Assessment method for tissue slice data heterogeneity and related equipment
Patent Information
- Application Number
- CN202280102033.X
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2022-12-30
- Publication Date
- 2025-07-01
AI Technical Summary
Existing technology lacks effective methods to evaluate the heterogeneity of tissue section data and to study the regulatory mechanisms of cell life and the process of cell lineage generation.
By obtaining the spatiotemporal transcriptome data of multiple slices of the target tissue, we perform cell type comparison, cluster analysis and correlation analysis to determine the similarity or difference in cell type proportions, gene expression and gene expression amounts to evaluate Organizational heterogeneity.
It provides a multi-dimensional evaluation method that can accurately judge the heterogeneity of tissue section data and improves the efficiency and accuracy of research on biological samples.
Smart Images
Figure CN120239886A_ABST
Abstract
Description
A method for evaluating heterogeneity of tissue section data and related equipment Technical Field
[0001] The present application relates to the field of biotechnology, and in particular to a method for evaluating the heterogeneity of tissue slice data and related equipment. Background Art
[0002] A tissue section is a slice of a biological sample—that is, a portion of that tissue. Spatiotemporal transcriptomics measures the total mRNA of intact tissues. By combining the spatial information of total mRNA with morphological information, the locations of gene expression are mapped, resulting in a complete gene expression map of biological processes. Compared to single-cell sequencing, spatiotemporal transcriptomics allows for the recording of lost spatial information, which is of great significance for studying the regulatory mechanisms of cellular life acquisition and the processes of cell lineage development.
[0003] The heterogeneity of tissue slice data refers to whether the gene expression patterns between different tissue slices are similar. However, there is currently no method to assess heterogeneity.
[0004] Summary of the Invention
[0005] The present application provides a method for evaluating the heterogeneity of tissue slice tissue data and related equipment, which can evaluate the heterogeneity of tissue slice data.
[0006] In a first aspect, the present application provides a method for evaluating heterogeneity of tissue slice data, the method comprising:
[0007] Acquiring spatiotemporal transcriptome data of a first slice of a target tissue and spatiotemporal transcriptome data of a second slice of the target tissue, wherein a distance between the first slice and the second slice is greater than a first preset distance;
[0008] Determining a first cell type alignment result, a first cluster alignment result, and a first correlation analysis result based on the spatiotemporal transcriptome data of the first slice and the spatiotemporal transcriptome data of the second slice;
[0009] An evaluation result of the heterogeneity of the target tissue is obtained based on the first cell type comparison result, the first cluster comparison result, and the first correlation analysis result.
[0010] Optionally, obtaining an evaluation result of the heterogeneity of the target tissue according to the first cell type comparison result, the first cluster comparison result, and the first correlation analysis result includes:
[0011] If the first cell type comparison result indicates that the proportion of cell types in the first slice is consistent with the proportion of cell types in the second slice; and the first cluster comparison result indicates that the gene expression in the first slice is consistent with the gene expression in the second slice; and the first correlation analysis result indicates that the gene expression amount in the first slice is correlated with the gene expression amount in the second slice, then an assessment result is obtained that the target tissue does not have heterogeneity.
[0012] Optionally, the method further includes:
[0013] If the first cell type comparison result indicates that the proportion of cell types in the first slice is inconsistent with the proportion of cell types in the second slice; or, the first cluster comparison result indicates that the gene expression in the first slice is inconsistent with the gene expression in the second slice; or, the first correlation analysis result indicates that the gene expression amount in the first slice is not correlated with the gene expression amount in the second slice, then an assessment result is obtained that the target tissue has heterogeneity.
[0014] Optionally, the process of determining the first cell type comparison result includes:
[0015] Determining the cell type and number of cells included in the first slice based on the spatiotemporal transcriptome data of the first slice; determining the cell type and number of cells included in the second slice based on the spatiotemporal transcriptome data of the second slice;
[0016] Calculating a chi-square value based on the cell types and numbers included in the first slice and the cell types and numbers included in the second slice;
[0017] According to the chi-square value, the corresponding P value is determined. If the P value is less than a first preset threshold, a first cell type comparison result is obtained, in which the proportion of cell types in the first slice is inconsistent with the proportion of cell types in the second slice; if the P value is greater than or equal to the first preset threshold, a first cell type comparison result is obtained, in which the proportion of cell types in the first slice is consistent with the proportion of cell types in the second slice.
[0018] Optionally, the process of determining the first cluster alignment result includes:
[0019] Clustering the gene expression conditions corresponding to the first slice according to the spatiotemporal transcriptome data of the first slice to obtain a first cluster image, and clustering the gene expression conditions corresponding to the second slice according to the spatiotemporal transcriptome data of the second slice to obtain a second cluster image;
[0020] If the difference between the first cluster image and the second cluster image is less than a second preset threshold, a first cluster comparison result is obtained, indicating that the gene expression in the first slice is consistent with the gene expression in the second slice; if the difference between the first cluster image and the second cluster image is greater than or equal to the second preset threshold, a first cluster comparison result is obtained, indicating that the gene expression in the first slice is inconsistent with the gene expression in the second slice.
[0021] Optionally, the process of determining the first correlation analysis result includes:
[0022] determining the gene expression level in the first slice based on the spatiotemporal transcriptome data of the first slice, and determining the gene expression level in the second slice based on the spatiotemporal transcriptome data of the second slice;
[0023] If the correlation coefficient between the gene expression amount in the first slice and the gene expression amount in the second slice is less than the third preset threshold, a first correlation analysis result is obtained, indicating that the gene expression amount in the first slice is not correlated with the gene expression amount in the second slice; if the correlation coefficient between the gene expression amount in the first slice and the gene expression amount in the second slice is greater than or equal to the third preset threshold, a first correlation analysis result is obtained, indicating that the gene expression amount in the first slice is correlated with the gene expression amount in the second slice.
