNA sequence. Specifically, it is defined as an integer mapping of the base misidentification probability. For a specific DNA sequence, such as the barcode sequence in this example, each base in the sequence is assigned a BQS. A higher BQS indicates a lower probability of misidentification, while a lower BQS indicates a higher probability of misidentification.

[0039] For ease of distinction, in this embodiment, the base quality value is represented by a number prefixed with Q, for example, a base quality value of 10 is recorded as Q10.

[0040] An embodiment of the present application provides a quality detection method for a spatiotemporal group positioning chip. Please refer to FIG1 , which is a flow chart of the method. The method may include the following steps.

[0041] S101, obtaining sequencing results of the chip to be tested, and generating a base quality distribution map of the chip to be tested according to the sequencing results of the chip to be tested.

[0042] The chip under test refers to the spatiotemporal positioning chip that needs to undergo quality inspection. There can be one or more chips under test. In a specific application scenario, several spatiotemporal positioning chips (for example, 36) can be produced simultaneously in the same batch. Then, all spatiotemporal positioning chips produced in the batch are used as the chips under test for the batch. For example, if 36 spatiotemporal positioning chips are produced in the batch, there will be 36 chips under test.

[0043] For each chip to be tested, the sequencing result of the chip to be tested may include at least the barcode sequence measured for each DNB binding site (hereinafter referred to as site) on the chip to be tested. In this embodiment, the sequencing result of a chip to be tested can be stored in a fastq format result file.

[0044] The base quality distribution diagram of the chip to be tested reflects the number of bases whose base quality values ​​are less than a preset base quality threshold in each barcode sequence measured by the chip to be tested.

[0045] It can be understood that for the sequencing results of the same chip to be tested, different base quality distribution maps can be obtained according to the different set base quality thresholds. In the relevant technical field, the commonly used base quality thresholds are Q10, Q20 and Q30, respectively. Among them, the base quality distribution map generated with Q10 as the base quality threshold can be recorded as a Q10 heat map, the base quality distribution map generated with Q20 as the base quality threshold can be recorded as a Q20 heat map, and the base quality distribution map generated with Q30 as the base quality threshold can be recorded as a Q30 heat map.

[0046] In some optional embodiments, the base quality distribution map generated in step S101 can be a Q10 heat map, a Q20 heat map, or a Q30 heat map. For ease of explanation, the following text uses the Q10 heat map as an example to introduce the technical solution of the present application.

[0047] Among them, the advantage of using the Q10 heat map is that when there are holes in the tissue expression map of the chip under test, the bright spots on the Q10 heat map can perfectly match the holes on the tissue expression map. In other words, compared with other heat maps, the Q10 heat map can most realistically reflect the quality defects of the chip under test.

[0048] The process of generating a Q10 heat map is as follows:

[0049] First, the coordinates corresponding to each barcode sequence in the sequencing results are determined. Specifically, for each barcode sequence, the coordinates of the site on the chip where the barcode sequence was measured can be determined based on the identification information of the barcode sequence in the sequencing results. The coordinates of the site on the chip where the barcode sequence was measured are determined as the coordinates corresponding to the barcode sequence.

[0050] The number of low-quality bases corresponding to each barcode sequence is then counted. In this embodiment, low-quality bases are defined as bases with a base quality value less than Q10. Accordingly, the number of low-quality bases refers to the number of bases in a barcode sequence with a base quality value less than Q10. For example, if a barcode sequence has five bases with base quality values ​​less than Q10, the number of low-quality bases in that barcode sequence is five.

[0051] The method for determining the base quality value of each base in the barcode sequence can be found in the literature in the relevant technical field and will not be described in detail here.

[0052] A Q10 heatmap is generated based on the coordinates and number of low-quality bases corresponding to each barcode sequence. Specifically, each pixel in the Q10 heatmap corresponds to a barcode sequence in the sequencing results (or the site where the barcode sequence was measured). The barcode sequence coordinates (equivalent to the coordinates of the site where the barcode sequence was measured) are the coordinates of the corresponding pixel, and the number of low-quality bases in the barcode sequence is the pixel value of the corresponding pixel.

[0053] For example, a barcode sequence with coordinates (10, 20) and 10 low-quality bases on the chip being tested can be mapped to a pixel with coordinates (10, 20) and a pixel value of 10 on the Q10 heat map. The set of pixels mapped to all barcode sequences in the sequencing results is equivalent to the Q10 heat map generated based on the sequencing results.

[0054] In summary, the process of generating a base quality distribution map of the chip to be tested based on the sequencing results of the chip to be tested can be summarized as follows:

[0055] For each site on the chip to be tested, the number of low-quality bases in the barcode sequence measured at the site in the sequencing results is detected; wherein, low-quality bases refer to bases whose base quality values ​​are less than the preset base quality threshold;

[0056] A base quality distribution map of the chip to be tested is generated based on the coordinates of each site in the chip to be tested and the number of low-quality bases in the measured barcode sequence. The pixels in the base quality distribution map correspond one-to-one to the sites on the chip to be tested, and the pixel value is the number of low-quality bases in the barcode sequence measured at the corresponding site.

[0057] Please refer to Figures 2 and 3, where Figure 2 is an example of a Q10 heat map of a chip under test, and Figure 3 is a magnified partial view of the Q10 heat map of the chip under test. As can be seen, the Q10 heat map contains multiple bright spots of varying sizes. The method provided in this embodiment evaluates the quality of the chip under test by analyzing the relevant indicators of these bright spots.

[0058] In addition to generating a base quality distribution map, step S101 may also include:

[0059] The sequencing results of the chip to be tested are counted and filtered to obtain the sequencing statistics of the chip to be tested.