[0024] Optionally, the method further includes:
[0025] Acquiring spatiotemporal transcriptome data of a third slice of the target tissue, where the distance between the third slice and the first slice is less than a second preset distance;
[0026] Determining a second cell type alignment result, a second cluster alignment result, and a second correlation analysis result based on the spatiotemporal transcriptome data of the first slice and the spatiotemporal transcriptome data of the third slice;
[0027] Obtaining an evaluation result of the heterogeneity of the target tissue according to the first cell type comparison result, the first cluster comparison result, and the first correlation analysis result, including:
[0028] An evaluation result of the heterogeneity of the target tissue is obtained based on the first cell type comparison result, the first cluster comparison result, the first correlation analysis result, and the second cell type comparison result, the second cluster comparison result, and the second correlation analysis result.
[0029] Optionally, the method further includes:
[0030] If the evaluation result of the heterogeneity of the target tissue indicates that the target tissue has no heterogeneity, the spatiotemporal transcriptome data of the first slice or the second slice is used as the spatiotemporal transcriptome data of the target tissue.
[0031] In a second aspect, the present application provides a device for evaluating the heterogeneity of tissue slice tissue data, the device comprising:
[0032] an acquisition module, configured to acquire spatiotemporal transcriptome data of a first slice of a target tissue and spatiotemporal transcriptome data of a second slice of the target tissue, wherein a distance between the first slice and the second slice is greater than a first preset distance;
[0033] a determination module, configured to determine a first cell type alignment result, a first cluster alignment result, and a first correlation analysis result based on the spatiotemporal transcriptome data of the first slice and the spatiotemporal transcriptome data of the second slice;
[0034] An analysis module is used to obtain an evaluation result of the heterogeneity of the target tissue based on the first cell type comparison result, the first cluster comparison result, and the first correlation analysis result.
[0035] Optionally, the analysis module is specifically used to obtain an assessment result that the target tissue does not have heterogeneity if the first cell type comparison result indicates that the proportion of cell types in the first slice is consistent with the proportion of cell types in the second slice; and the first cluster comparison result indicates that the gene expression in the first slice is consistent with the gene expression in the second slice; and the first correlation analysis result indicates that the gene expression amount in the first slice is correlated with the gene expression amount in the second slice.
[0036] Optionally, the analysis module is also used to obtain an assessment result that the target tissue has heterogeneity if the first cell type comparison result indicates that the proportion of cell types in the first slice is inconsistent with the proportion of cell types in the second slice; or the first cluster comparison result indicates that the gene expression in the first slice is inconsistent with the gene expression in the second slice; or the first correlation analysis result indicates that the gene expression amount in the first slice is not correlated with the gene expression amount in the second slice.
[0037] Optionally, the determining module is specifically configured to determine the cell type and number included in the first slice based on the spatiotemporal transcriptome data of the first slice; and determine the cell type and number included in the second slice based on the spatiotemporal transcriptome data of the second slice;
[0038] Calculating a chi-square value based on the cell types and numbers included in the first slice and the cell types and numbers included in the second slice;
[0039] According to the chi-square value, the corresponding P value is determined. If the P value is less than a first preset threshold, a first cell type comparison result is obtained, in which the proportion of cell types in the first slice is inconsistent with the proportion of cell types in the second slice; if the P value is greater than or equal to the first preset threshold, a first cell type comparison result is obtained, in which the proportion of cell types in the first slice is consistent with the proportion of cell types in the second slice.
[0040] Optionally, the determining module is specifically configured to cluster the gene expression conditions corresponding to the first slice according to the spatiotemporal transcriptome data of the first slice to obtain a first cluster image, and cluster the gene expression conditions corresponding to the second slice according to the spatiotemporal transcriptome data of the second slice to obtain a second cluster image;
[0041] If the difference between the first cluster image and the second cluster image is less than a second preset threshold, a first cluster comparison result is obtained, indicating that the gene expression in the first slice is consistent with the gene expression in the second slice; if the difference between the first cluster image and the second cluster image is greater than or equal to the second preset threshold, a first cluster comparison result is obtained, indicating that the gene expression in the first slice is inconsistent with the gene expression in the second slice.
[0042] Optionally, the determining module is specifically configured to determine the gene expression level in the first slice based on the spatiotemporal transcriptome data of the first slice, and determine the gene expression level in the second slice based on the spatiotemporal transcriptome data of the second slice;
[0043] If the correlation coefficient between the gene expression amount in the first slice and the gene expression amount in the second slice is less than the third preset threshold, a first correlation analysis result is obtained, indicating that the gene expression amount in the first slice is not correlated with the gene expression amount in the second slice; if the correlation coefficient between the gene expression amount in the first slice and the gene expression amount in the second slice is greater than or equal to the third preset threshold, a first correlation analysis result is obtained, indicating that the gene expression amount in the first slice is correlated with the gene expression amount in the second slice.
[0044] Optionally, the acquisition module is further configured to acquire spatiotemporal transcriptome data of a third slice of the target tissue, where the distance between the third slice and the first slice is less than a second preset distance;
[0045] The determining module is further configured to determine a second cell type comparison result, a second clustering comparison result, and a second correlation analysis result based on the spatiotemporal transcriptome data of the first slice and the spatiotemporal transcriptome data of the third slice;
[0046] The analysis module is specifically used to obtain an evaluation result of the heterogeneity of the target tissue based on the first cell type comparison result, the first cluster comparison result, the first correlation analysis result, and the second cell type comparison result, the second cluster comparison result, and the second correlation analysis result.
[0047] Optionally, the analysis module is further configured to use the spatiotemporal transcriptome data of the first slice or the second slice as the spatiotemporal transcriptome data of the target tissue if the evaluation result of the heterogeneity of the target tissue indicates that the target tissue does not have heterogeneity.
[0048] In a third aspect, the present application provides a device comprising: a processor and a memory;
[0049] One or more computer programs are stored in the memory, and the one or more computer programs include instructions; when the instructions are executed by the processor, the electronic device executes the method as described in any one of the first aspects.
[0050] In a fourth aspect, the present application provides a computer storage medium comprising computer instructions. When the computer instructions are executed on an electronic device, the electronic device executes the method as described in any one of the first aspects.
[0051] In a fifth aspect, the present application provides a computer program product. When the computer program product is run on a computer, the computer executes the method as described in any one of the first aspects.
[0052] The technical solution of this application has the following beneficial effects:
[0053] The present application provides a method for evaluating the heterogeneity of tissue slice tissue data and related equipment, the method comprising: obtaining spatiotemporal transcriptome data of a first slice of a target tissue and spatiotemporal transcriptome data of a second slice of the target tissue, wherein the distance between the first slice and the second slice is greater than a first preset distance; determining a first cell type comparison result, a first cluster comparison result, and a first correlation analysis result based on the spatiotemporal transcriptome data of the first slice and the spatiotemporal transcriptome data of the second slice; obtaining an evaluation result of the heterogeneity of the target tissue based on the first cell type comparison result, the first cluster comparison result, and the first correlation analysis result. It can be seen that the method analyzes the heterogeneity of tissue slice data based on multiple results, and then obtains an evaluation result of the heterogeneity of the target tissue.
[0054] It should be understood that the description of technical features, technical solutions, beneficial effects or similar language in this application does not imply that all features and advantages can be realized in any single embodiment. On the contrary, it is understood that the description of a feature or beneficial effect means that a specific technical feature, technical solution or beneficial effect is included in at least one embodiment. Therefore, the description of a technical feature, technical solution or beneficial effect in this specification does not necessarily refer to the same embodiment. Furthermore, the technical features, technical solutions and beneficial effects described in the present embodiment can also be combined in any appropriate manner. Those skilled in the art will understand that the embodiment can be implemented without one or more specific technical features, technical solutions or beneficial effects of a specific embodiment. In other embodiments, additional technical features and beneficial effects can also be identified in specific embodiments that do not embody all embodiments. BRIEF DESCRIPTION OF THE DRAWINGS
[0055] FIG1 is a flow chart of a method for evaluating heterogeneity of tissue slice data provided in an embodiment of the present application;
[0056] FIG2 is a schematic diagram of the proportion of cell types provided in an embodiment of the present application;
[0057] FIG3 is a schematic diagram of a cluster image provided in an embodiment of the present application;
[0058] FIG4 is a schematic diagram of an unsupervised clustering image provided in an embodiment of the present application;
[0059] FIG5 is a schematic diagram of a Spearman coefficient provided in an embodiment of the present application;
[0060] FIG6 is a schematic diagram of a slice selection method provided in an embodiment of the present application;
[0061] FIG7 is a schematic diagram of a device for evaluating heterogeneity of tissue slice tissue data provided in an embodiment of the present application. DETAILED DESCRIPTION
[0062] The terms "first", "second" and "third" in the specification, claims and drawings of this application are used to distinguish different objects rather than to limit a specific order.
[0063] In the embodiments of this application, words such as "exemplary" or "for example" are used to indicate examples, illustrations, or descriptions. Any embodiment or design described as "exemplary" or "for example" in the embodiments of this application should not be interpreted as being preferred or advantageous over other embodiments or designs. Rather, the use of words such as "exemplary" or "for example" is intended to present the relevant concepts in a concrete manner.
[0064] To make the description of the following embodiments clear and concise, a brief introduction to the related technologies is first given:
[0065] Spatiotemporal transcriptomics technology, used in life science research, was once named Technology of the Year. Consequently, research utilizing this technology is increasing, advancing research in areas such as species evolution, embryonic development, and disease mechanisms.
[0066] Currently, spatiotemporal transcriptomics technology can be used to capture mRNA in tissues based on spatiotemporal chips (Stereo Chip), and restore spatial positions through spatial barcodes (Coordinate ID, CID), enabling tissue spatial detection and establishing relationships between cell gene expression and morphology and the local environment. Compared with similar technologies, spatiotemporal omics (spatiotemporal transcriptomics) technology is a technology that can simultaneously achieve "subcellular resolution" and "centimeter-level panoramic field of view", and can achieve simultaneous analysis of genes and images. It has potential application prospects and value in RNA sequencing, spatially resolved epigenomics (such as chromatin accessibility analysis and DNA methylation detection) and genome sequencing. Compared with traditional bioinformatics omics research, it has greater research prospects and value.
[0067] The heterogeneity of tissue slice data refers to whether the gene expression patterns between different tissue slices are similar. However, there is currently no method to assess heterogeneity.
[0068] In view of this, the present application provides a method for evaluating the heterogeneity of tissue slice data, which can be performed by an evaluation device. Specifically, the method includes: the evaluation device obtains spatiotemporal transcriptome data of a first slice of a target tissue and spatiotemporal transcriptome data of a second slice of the target tissue, and the distance between the first slice and the second slice is greater than a first preset distance; based on the spatiotemporal transcriptome data of the first slice and the spatiotemporal transcriptome data of the second slice, a first cell type alignment result, a first cluster alignment result, and a first correlation analysis result are determined; based on the first cell type alignment result, the first cluster alignment result, and the first correlation analysis result, an evaluation result for the heterogeneity of the target tissue is obtained.