[0060] In some optional embodiments, the sequencing statistics of the chip to be tested may include the following parameters:

[0061] The number of unique barcode types, in English, is called get unique barcode types, which indicates the number of barcode sequence types obtained after filtering and deduplication.

[0062] Reverse complementary sequence, in English, barcode reverse complement, indicates whether each barcode sequence has undergone reverse complementation processing.

[0063] Sequence start, also known as barcode start in English, indicates the starting position of the barcode sequence in reads (starting from 0).

[0064] Sequence length, in English, is barcode length, which indicates the length of each barcode sequence.

[0065] Sequence fragment, in English, barcode segment, indicates that each read contains several barcode sequences.

[0066] The total number of records, called total reads in English, indicates the total number of read sequences in the sequencing result file.

[0067] The total number of bases, in English, is total bases, which indicates the total number of bases contained in all reads sequences.

[0068] Reads without position refers to reads whose coordinate positions on the chip cannot be determined.

[0069] N-base sequence, also known as barcode with N in English, means a barcode sequence containing N bases.

[0070] The A / C / T / G base sequence, also known as a barcode with polyA|C|T|G in English, indicates a barcode in which one of the four bases accounts for more than 80%.

[0071] Repeated sequences, also known as duplicated barcodes in English, indicate the number and ratio of non-adjacent repeated barcodes.

[0072] EST neighbor duplicated barcodes, which indicates the number and ratio of adjacent duplicate barcodes (adjacent duplications are defined as two barcodes with the same sequence and adjacent positions on the chip).

[0073] The Q10 / Q20 / Q30 base ratio, in English Q10 / Q20 / Q30 bases, indicates the proportion of bases with base quality values ​​greater than Q10, Q20, and Q30 respectively to all bases.

[0074] The above statistical results can be used as a basis for determining the specific cause of the abnormality when it is found that the chip under test does not meet the quality requirements.

[0075] S102 , performing quality inspection on the chip to be tested according to the base quality distribution map to obtain quality indicators of the chip to be tested.

[0076] As described in step S101 , the base quality distribution map in this embodiment may specifically be a Q10 heat map, and therefore step S102 is equivalent to performing a quality test on the chip to be tested based on the Q10 heat map.

[0077] Please refer to FIG4 , which is a flowchart of performing quality inspection on a chip to be tested based on a Q10 heat map provided in this embodiment. As shown in FIG4 , the specific implementation process of step S102 may include the following steps.

[0078] S401, count the proportion of low-quality sequences.

[0079] Optionally, when the chip to be tested is a chip to be tested for a certain specific model of gene sequencing equipment, such as a chip to be tested on the DNBSEQ-T1 platform, each field of view (which can be represented by FOV) of such a chip to be tested will be surrounded by a circle of defocus, resulting in the barcode sequence measured at the site located at the defocus position being empty, that is, the barcode sequence will not be measured at the site at the defocus position, which will result in the presence of a grid white edge similar to a trace on the Q10 heat map of such a chip to be tested. For example, Figure 5 is a schematic diagram of the white edge in the Q10 heat map provided in this embodiment.

[0080] In order to eliminate these white edges, when the chip to be tested is a chip of the above-mentioned specific model of gene sequencing equipment, an operation of eliminating the white edges may be performed before executing S401.

[0081] The specific operation of eliminating white edges is to first detect white edges in the Q10 heat map using Hough transform, and then fill all pixels in the white edges with 0, that is, set the pixel value of each pixel constituting the white edges to 0, thereby eliminating the white edges.

[0082] That is to say, before S401, it also includes:

[0083] Hough transform was used to detect white edges in the base quality distribution graph;

[0084] Set the pixel values ​​of the pixels contained in the white border to 0.

[0085] In this embodiment, a low-quality sequence is defined as a barcode sequence in which the number of low-quality bases is greater than a preset low-quality threshold. The low-quality threshold is a preset positive integer, and its specific value can be set as needed and is not limited.

[0086] For example, when using a spatiotemporal mapping chip for spatial transcriptome capture and sequencing of the captured mRNA, the measured barcodes can be subjected to single-bit error tolerance. Therefore, if a barcode sequence contains at most one low-quality base, the low-quality base can be corrected, and such a barcode sequence will not affect the accuracy of subsequent analysis based on the sequencing results. However, if a barcode sequence contains two or more low-quality bases, correction cannot be performed, and such a barcode sequence will have a negative impact on the accuracy of subsequent analysis results.

[0087] For the reasons mentioned above, the low-quality threshold can be set to 1. That is, if the number of low-quality bases in a barcode sequence is greater than 1, the barcode sequence is considered low-quality. The low-quality sequence ratio is the proportion of low-quality sequences among all barcode sequences measured by the chip under test. Specifically, the low-quality sequence ratio can be equal to the number of low-quality sequences divided by the total number of barcode sequences measured by the chip under test.

[0088] As previously mentioned, the pixel value of a pixel in the Q10 heat map is equal to the number of low-quality bases in the barcode sequence corresponding to the pixel, so the implementation process of step S401 may include:

[0089] Identifying pixels in the base quality distribution map whose pixel values ​​are greater than a preset low-quality threshold;

[0090] The proportion of pixels with pixel values ​​greater than the low-quality threshold in the base quality distribution map is determined as the low-quality sequence ratio of the chip to be tested.

[0091] Taking the low quality threshold equal to 1 as an example, we can count the number of pixels with a pixel value greater than 1 in the Q10 heat map, and then divide the number of pixels with a pixel value greater than 1 by the total number of pixels in the Q10 heat map. The result is the low quality sequence ratio.