[0069] In order to make the technical solution of the present application clearer and easier to understand, the technical solution provided by the present application is introduced below from the perspective of the evaluation equipment in combination with the accompanying drawings.
[0070] As shown in FIG1 , this figure is a flow chart of a method for evaluating heterogeneity of tissue slice data provided in an embodiment of the present application, the method comprising:
[0071] S101. An evaluation device obtains spatiotemporal transcriptome data of a first slice of a target tissue and spatiotemporal transcriptome data of a second slice of the target tissue, wherein a distance between the first slice and the second slice is greater than a first preset distance.
[0072] The target tissue may be a tissue of a biological sample, and the biological sample may be an animal sample, a human sample, etc. The spatiotemporal transcriptome data may be data obtained by spatiotemporal omics technology.
[0073] The distance between the first slice and the second slice is greater than a first preset distance, where the first preset distance may be an empirically determined distance. In some examples, the first preset distance may have different values for different target tissues. The distance between the first slice and the second slice being greater than the first preset distance indicates that a sampling location of the first slice on the target tissue is farther away from a sampling location of the second slice on the target tissue. In some examples, the first preset distance may be 1 cm.
[0074] S102 : The evaluation device determines a first cell type comparison result, a first cluster comparison result, and a first correlation analysis result based on the spatiotemporal transcriptome data of the first slice and the spatiotemporal transcriptome data of the second slice.
[0075] In certain embodiments, the spatiotemporal transcriptome data captured by the assessment device can be summarized, and the spatiotemporal transcriptome data can be gem format data, and gem format data can be divided into 4 rows, the first row gene ID, the second row captures the horizontal coordinate of the position, the third row captures the vertical coordinate of the position, and the fourth row is the expression (also referred to as expression abundance) of the gene under the coordinate corresponding to the second and third rows, and the assessment device can process the above-mentioned spatiotemporal transcriptome data, and then obtain Spot (bin50) data, and the Spot (bin50) data can characterize the expression of genes under the window of 25*25um, then, singleR technology can be used to obtain cell type proportions (such as cell type and corresponding quantity) in the first slice. Specifically, the input of the singleR technology is above-mentioned Spot (bin50) data, and the output is above-mentioned cell type proportions, and the cell type proportions can be presented to the user in the form of an image. Similarly, the cell type proportions corresponding to the second slice can also be obtained, and the specific process is similar to the processing flow of the first slice, and will not be repeated here.
[0076] As shown in Figure 2, this figure is a schematic diagram of the cell type ratio provided in an embodiment of the present application. The horizontal axis: d1 represents the cell type ratio in the first slice, d2 represents the cell type ratio in the second slice, and d4 represents the cell type ratio in the fourth slice. The fourth slice can be a slice of the target tissue that is closer to the first slice. In this embodiment, the fourth slice is a slice of other tissues as an example; the vertical axis: represents the ratio.
[0077] In some embodiments, after the evaluation device determines the cell types and quantities included in the first slice based on the spatiotemporal transcriptome data of the first slice; and determines the cell types and quantities included in the second slice based on the spatiotemporal transcriptome data of the second slice, the chi-square value can be calculated based on the cell types and quantities included in the first slice and the cell types and quantities included in the second slice, and then the corresponding P value is determined based on the chi-square value. If the P value is less than a first preset threshold, a first cell type comparison result is obtained, in which the proportion of cell types in the first slice is inconsistent with the proportion of cell types in the second slice; if the P value is greater than or equal to the first preset threshold, a first cell type comparison result is obtained, in which the proportion of cell types in the first slice is consistent with the proportion of cell types in the second slice.
[0078] Specifically, the chi-square test related information is shown in Table 1 below.
[0079] Table 1:
[0080]
[0081] Then, based on Table 1 and the chi-square value calculation formula, the chi-square value corresponding to Table 1 is obtained. The chi-square value calculation formula is as follows:
[0082]
[0083] Among them, χ 2 The chi-square value is then calculated using the degree of freedom calculation method. A chi-square value of 12.857 corresponds to a P value of 0.00033621917105653283, i.e., P < 0.05 (the first preset threshold, generally 0.05), indicating that there is a difference between the cells in the first and second slices.
[0084] It should be noted that the above example only introduces the judgment method by taking the difference between the cells in the first slice and the second slice as an example. In the embodiment of the present application, it is not limited to the existence of or non-existence of differences between the cells in the first slice and the second slice.
[0085] In some embodiments, the evaluation device can cluster the gene expression conditions corresponding to the first slice based on the spatiotemporal transcriptome data of the first slice to obtain a first cluster image, and cluster the gene expression conditions corresponding to the second slice based on the spatiotemporal transcriptome data of the second slice to obtain a second cluster image; if the difference between the first cluster image and the second cluster image is less than a second preset threshold, a first cluster comparison result is obtained, in which the gene expression conditions in the first slice are consistent with the gene expression conditions in the second slice; if the difference between the first cluster image and the second cluster image is greater than or equal to the second preset threshold, a first cluster comparison result is obtained, in which the gene expression conditions in the first slice are inconsistent with the gene expression conditions in the second slice.
[0086] Continuing with the previous example, the evaluation device can obtain the corresponding Spot (bin50) data based on the spatiotemporal transcriptome data of the first slice, and then use the Leiden method to cluster based on gene expression to obtain the first cluster image. Similarly, the second cluster image corresponding to the second slice can also be obtained.
[0087] As shown in Figure 3, this figure is a schematic diagram of a cluster image provided by an embodiment of the present application. Figure 3(a) is a first cluster image corresponding to the first slice (which can be used to represent the spatial distribution of clusters), Figure 3(b) is the presentation result of a certain class of the first cluster image, Figure 3(c) is a second cluster image corresponding to the second slice (which can be used to represent the spatial distribution of clusters), and Figure 3(d) is the presentation result of a certain class of the second cluster image. In some embodiments, the evaluation device can compare the above Figures 3(b) and 3(d) to determine whether the first cluster image and the second cluster image are consistent in determining gene expression. Specifically, Figure 3(b) can represent the spatial distribution of the first class of genes on the first slice, and Figure 3(d) can represent the spatial distribution of the first class of genes on the second slice. If the difference between Figures 3(b) and 3(d) is less than a second preset threshold, it can be considered that the first cluster image and the second cluster image are consistent in determining gene expression. For example, the above-mentioned second preset threshold can be 20%, 10%, etc. In some examples, when the evaluation device determines that the difference between Figure 3(b) and Figure 3(d) is less than a second preset threshold, it determines a first clustering comparison result that the gene expression situation in the first slice is consistent with the gene expression situation in the second slice; when the evaluation device determines that the difference between Figure 3(b) and Figure 3(d) is greater than or equal to the second preset threshold, it determines a first clustering comparison result that the gene expression situation in the first slice is inconsistent with the gene expression situation in the second slice.
[0088] In other examples, the evaluation device can perform unsupervised clustering based on the expression of genes to obtain a first cluster image corresponding to the first slice and a second cluster image corresponding to the second slice. As shown in Figure 4, this figure is a schematic diagram of an unsupervised cluster image provided by an embodiment of the present application. Among them, Figure 4 (a) is the first cluster image corresponding to the first slice, Figure 4 (b) is the second cluster image corresponding to the second slice, and Figure 4 (d) is the fourth cluster image corresponding to the fourth slice. Figure 4 (c) is the overlapping image corresponding to multiple slices. In some examples, the evaluation device can determine whether the gene expression is consistent by judging the overlap between the above-mentioned cluster images. If the overlapping part of the cluster images is greater than a threshold (such as 50%), it indicates that the gene expression is consistent, otherwise it is inconsistent. In other examples, the evaluation device can calculate the shape difference between the first cluster image (such as Figure 4(a)) and the second cluster image (such as Figure 4(b)). If the shape difference is less than a threshold value (such as 20%), it is determined that the first cluster comparison result is consistent with the gene expression in the first slice and the gene expression in the second slice; if the shape difference is greater than or equal to the threshold value (such as 20%), it is determined that the first cluster comparison result is inconsistent with the gene expression in the first slice.
[0089] In some embodiments, the evaluation device determines the gene expression level in the first slice based on the spatiotemporal transcriptome data of the first slice, and determines the gene expression level in the second slice based on the spatiotemporal transcriptome data of the second slice; if the correlation coefficient between the gene expression level in the first slice and the gene expression level in the second slice is less than a third preset threshold, a first correlation analysis result is obtained, indicating that the gene expression level in the first slice is not correlated with the gene expression level in the second slice; if the correlation coefficient between the gene expression level in the first slice and the gene expression level in the second slice is greater than or equal to the third preset threshold, a first correlation analysis result is obtained, indicating that the gene expression level in the first slice is correlated with the gene expression level in the second slice.
[0090] In some examples, the correlation coefficient can be based on the Spearman coefficient, and the evaluation device can calculate the Spearman coefficient based on the gene expression levels of different slices, as shown in Figure 5, which is a schematic diagram of a Spearman coefficient provided in an embodiment of the present application. Among them, FP2000002457_K2, FP2000002457_L1, and FP2000002457_L3 are adjacent chips, FP2000002457_K1 is a chip of the same tissue that is farther away, and Other is a chip of other tissues. For example, FP2000002457_K2 is the chip corresponding to the first slice, FP2000002457_K1 is the chip corresponding to the second slice, FP2000002457_L1 is the chip corresponding to the third slice, and Other is the chip corresponding to the fourth slice.
[0091] In some examples, a correlation coefficient greater than 0.90 (a third preset threshold) is defined as a consistency evaluation indicator. If the correlation coefficient between the gene expression amount in the first slice and the gene expression amount in the second slice is greater than or equal to the third preset threshold, a first correlation analysis result is obtained, indicating that the gene expression amount in the first slice is correlated with the gene expression amount in the second slice. Otherwise, a first correlation analysis result is obtained, indicating that the gene expression amount in the first slice is not correlated with the gene expression amount in the second slice.
[0092] In other embodiments, the evaluation system can also perform differential analysis based on bulk data, with the data corresponding to each slice used as bulk data for differential analysis using edgeR. The proportion of upregulated and downregulated genes to the total gene count is calculated. If the cpm > 10, which is less than 6%, the gene expression is determined to be consistent, and a first correlation analysis result is obtained that the gene expression in the first slice is correlated with the gene expression in the second slice. Otherwise, a first correlation analysis result is obtained that the gene expression in the first slice is not correlated with the gene expression in the second slice.
[0093] S103. The evaluation device obtains an evaluation result for the heterogeneity of the target tissue according to the first cell type comparison result, the first cluster comparison result, and the first correlation analysis result.