[0092] S402 , performing pooling and normalization processing on the Q10 heat map to obtain a pre-processed heat map of the chip to be tested.

[0093] Pooling processing is performed on the Q10 heat map, including:

[0094] A1, based on a pooling window of a preset size, divides the Q10 heat map into several pooling regions.

[0095] Exemplarily, the preset size can be 20*20. Based on the 20*20 pooling window, the Q10 heat map can be divided into multiple 20*20 pooling areas. Different pooling areas do not overlap with each other, and each pooling area includes 20 rows and 20 columns of pixels in the Q10 heat map.

[0096] A2, sum the pixels in each pooling area to obtain the enhanced pixels corresponding to each pooling area.

[0097] A3: Combine the enhanced pixels according to the positions of the corresponding pooling areas to obtain an enhanced image.

[0098] When executing A2, first, for each pooled region, the pixel values ​​of the 20*20 pixels (i.e., 400 pixels) in the Q10 heat map within the pooled region are summed, and the sum is determined as the pixel value of the enhanced pixel corresponding to the pooled region. In this way, each pooled region in the Q10 heat map is mapped to an enhanced pixel.

[0099] Then, in A3, the enhanced image is obtained by combining the corresponding enhanced pixels according to the position of the pooled area in the Q10 heat map. For example, the pooled area located in the first row and first column of the Q10 heat map will be mapped to an enhanced pixel located in the first row and first column of the enhanced image. The pooled area located in the first row and second column will be mapped to an enhanced pixel located in the first row and second column of the enhanced image. And so on. The enhanced image can be obtained by combining the enhanced pixels.

[0100] After pooling, the enhanced image is normalized as follows:

[0101] First, the maximum pixel value and the minimum pixel value among the pixel values ​​of all pixels in the enhanced image are determined.

[0102] Then, for each pixel in the enhanced image, the normalized pixel value of the pixel is calculated according to the following formula.

[0103]

[0104] Among them, P1 represents the normalized pixel value, P2 represents the original pixel value of the pixel in the enhanced image, Pmin represents the minimum pixel value determined in the previous step, and Pmax represents the maximum pixel value determined in the previous step.

[0105] By using the above formula, the normalized pixel value of each pixel in the range of 0 to 255 can be calculated.

[0106] Finally, the pixel value of each pixel in the enhanced image is set to the normalized pixel value of the pixel, thereby completing the normalization process.

[0107] The image obtained after each pixel is set to the normalized pixel value is the preprocessed heat map obtained after the Q10 heat map is pooled and normalized.

[0108] Optionally, if the pixel value of a pixel in the preprocessed heat map is not an integer after normalization, the pixel value of the pixel may be rounded up according to a rounding rule.

[0109] Step S402 is equivalent to performing pooling and normalization processing on the base quality distribution map to obtain a pre-processed heat map of the chip to be tested.

[0110] S403 , identifying bright spots in the pre-processed heat map of the chip to be tested.

[0111] In this embodiment, the bright spots may include highlighted areas and field of view missing areas in the preprocessing heat map. Therefore, step S403 may specifically include identifying highlighted areas in the preprocessing heat map and identifying field of view missing areas in the preprocessing heat map.

[0112] In this embodiment, a pixel value that is too high is defined as a pixel value that is greater than twice the pixel mean of the preprocessing heat map. Therefore, in step S403, the pixel values ​​of all pixels in the preprocessing heat map can be averaged to obtain the average value of the pixel values ​​of all pixels in the preprocessing heat map, that is, the pixel mean of the preprocessing heat map. Then, each pixel in the preprocessing heat map is identified one by one to see whether the pixel value is greater than twice the pixel mean. Pixels with pixel values ​​greater than twice the pixel mean are determined to be pixels with too high pixel values. The area consisting of pixels with too high pixel values ​​is the highlight area.

[0113] Please refer to Figure 6, which is a schematic diagram of the highlighted areas in a Q10 heat map provided in an embodiment of the present application. The areas circled by white lines and pointed by white arrows in Figure 6 are the two larger highlighted areas in the preprocessing heat map.

[0114] The method for identifying the missing area of ​​the field of view is as follows:

[0115] First, the gradient of the preprocessed heat map is calculated to obtain the gradient value of each pixel in the preprocessed heat map. The specific algorithm for calculating the gradient of pixels in the image can be found in the literature in the relevant technical field and will not be described in detail here.

[0116] Then, the area consisting of pixels with slower pixel value changes in the preprocessed heat map, that is, pixels with smaller gradient values, is determined as the field of view loss area. Specifically, a gradient threshold can be pre-set based on actual conditions, and the area consisting of pixels with gradient values ​​less than the gradient threshold is determined as the field of view loss area.

[0117] Please refer to Figure 7, which is a schematic diagram of a field of view missing area in a pre-processing heat map provided in an embodiment of the present application. The white area pointed out by the white arrow in Figure 7 is a larger field of view missing area in the pre-processing heat map.

[0118] S404 , counting the number of bright spots, the maximum bright spot area, the total bright spot area and the standard deviation of the bright spot area of ​​the preprocessed heat map.

[0119] The maximum bright spot area is the area of ​​the largest bright spot in the preprocessed heat map. The area of ​​a bright spot can be expressed by the number of pixels contained in the bright spot.

[0120] The total area of ​​bright spots is the sum of the areas of all bright spots in the preprocessed heat map.

[0121] The standard deviation of the bright spot area is the standard deviation of the array composed of the areas of all bright spots in the preprocessed heat map. The specific algorithm of the standard deviation can be found in the relevant literature and will not be described in detail here.

[0122] After counting the various indicators in step S404, the quality inspection process ends.

[0123] According to the quality detection process shown in FIG4 , it can be seen that the quality indicators of the chip to be tested in this embodiment may include the proportion of low-quality sequences, the number of bright spots in the preprocessing heat map, the maximum bright spot area, the total bright spot area and the standard deviation of the bright spot area.

[0124] S103 , determining a quality detection result of the chip to be tested according to the quality index of the chip to be tested and a preset quality index threshold.

[0125] The quality test result may specifically include the availability of the chip under test. The specific value of the quality indicator threshold can be set based on relevant experimental data and the experience of technicians, and is not limited in this embodiment.

[0126] In step S103 , each quality indicator may be compared with a preset quality indicator threshold of the quality indicator, thereby determining whether the quality indicator of the chip to be tested is qualified.

[0127] If at least one quality indicator of the chip under test fails to meet the requirements, the availability of the chip under test is determined to be unavailable. If all quality indicators of the chip under test meet the requirements, the availability of the chip under test is determined to be available.

[0128] The quality indicator thresholds may include a low quality ratio threshold, a maximum area threshold, a total bright spot area threshold, a bright spot number threshold, and a standard deviation threshold. Optionally, the quality indicator threshold corresponding to the maximum bright spot area may also include several area intervals.

[0129] The following describes the process of testing whether the aforementioned quality indicators are qualified with reference to specific examples.

[0130] The process of detecting whether the low-quality sequence ratio is qualified:

[0131] Determine whether the low-quality sequence ratio of the chip to be tested is greater than a preset low-quality ratio threshold. If it is greater than the low-quality ratio threshold, it is determined that the low-quality sequence ratio of the chip to be tested is unqualified. If it is less than or equal to the low-quality ratio threshold, it is determined that the low-quality sequence ratio of the chip to be tested is qualified.

[0132] The low quality ratio threshold may vary depending on the model of the gene sequencing device to which the chip to be tested belongs. For example, the low quality ratio threshold of the DNBSEQ-T1 device may be 30%, and the low quality ratio threshold of the DNBSEQ-T10 device may be 25%.

[0133] The process of testing whether the maximum bright spot area is qualified:

[0134] The process of detecting whether the maximum bright spot area is qualified may be different depending on the model of the device to which the chip to be tested belongs.

[0135] For example, if the chip to be tested belongs to the DNBSEQ-T10 platform, three area intervals can be set, where the largest area interval can be greater than 850*850, the smaller area interval can be greater than 500*500 but less than or equal to 850*850, and the smallest area interval can be less than or equal to 500*500.

[0136] Based on this setting, if the maximum bright spot area belongs to the smallest area interval, it is determined that the maximum bright spot area of ​​the chip to be tested belongs to the high quality inspection level, and the maximum bright spot area indicator is qualified.

[0137] If the maximum bright spot area belongs to a smaller area range, it is determined that the maximum bright spot area of ​​the chip to be tested belongs to the medium quality inspection level. At this time, manual inspection is required. If the manual inspection passes, the maximum bright spot area indicator is determined to be qualified. If the manual inspection fails, the maximum bright spot area indicator is determined to be unqualified.

[0138] If the maximum bright spot area belongs to the largest area interval, it is determined that the maximum bright spot area of ​​the chip to be tested belongs to the low quality inspection level, and the maximum bright spot area indicator is unqualified.

[0139] If the chip to be tested belongs to the DNBSEQ-T1 platform, the maximum bright spot area is compared with the preset maximum area threshold. If the maximum bright spot area is greater than the maximum area threshold, the maximum bright spot area indicator is determined to be unqualified; if the maximum bright spot area is less than or equal to the maximum area threshold, the maximum bright spot area indicator is determined to be qualified.

[0140] The maximum area threshold may be set to 1% of the chip area of ​​the chip to be tested, or may be set to other proportions without limitation.

[0141] The process of testing whether the total area of ​​bright spots is qualified:

[0142] If the total bright spot area is greater than the preset total bright spot area threshold, the total bright spot area of ​​the chip to be tested is determined to be unqualified; if the total bright spot area is less than or equal to the total bright spot area threshold, the total bright spot area of ​​the chip to be tested is determined to be qualified.

[0143] The total bright spot area threshold can be determined based on the device model of the chip being tested. For example, if the chip being tested is on the DNBSEQ-T10 platform, the total bright spot area threshold can be set to 35% of the field of view (FOV), i.e., 0.35*FOV. If the chip being tested is on the DNBSEQ-T1 platform, the total bright spot area threshold can be set to 0.01*chip area.

[0144] The process of detecting whether the number of bright spots is qualified:

[0145] It is determined whether the number of bright spots is greater than a bright spot number threshold. If it is greater than the bright spot number threshold, it is determined that the number of bright spots is unqualified. If it is less than or equal to the bright spot number threshold, it is determined that the number of bright spots is qualified.

[0146] The bright spot number threshold can be set based on the total number of fields of view of the chip to be tested. It is generally considered acceptable if the average number of bright spots in each field of view is less than two. Therefore, the bright spot number threshold can be set to three times the total number of fields of view in the chip to be tested. Therefore, when the number of bright spots is greater than the bright spot number threshold, it can be considered that the average number of bright spots appearing in each field of view reaches three or more, and therefore it can be determined that this indicator fails.

[0147] The reasons for considering the number of bright spots when determining quality inspection results are:

[0148] Some chips under test may have bright spot distribution as shown in the schematic diagram of Figure 8, that is, there are many bright spots, but the total area of ​​the bright spots is very small. In this case, although the total area of ​​the bright spots is qualified, the chip under test is still unusable. Therefore, it is necessary to consider whether the number of bright spots is qualified when determining the quality inspection results to avoid the situation of unusable chips under test as shown in Figure 8.