[0094] In some embodiments, if the first cell type comparison result indicates that the proportion of cell types in the first slice is consistent with the proportion of cell types in the second slice; and the first cluster comparison result indicates that the gene expression in the first slice is consistent with the gene expression in the second slice; and the first correlation analysis result indicates that the gene expression amount in the first slice is correlated with the gene expression amount in the second slice, the evaluation device obtains an evaluation result that the target tissue does not have heterogeneity.
[0095] In other embodiments, if the first cell type comparison result indicates that the proportion of cell types in the first slice is inconsistent with the proportion of cell types in the second slice; or, the first cluster comparison result indicates that the gene expression in the first slice is inconsistent with the gene expression in the second slice; or, the first correlation analysis result indicates that the gene expression amount in the first slice is not correlated with the gene expression amount in the second slice, then an assessment result is obtained that the target tissue has heterogeneity.
[0096] Based on the above description, an embodiment of the present application provides a method for evaluating the heterogeneity of tissue slice tissue data, the method comprising: obtaining spatiotemporal transcriptome data of a first slice of a target tissue and spatiotemporal transcriptome data of a second slice of the target tissue, wherein the distance between the first slice and the second slice is greater than a first preset distance; determining a first cell type comparison result, a first cluster comparison result, and a first correlation analysis result based on the spatiotemporal transcriptome data of the first slice and the spatiotemporal transcriptome data of the second slice; obtaining an evaluation result for the heterogeneity of the target tissue based on the first cell type comparison result, the first cluster comparison result, and the first correlation analysis result. It can be seen that the method analyzes the heterogeneity of tissue slice data based on multiple results, and then obtains an evaluation result of the heterogeneity of the target tissue.
[0097] In some embodiments, the evaluation device may further obtain spatiotemporal transcriptome data of a third slice of the target tissue, wherein the distance between the third slice and the first slice is less than a second preset distance, wherein the second preset distance is less than or equal to the first preset distance. In some examples, the second preset distance may be 10 μm. Then, based on the spatiotemporal transcriptome data of the first slice and the spatiotemporal transcriptome data of the third slice, a second cell type comparison result, a second cluster comparison result, and a second correlation analysis result are determined. The specific determination process can be referred to the above embodiment and will not be repeated here.
[0098] Next, the evaluation device obtains an evaluation result for the heterogeneity of the target tissue based on the first cell type comparison result, the first cluster comparison result, the first correlation analysis result, and the second cell type comparison result, the second cluster comparison result, and the second correlation analysis result.
[0099] In this embodiment, the evaluation device not only determines the heterogeneity evaluation result based on adjacent slices that are farther away, but also combines adjacent slices that are closer, thereby further improving the accuracy of the evaluation result.
[0100] In some embodiments, if the target tissue heterogeneity assessment result indicates that the target tissue is not heterogeneous, the spatiotemporal transcriptome data of the first slice or the second slice is used as the spatiotemporal transcriptome data of the target tissue. If the target tissue is not heterogeneous, the target tissue portion can be used to represent the entire target tissue, saving a considerable amount of time and improving efficiency for clinical and other research.
[0101] The following is an introduction with specific examples.
[0102] As shown in Figure 6, this figure is a schematic diagram of a slice selection provided in an embodiment of the present application. In the embodiment of the present application, adjacent slices of the target tissue, slices that are farther apart, and other tissue slices of the same sample can be selected. Among them, adjacent slices can be used to determine whether adjacent slices can represent the spatial expression of the target tissue in the vicinity; slices that are farther apart are used to determine whether slices that are farther apart can represent the spatial expression of the target tissue that is farther apart; other tissue slices of the same sample are used for control experiments to obtain various thresholds.
[0103] As shown in FIG7 , this figure is a schematic diagram of a device for evaluating heterogeneity of tissue slice tissue data provided in an embodiment of the present application, the device comprising:
[0104] An acquisition module 701 is configured to acquire spatiotemporal transcriptome data of a first slice of a target tissue and spatiotemporal transcriptome data of a second slice of the target tissue, wherein a distance between the first slice and the second slice is greater than a first preset distance;
[0105] a determination module 702 for determining a first cell type alignment result, a first cluster alignment result, and a first correlation analysis result based on the spatiotemporal transcriptome data of the first slice and the spatiotemporal transcriptome data of the second slice;
[0106] The analysis module 703 is configured to obtain an evaluation result of the heterogeneity of the target tissue based on the first cell type comparison result, the first cluster comparison result, and the first correlation analysis result.
[0107] Optionally, the analysis module 703 is specifically used to obtain an assessment result that the target tissue does not have heterogeneity if the first cell type comparison result indicates that the proportion of cell types in the first slice is consistent with the proportion of cell types in the second slice; and the first cluster comparison result indicates that the gene expression status in the first slice is consistent with the gene expression status in the second slice; and the first correlation analysis result indicates that the gene expression level in the first slice is correlated with the gene expression level in the second slice.
[0108] Optionally, the analysis module 703 is also used to obtain an assessment result that the target tissue has heterogeneity if the first cell type comparison result indicates that the proportion of cell types in the first slice is inconsistent with the proportion of cell types in the second slice; or the first cluster comparison result indicates that the gene expression in the first slice is inconsistent with the gene expression in the second slice; or the first correlation analysis result indicates that the gene expression amount in the first slice is not correlated with the gene expression amount in the second slice.
[0109] Optionally, the determining module 702 is specifically configured to determine the cell type and number included in the first slice based on the spatiotemporal transcriptome data of the first slice; and determine the cell type and number included in the second slice based on the spatiotemporal transcriptome data of the second slice;
[0110] Calculating a chi-square value based on the cell types and numbers included in the first slice and the cell types and numbers included in the second slice;
[0111] According to the chi-square value, the corresponding P value is determined. If the P value is less than a first preset threshold, a first cell type comparison result is obtained, in which the proportion of cell types in the first slice is inconsistent with the proportion of cell types in the second slice; if the P value is greater than or equal to the first preset threshold, a first cell type comparison result is obtained, in which the proportion of cell types in the first slice is consistent with the proportion of cell types in the second slice.