[0149] The process of testing whether the standard deviation of the bright spot area is qualified:

[0150] Detect whether the standard deviation of the bright spot area is less than a preset standard deviation threshold. If it is not less than the standard deviation threshold, the bright spot area standard deviation indicator is determined to be qualified. If it is less than the standard deviation threshold, the bright spot area standard deviation indicator is determined to be unqualified.

[0151] The standard deviation threshold can be set according to actual conditions and is not limited. For example, the standard deviation threshold can be set to 0.08.

[0152] The reason for considering the standard deviation of the bright spot area when determining the quality inspection results is:

[0153] When the lens is out of focus, the pre-processed heat map of the chip under test may show a bright spot distribution as shown in Figure 9, that is, the bright spots appear according to a certain pattern. If the lens is out of focus, even if the other aforementioned indicators are qualified, the chip under test is still unusable.

[0154] Therefore, in this embodiment, the standard deviation of the bright spot area is detected to determine whether the bright spots on the preprocessed heat map appear in a certain pattern. If the standard deviation of the bright spot area is less than the standard deviation threshold, it is considered that the bright spots appear in a regular pattern, which further indicates that the lens is out of focus. Therefore, the standard deviation of the bright spot area fails to meet the standard, and the chip under test is unusable. This can avoid the problem of lens out of focus.

[0155] According to the above process of testing whether each quality indicator is qualified, it can be seen that the step of determining the quality test result in S103 is equivalent to:

[0156] If the chip to be tested meets at least one of the following conditions: the low-quality sequence ratio is greater than the low-quality ratio threshold, the maximum bright spot area is greater than the maximum area threshold, the number of bright spots is greater than the bright spot number threshold, the total bright spot area is greater than the total bright spot area threshold, and the bright spot area standard deviation is less than the standard deviation threshold, the chip to be tested is determined to be unusable;

[0157] If the proportion of low-quality sequences of the chip to be tested is not greater than the low-quality proportion threshold, the maximum bright spot area is not greater than the maximum area threshold, the number of bright spots is not greater than the bright spot number threshold, the total area of ​​bright spots is not greater than the total area threshold, and the standard deviation of the bright spot area is not less than the standard deviation threshold, the chip to be tested is determined to be usable.

[0158] In some optional embodiments, the quality inspection results may include, in addition to usability, several other parameters that can reflect the quality of the chip under test. For example, after performing a quality inspection on a chip under test according to the method shown in FIG1 , the quality inspection results obtained can be represented by Table 1:

[0159] Table 1

[0160] Chip QC CheckHighLow quality barcode rate11.59%(Pass)Max defects area(bin)303.32(High)Sum of defects area(bin)1166.96(Pass)Approx number of FOV81Number of defects threshold has been set as243Number of all defects found153Defects Area Standard deviation10948.46(Pass)

[0161] The meanings of the parameters in Table 1 are as follows.

[0162] Chip QC check: This parameter indicates the final quality control status of the chip. This parameter can have different value ranges depending on the device used to test the chip. Taking the DNBSEQ-T10 platform as an example, the final quality control status of the chip is divided into three levels: High, Medium, and Low.

[0163] High indicates that all other quality indicators except the maximum bright spot area (including the proportion of low-quality sequences, number of bright spots, total bright spot area, and bright spot area standard deviation) are qualified, and the quality inspection grade after the maximum bright spot area test is high; Medium indicates that all other quality indicators except the maximum bright spot area are qualified, but the quality inspection grade after the maximum bright spot area test is medium; Low indicates that at least one of the other quality indicators except the maximum bright spot area fails, or the quality inspection grade after the maximum bright spot area test is low.

[0164] The low quality barcode rate, i.e. the low quality sequence ratio mentioned above, is 11.59% in Table 1, which is less than the threshold of 25%. The chip under test passes this indicator.

[0165] Max defects area (bin), that is, the maximum bright spot area mentioned above, is bin 303.32 in Table 1, that is, 303.32*303.32, which is less than the threshold of 500*500. The quality inspection level of the chip to be tested is high, and this indicator passes the test.

[0166] Sum of defects area (bin), that is, the total area of ​​bright spots. In Table 1, this indicator is bin 1166.96, 1166.96*1166.96=1361889, which is less than the threshold value of 2969949. The chip under test passes this indicator.

[0167] Approx number of FOV, which indicates the number of fields of view in the chip under test, is 81 in Table 1.

[0168] Number of defects threshold has been set as, which represents the bright spot number threshold calculated according to the number of fields of view. In the example of Table 1, the bright spot number threshold is 243.

[0169] Number of all defects found indicates the number of bright spots detected. In the example in Table 1, the number of bright spots is 153, which is less than the bright spot number threshold. The number of bright spots on the tested chip is qualified.

[0170] Defects Area Standard Deviation: If the standard deviation of the detected defect area is greater than the threshold of 0.08, the chip passes this test.

[0171] Please refer to Figure 10, which shows an example of a chip to be tested cut in this embodiment. In some optional embodiments, considering that a spatiotemporal group positioning chip is physically cut into multiple fragments of different sizes as shown in Figure 10 during use, the result file of each chip can be compressed and stored as follows.

[0172] The image is split into multiple sub-result files based on the actual cutting range. Each sub-result file corresponds to a fragment one-to-one, meaning each sub-result file stores multiple barcode sequences measured for a fragment. Each sub-result file can be further divided into multiple blocks, each corresponding to a field of view in the fragment and containing the barcode sequence for that field of view. In addition, each block contains a compression header that includes the field of view number of the corresponding field of view and the data size of the block.