[0112] Optionally, the determining module 702 is specifically configured to cluster the gene expression conditions corresponding to the first slice according to the spatiotemporal transcriptome data of the first slice to obtain a first cluster image, and cluster the gene expression conditions corresponding to the second slice according to the spatiotemporal transcriptome data of the second slice to obtain a second cluster image;
[0113] If the difference between the first cluster image and the second cluster image is less than a second preset threshold, a first cluster comparison result is obtained, indicating that the gene expression in the first slice is consistent with the gene expression in the second slice; if the difference between the first cluster image and the second cluster image is greater than or equal to the second preset threshold, a first cluster comparison result is obtained, indicating that the gene expression in the first slice is inconsistent with the gene expression in the second slice.
[0114] Optionally, the determining module 702 is specifically configured to determine the gene expression level in the first slice based on the spatiotemporal transcriptome data of the first slice, and determine the gene expression level in the second slice based on the spatiotemporal transcriptome data of the second slice;
[0115] If the correlation coefficient between the gene expression amount in the first slice and the gene expression amount in the second slice is less than the third preset threshold, a first correlation analysis result is obtained, indicating that the gene expression amount in the first slice is not correlated with the gene expression amount in the second slice; if the correlation coefficient between the gene expression amount in the first slice and the gene expression amount in the second slice is greater than or equal to the third preset threshold, a first correlation analysis result is obtained, indicating that the gene expression amount in the first slice is correlated with the gene expression amount in the second slice.
[0116] Optionally, the acquisition module 701 is further configured to acquire spatiotemporal transcriptome data of a third slice of the target tissue, where the distance between the third slice and the first slice is less than a second preset distance;
[0117] The determining module 702 is further configured to determine a second cell type alignment result, a second cluster alignment result, and a second correlation analysis result based on the spatiotemporal transcriptome data of the first slice and the spatiotemporal transcriptome data of the third slice;
[0118] The analysis module 703 is specifically used to obtain an evaluation result of the heterogeneity of the target tissue based on the first cell type comparison result, the first cluster comparison result, the first correlation analysis result, and the second cell type comparison result, the second cluster comparison result, and the second correlation analysis result.
[0119] Optionally, the analysis module 703 is further configured to use the spatiotemporal transcriptome data of the first slice or the second slice as the spatiotemporal transcriptome data of the target tissue if the evaluation result of the heterogeneity of the target tissue indicates that the target tissue has no heterogeneity.
[0120] An embodiment of the present application further provides a device, the device comprising: a processor and a memory;
[0121] One or more computer programs are stored in the memory, and the one or more computer programs include instructions; when the instructions are executed by the processor, the electronic device executes the method as described in any one of the method embodiments.
[0122] An embodiment of the present application further provides a computer storage medium, which includes computer instructions. When the computer instructions are executed on an electronic device, the electronic device executes the method as described in any one of the method embodiments.
[0123] An embodiment of the present application further provides a computer program product. When the computer program product is run on a computer, the computer executes the method as described in any one of the method embodiments.
[0124] It should also be noted that the device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separate, 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 across multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the present embodiment. In addition, in the drawings of the device embodiments provided in this application, the connection relationship between the modules indicates that there is a communication connection between them, which can be specifically implemented as one or more communication buses or signal lines.
[0125] Through the description of the above embodiments, those skilled in the art can clearly understand that the present application can be implemented by means of software plus necessary general hardware, and of course can also be implemented by special hardware including application-specific integrated circuits, special CPUs, special memories, special components, etc. In general, all functions performed by computer programs can be easily implemented with corresponding hardware, and the specific hardware structures used to implement the same function can also be diverse, such as analog circuits, digital circuits or special circuits, etc. However, for the present application, software program implementation is a better implementation method in most cases. Based on this understanding, the technical solution of the present application is essentially or the part that contributes to the prior art can be embodied in the form of a software product, which is stored in a readable storage medium, such as a computer's floppy disk, USB flash drive, mobile hard disk, ROM, RAM, magnetic disk or optical disk, etc., and includes a number of instructions to enable a computer device (which can be a personal computer, training equipment, or network equipment, etc.) to execute the methods described in each embodiment of the present application.
[0126] In the above embodiments, all or part of the embodiments may be implemented by software, hardware, firmware, or any combination thereof. When implemented by software, all or part of the embodiments may be implemented in the form of a computer program product.
[0127] The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from a website, a computer, a training device or a data center by wired (e.g., coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) mode to another website, a computer, a training device or a data center. The computer-readable storage medium can be any available medium that a computer can store or a data storage device such as a training device, a data center, etc. that includes one or more available media integrations. The available medium can be a magnetic medium, (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium (e.g., a solid-state drive (SSD)).
Claims
1. A method for evaluating the heterogeneity of tissue slice data, characterized in that: include: Acquire spatiotemporal transcriptome data of a first slice of a target tissue and spatiotemporal transcriptome data of a second slice of the target tissue, wherein a distance between the first slice and the second slice is greater than a first preset distance; Determining a first cell type comparison result, a first clustering comparison result, and a first correlation analysis result according to the spatiotemporal transcriptome data of the first slice and the spatiotemporal transcriptome data of the second slice; An evaluation result of the heterogeneity of the target tissue is obtained according to the first cell type comparison result, the first cluster comparison result and the first correlation analysis result.