[0173] That is, the sequencing results of the chip to be tested include multiple sub-result files, and the multiple sub-result files correspond one-to-one to the multiple fragments into which the chip to be tested is divided according to the preset cutting range;

[0174] Each sub-result file includes a plurality of blocks, and the blocks correspond one-to-one to the fields of view of the fragments corresponding to the sub-result files;

[0175] The block of the sub-result file contains the barcode sequence measured for the fragment corresponding to the sub-result file and under the field of view corresponding to the block.

[0176] The advantage of adopting this storage method is that the corresponding data of the corresponding field of view range can be quickly extracted from the compressed result file according to the field of view number range corresponding to the small fragments.

[0177] The above result file storage method can be applied to certain specific models of gene sequencing equipment, for example, the MGI DNBSEQ-T10 sequencing platform.

[0178] The quality indicator thresholds used in the above-mentioned detection of whether each quality indicator is qualified can be determined as follows.

[0179] How the low quality ratio threshold is determined.

[0180] The low quality ratio threshold can be determined based on the relationship between the matching ratio and the passing ratio of the sequencing results. Please refer to Figure 11, which is a schematic diagram of the relationship between the matching ratio and quality value of the sequencing results obtained by counting a large number of samples in an embodiment of the present application.

[0181] The horizontal axis represents the pass ratio, which can be understood as the proportion of barcode sequences that are not low-quality sequences in the sequencing results of the chip to be tested. In other words, if the pass ratio is 0.75, the proportion of low-quality sequences is 0.25. If the pass ratio is 0.8, the proportion of low-quality sequences is 0.2.

[0182] The match ratio refers to the proportion of barcode sequences that meet the sequence matching (barcode mapping) criteria among all barcode sequences included in the sequencing results. Sequence matching refers to the ability of a barcode sequence to be mapped back to its original spatial location after alignment with the mask file of the spatiotemporal group positioning chip.

[0183] From the statistical results in Figure 11, it can be seen that the matching ratio and the pass ratio are positively correlated. When the pass ratio reaches 75%, the corresponding matching ratio can reach 60%. In practical applications, as long as the matching ratio of the sequencing result is greater than or equal to 60%, the sequencing result can be used for subsequent analysis. Therefore, the quality of the chip under test can be tested based on a pass ratio greater than or equal to 75%. A pass ratio greater than or equal to 75% corresponds to a low-quality sequence ratio less than or equal to 25%. Therefore, the low-quality ratio threshold can be determined as 25%.

[0184] How to determine the maximum area threshold.

[0185] The maximum area threshold can be determined based on the distribution of the maximum bright spot areas of multiple spatiotemporal group positioning chips.

[0186] Please refer to Figure 12, which shows a schematic diagram of the distribution of the maximum defect area of ​​a spatiotemporal group positioning chip according to an embodiment of the present application. Figure 12 shows the distribution of the maximum bright spot area for 800 chips. The horizontal axis represents the chip number, ranging from 1 to 800, and the vertical axis represents the maximum bright spot area detected on each chip using the aforementioned method, ranging from 0 to 1.4, with units of 1e6 (10 to the sixth power).

[0187] The left side of the dotted line represents chips manually judged acceptable, while the right side represents chips manually judged unacceptable. As shown in Figure 12, the maximum bright spot area of ​​chips manually judged acceptable is approximately 500*500. Therefore, chips with a maximum bright spot area below 500*500 are considered high-quality chips. Furthermore, there is an inflection point on the statistical curve in Figure 12. Above this point, the maximum bright spot area of ​​chips increases rapidly. Therefore, chips with a maximum bright spot area greater than the inflection point (approximately 850*850) are considered low-quality chips. Chips with a maximum bright spot area between 500*500 and 800*800 are considered acceptable, and their usability can be determined based on manual inspection.

[0188] How to determine the total bright spot area threshold.

[0189] The threshold value of the total bright spot area can be determined according to the distribution of the total bright spot areas of multiple spatiotemporal group positioning chips.

[0190] Please refer to Figure 13, which shows a schematic diagram of the total area distribution of chip defects based on spatiotemporal group positioning according to an embodiment of the present application. Figure 13 shows the total area distribution of bright spots across 400 chips. The horizontal axis represents the chip number, ranging from 1 to 400, and the vertical axis represents the total area of ​​bright spots, ranging from 0 to 1.2, with units of 1e7 (10 to the power of 7).

[0191] As can be seen from Figure 13, at the inflection point of the curve in Figure 13, the corresponding total area of ​​the bright spot is 3010200, while the area of ​​a field of view of the spatiotemporal group positioning chip used in the DNBSEQ-T10 platform is 8485569, and 0.35*8485569 is approximately 2969949. It can be seen that the total area of ​​the bright spot corresponding to the inflection point is approximately equal to 35% of the field of view area, so 0.35*field of view area is determined as the total area threshold of the bright spot of the chip of the DNBSEQ-T10 platform.

[0192] The total bright spot area threshold of the chip of another model of equipment in the aforementioned example can be determined in a similar manner and will not be described in detail.

[0193] Determining the bright spot number threshold: The bright spot number threshold can be directly determined as three times the number of fields of view of the chip to be tested, which means that on average only three bright spots are allowed to appear in each field of view.

[0194] How the standard deviation threshold is determined.

[0195] The standard deviation of the bright spot area of ​​the chip with regular bright spots and the standard deviation of the bright spot area of ​​the chip with irregular bright spots were manually determined through calculation, and then a value of 0.08 was selected to distinguish the two chips.

[0196] The beneficial effects of this embodiment are:

[0197] A corresponding base quality distribution map is generated based on the sequencing results of the chip to be tested, and the base quality distribution map is analyzed by computer to obtain various quality indicators reflecting the quality of the chip to be tested. Then, the quality detection results are determined based on the comparison of these quality indicators with the corresponding quality indicator thresholds. Obviously, the quality detection results obtained in this way have higher accuracy and detection efficiency than the results of naked eye recognition.

[0198] In addition, the quality inspection results obtained in this embodiment can also be sent to any one or more terminals in the form of a web page report, so that users can browse the quality inspection results online.

[0199] According to the quality detection method of the spatiotemporal group positioning chip provided in the embodiment of the present application, the embodiment of the present application also provides a quality detection device for the spatiotemporal group positioning chip. Please refer to Figure 14, which is a structural diagram of the device.

[0200] The obtaining unit 1401 is used to obtain the sequencing result of the chip to be tested, and generate a base quality distribution map of the chip to be tested according to the sequencing result of the chip to be tested.

[0201] The detection unit 1402 is used to perform quality detection on the chip to be tested according to the base quality distribution map to obtain the quality index of the chip to be tested.

[0202] The quality index of the chip to be tested includes at least one of the following: the proportion of low-quality sequences, the maximum bright spot area, the number of bright spots, the standard deviation of the bright spot area, and the total bright spot area.

[0203] The determining unit 1403 is configured to determine a quality detection result of the chip to be tested according to a quality index of the chip to be tested and a preset quality index threshold.

[0204] Optionally, the detection unit 1402 performs quality detection on the chip to be tested according to the base quality distribution map to obtain the quality index of the chip to be tested, specifically for:

[0205] Count the proportion of low-quality sequences on the chip to be tested based on the base quality distribution map;

[0206] Perform pooling and normalization on the base quality distribution map to obtain a pre-processed heat map of the chip to be tested;

[0207] Identify bright spots in the pre-processed heat map of the chip under test; wherein the bright spots include highlighted areas and areas with missing fields of view;

[0208] The number of bright spots, the maximum bright spot area, the total bright spot area and the standard deviation of the bright spot area of ​​the preprocessed heat map were counted.

[0209] Optionally, the detection unit 1402 is further configured to:

[0210] Hough transform was used to detect white edges in the base quality distribution graph;

[0211] Set the pixel values ​​of the pixels contained in the white border to 0.

[0212] Optionally, the quality indicator thresholds include a low quality ratio threshold, a maximum area threshold, a bright spot total area threshold, a bright spot number threshold, and a standard deviation threshold;

[0213] When determining the quality test result of the chip to be tested based on the quality index of the chip to be tested and a preset quality index threshold, the determining unit 1403 is specifically configured to:

[0214] If the chip to be tested meets at least one of the following conditions: the low-quality sequence ratio is greater than the low-quality ratio threshold, the maximum bright spot area is greater than the maximum area threshold, the number of bright spots is greater than the bright spot number threshold, the total bright spot area is greater than the total bright spot area threshold, and the bright spot area standard deviation is less than the standard deviation threshold, the chip to be tested is determined to be unusable;

[0215] If the proportion of low-quality sequences of the chip to be tested is not greater than the low-quality proportion threshold, the maximum bright spot area is not greater than the maximum area threshold, the number of bright spots is not greater than the bright spot number threshold, the total area of ​​bright spots is not greater than the total area threshold, and the standard deviation of the bright spot area is not less than the standard deviation threshold, the chip to be tested is determined to be usable.

[0216] When the obtaining unit 1401 generates a base quality distribution map of the chip to be tested based on the sequencing results of the chip to be tested, it is specifically used to:

[0217] For each site on the chip to be tested, the number of low-quality bases in the barcode sequence measured at the site in the sequencing results is detected; wherein, low-quality bases refer to bases whose base quality values ​​are less than the preset base quality threshold;

[0218] A base quality distribution map of the chip to be tested is generated based on the coordinates of each site in the chip to be tested and the number of low-quality bases in the measured barcode sequence. The pixels in the base quality distribution map correspond one-to-one to the sites on the chip to be tested, and the pixel value is the number of low-quality bases in the barcode sequence measured at the corresponding site.

[0219] The sequencing results of the chip to be tested may include multiple sub-result files, and the multiple sub-result files correspond one-to-one to the multiple fragments into which the chip to be tested is divided according to a preset cutting range;

[0220] Each sub-result file includes a plurality of blocks, and the blocks correspond one-to-one to the fields of view of the fragments corresponding to the sub-result files;

[0221] The block of the sub-result file contains the barcode sequence measured for the fragment corresponding to the sub-result file and under the field of view corresponding to the block.

[0222] When the detection unit 1402 counts the proportion of low-quality sequences of the chip to be tested according to the base quality distribution map, it is specifically used to:

[0223] Identifying pixels in the base quality distribution map whose pixel values ​​are greater than a preset low-quality threshold;

[0224] The proportion of pixels with pixel values ​​greater than the low-quality threshold in the base quality distribution map is determined as the low-quality sequence ratio of the chip to be tested.

[0225] The specific working principle of the quality detection device of the spatiotemporal group positioning chip provided in this embodiment can be found in the relevant steps of the quality detection method of the spatiotemporal group positioning chip provided in the embodiment of the present application, and will not be repeated here.

[0226] An embodiment of the present application also provides an electronic device, see Figure 15, including a memory 1501 and a processor 1502.

[0227] The memory 1501 is used to store computer programs.

[0228] The processor 1502 is used to execute a computer program. When the computer program is executed, it is specifically used to implement the quality detection method of the spatiotemporal group positioning chip provided in any embodiment of the present application.

[0229] An embodiment of the present application further provides a computer storage medium for storing a computer program. When the computer program is executed, it is specifically used to implement the quality detection method of the spatiotemporal group positioning chip provided in any embodiment of the present application.