2. The method according to claim 1, characterized in that The step of obtaining an evaluation result of the heterogeneity of the target tissue according to the first cell type comparison result, the first cluster comparison result and the first correlation analysis result includes: If the first cell type comparison result indicates that the proportion of cell types in the first slice is consistent with the proportion of cell types in the second slice; and the first cluster comparison result indicates that the gene expression in the first slice is consistent with the gene expression in the second slice; and the first correlation analysis result indicates that the gene expression amount in the first slice is correlated with the gene expression amount in the second slice, then an assessment result is obtained that the target tissue does not have heterogeneity.
3. The method according to claim 2, characterized in that The method further comprises: If the first cell type comparison result indicates that the proportion of cell types in the first slice is inconsistent with the proportion of cell types in the second slice; or, the first cluster comparison result indicates that the gene expression in the first slice is inconsistent with the gene expression in the second slice; or, the first correlation analysis result indicates that the gene expression amount in the first slice is not correlated with the gene expression amount in the second slice, then an assessment result is obtained that the target tissue has heterogeneity.
4. The method according to any one of claims 1 to 3, characterized in that: The process of determining the first cell type comparison result includes: Determine the type and quantity of cells included in the first slice according to the spatiotemporal transcriptome data of the first slice; determine the type and quantity of cells included in the second slice according to the spatiotemporal transcriptome data of the second slice; Calculating a chi-square value according to the cell types and numbers included in the first slice and the cell types and numbers included in the second slice; According to the chi-square value, the corresponding P value is determined. If the P value is less than a first preset threshold value, a first cell type comparison result is obtained in which the proportion of cell types in the first slice is inconsistent with the proportion of cell types in the second slice; if the P value is greater than or equal to the first preset threshold value, a first cell type comparison result is obtained in which the proportion of cell types in the first slice is consistent with the proportion of cell types in the second slice.
5. The method according to any one of claims 1 to 3, characterized in that: The process of determining the first cluster comparison result includes: Clustering the gene expression conditions corresponding to the first slice according to the spatiotemporal transcriptome data of the first slice to obtain a first cluster image, and clustering the gene expression conditions corresponding to the second slice according to the spatiotemporal transcriptome data of the second slice to obtain a second cluster image; If the difference between the first cluster image and the second cluster image is less than a second preset threshold, a first cluster comparison result is obtained, in which the gene expression in the first slice is consistent with the gene expression in the second slice; if the difference between the first cluster image and the second cluster image is greater than or equal to the second preset threshold, a first cluster comparison result is obtained, in which the gene expression in the first slice is inconsistent with the gene expression in the second slice.
6. The method according to any one of claims 1 to 3, characterized in that: The process of determining the first correlation analysis result includes: Determine the gene expression level in the first slice according to the spatiotemporal transcriptome data of the first slice, and determine the gene expression level in the second slice according to the spatiotemporal transcriptome data of the second slice; If the correlation coefficient between the gene expression amount in the first slice and the gene expression amount in the second slice is less than the third preset threshold, a first correlation analysis result is obtained, indicating that the gene expression amount in the first slice is not correlated with the gene expression amount in the second slice; if the correlation coefficient between the gene expression amount in the first slice and the gene expression amount in the second slice is greater than or equal to the third preset threshold, a first correlation analysis result is obtained, indicating that the gene expression amount in the first slice is correlated with the gene expression amount in the second slice.
7. The method according to claim 1, characterized in that The method further comprises: Acquiring spatiotemporal transcriptome data of a third slice of the target tissue, wherein the distance between the third slice and the first slice is less than a second preset distance; Determining a second cell type comparison result, a second clustering comparison result, and a second correlation analysis result according to the spatiotemporal transcriptome data of the first slice and the spatiotemporal transcriptome data of the third slice; Obtaining an evaluation result of the heterogeneity of the target tissue according to the first cell type comparison result, the first cluster comparison result, and the first correlation analysis result, including: Based on the first cell type alignment result, the first cluster alignment result, the first correlation analysis result, and the second cell type alignment result, the second cluster alignment result, and the second correlation analysis result, an evaluation result of the heterogeneity of the target tissue is obtained.
8. The method according to claim 1, characterized in that The method further comprises: If the evaluation result of the heterogeneity of the target tissue indicates that the target tissue has no heterogeneity, the spatiotemporal transcriptome data of the first slice or the second slice is used as the spatiotemporal transcriptome data of the target tissue.
9. A device for evaluating the heterogeneity of tissue slice tissue data, characterized in that: include: An acquisition module, configured to acquire spatiotemporal transcriptome data of a first slice of a target tissue and spatiotemporal transcriptome data of a second slice of the target tissue, wherein a distance between the first slice and the second slice is greater than a first preset distance; A determination module, configured to determine a first cell type comparison result, a first clustering comparison result, and a first correlation analysis result according to the spatiotemporal transcriptome data of the first slice and the spatiotemporal transcriptome data of the second slice; An analysis module is used to obtain an evaluation result of the heterogeneity of the target tissue according to the first cell type comparison result, the first cluster comparison result and the first correlation analysis result.
10. A device, characterized in that: include: Processor and memory; One or more computer programs are stored in the memory, and the one or more computer programs include instructions; when the instructions are executed by the processor, the electronic device executes the method as described in any one of claims 1 to 8.
11. A computer storage medium, characterized in that: The method comprises computer instructions. When the computer instructions are executed on an electronic device, the electronic device executes the method as claimed in any one of claims 1 to 8.
12. A computer program product, characterized in that When the computer program product runs on a computer, the computer executes the method according to any one of claims 1 to 8.