[0230] The above description is merely a specific embodiment of the present application, but the scope of protection of the present application is not limited thereto. Any changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in this application should be included in the scope of protection of this application. Therefore, the scope of protection of this application should be based on the scope of protection of the claims.

Claims

1. A quality detection method for a spatiotemporal group positioning chip, characterized in that: include: Obtaining sequencing results of the chip to be tested, and generating a base quality distribution map of the chip to be tested according to the sequencing results of the chip to be tested; Performing quality inspection on the chip to be tested according to the base quality distribution map to obtain a quality index of the chip to be tested; wherein the quality index of the chip to be tested includes at least one of a low-quality sequence ratio, a maximum bright spot area, a number of bright spots, a standard deviation of the bright spot area, and a total bright spot area; A quality inspection result of the chip to be tested is determined according to the quality index of the chip to be tested and a preset quality index threshold.

2. The method according to claim 1, characterized in that The step of performing quality inspection on the chip to be tested according to the base quality distribution map to obtain a quality index of the chip to be tested includes: Counting the proportion of low-quality sequences of the chip to be tested according to the base quality distribution graph; Performing pooling and normalization processing on the base quality distribution map to obtain a preprocessing heat map of the chip to be tested; Identify bright spots in the pre-processed heat map of the chip to be tested; wherein the bright spots include highlight areas and field of view missing areas; The number of bright spots, the maximum bright spot area, the total bright spot area and the standard deviation of the bright spot area of ​​the preprocessed heat map are counted.

3. The method according to claim 2, characterized in that Before counting the proportion of low-quality sequences of the chip to be tested according to the base quality distribution graph, the method further includes: The white edges were detected in the base quality distribution graph using Hough transform; Set the pixel values ​​of the pixels contained in the white border to 0.

4. The method according to claim 1, characterized in that The quality index thresholds include a low quality ratio threshold, a maximum area threshold, a bright spot total area threshold, a bright spot number threshold and a standard deviation threshold; The step of determining the quality inspection result of the chip to be tested according to the quality index of the chip to be tested and a preset quality index threshold comprises: If the chip to be tested meets at least one of the following conditions: the low-quality sequence ratio is greater than the low-quality ratio threshold, the maximum bright spot area is greater than the maximum area threshold, the number of bright spots is greater than the bright spot number threshold, the total area of ​​bright spots is greater than the total area threshold of bright spots, and the standard deviation of the bright spot area is less than the standard deviation threshold, it is determined that the chip to be tested is unavailable; If each of the following conditions is met: the low-quality sequence ratio of the chip to be tested is not greater than the low-quality ratio threshold, the maximum bright spot area is not greater than the maximum area threshold, the number of bright spots is not greater than the bright spot number threshold, the total bright spot area is not greater than the total bright spot area threshold, and the bright spot area standard deviation is not less than the standard deviation threshold, it is determined that the chip to be tested is available.

5. The method according to claim 1, characterized in that The step of generating a base quality distribution map of the chip to be tested according to the sequencing result of the chip to be tested comprises: For each site of the chip to be tested, the number of low-quality bases in the barcode sequence measured at the site in the sequencing result is detected; wherein the low-quality base refers to a base whose base quality value is less than a preset base quality threshold; A base quality distribution map of the chip to be tested is generated according to the coordinates of each site in the chip to be tested and the number of low-quality bases in the barcode sequence measured; wherein the pixels of the base quality distribution map correspond to the sites of the chip to be tested one by one, and the pixel value of the pixel is the number of low-quality bases in the barcode sequence measured at the corresponding site.

6. The method according to claim 1, characterized in that The sequencing result of the chip to be tested includes a plurality of sub-result files, and the plurality of sub-result files correspond one to one with the plurality of fragments into which the chip to be tested is divided according to a preset cutting range; Each of the sub-result files includes a plurality of blocks, and the blocks correspond one-to-one to the fields of view of the fragments corresponding to the sub-result files; The block of the sub-result file contains a barcode sequence measured for the fragment corresponding to the sub-result file in the field of view corresponding to the block.

7. The method according to claim 2, characterized in that: The counting of the proportion of low-quality sequences of the chip to be tested according to the base quality distribution graph comprises: Identifying pixels in the base quality distribution map whose pixel values ​​are greater than a preset low quality threshold; The proportion of pixels whose pixel values ​​are greater than the low-quality threshold in the base quality distribution map is determined as the low-quality sequence ratio of the chip to be tested.

8. A quality detection device for a spatiotemporal group positioning chip, characterized in that: include: An obtaining unit, used to obtain the sequencing result of the chip to be tested, and generate a base quality distribution map of the chip to be tested according to the sequencing result of the chip to be tested; A detection unit, used to perform quality detection on the chip to be tested according to the base quality distribution map to obtain a quality index of the chip to be tested; wherein the quality index of the chip to be tested includes at least one of a low-quality sequence ratio, a maximum bright spot area, a number of bright spots, a standard deviation of the bright spot area, and a total bright spot area; The determination unit is used to determine the quality detection result of the chip to be tested according to the quality index of the chip to be tested and a preset quality index threshold.

9. An electronic device, characterized in that: including memory and processor; Wherein, the memory is used to store computer programs; The processor is used to execute the computer program, and when the computer program is executed, it is specifically used to implement the quality detection method of the spatiotemporal group positioning chip as described in any one of claims 1 to 7.

10. A computer storage medium, characterized in that: Used to store computer programs, which, when executed, are specifically used to implement the quality detection method for the spatiotemporal group positioning chip as described in any one of claims 1 to 7.

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