Analysis method, device and storage medium for non-invasive prenatal genetic testing sequencing data

Abstract

The present application discloses an analysis method, device and storage medium for sequencing data of non-invasive prenatal genetic testing. The method of the present application includes obtaining the original sequencing results of samples with two or more chromosomal aneuploidies from NIPT sequencing data, aligning them with the reference genome, and removing mismatched or duplicate reads; calculating the Z values ​​of chromosomes other than Y and chromosome 19 according to the NIFTY algorithm, and calculating the average of the top five absolute values ​​of the Z values. If it is greater than the threshold, the subject to be tested is judged to be a high-risk population for tumors. The present application is the first to use the average of the top five absolute values ​​of the chromosome Z values ​​of MCA samples in NIPT testing to evaluate the tumor situation during pregnancy. The analysis method of the present application can directly use NIPT sequencing data, which is simple and convenient, and there is no additional cost other than NIPT sequencing, which further expands the use of NIPT in detecting occult maternal cancers during pregnancy.

Description

Technical Field

[0001] The present application relates to the technical field of gene sequencing data analysis, and in particular to an analysis method, device and storage medium for non-invasive prenatal gene testing sequencing data. Background Art

[0002] Pregnancy complicated by cancer is relatively rare, with an incidence rate of 0.07% to 0.1%. The more common types of tumors include lymphoma, breast cancer, ovarian cancer, melanoma, leukemia, and colorectal cancer. Due to the hidden and latent nature of tumors and their occurrence during pregnancy, common symptoms of tumors can be masked by physiological changes during pregnancy. Due to the particularity of pregnancy, considering the inherent risks of fetal exposure to supplementary examinations, such as ionizing radiation, it is not easy for doctors to immediately check the causes of these symptoms; on the other hand, pregnancy interferes with the sensitivity and specificity of diagnostic methods, and even when symptoms are properly examined, there is still a high rate of misdiagnosis or missed diagnosis.

[0003] The peripheral blood of cancer patients contains circulating tumor DNA (ctDNA) of tumor origin. ctDNA only accounts for a small part of all free DNA fragments (cell-fell DNA, cfDNA) in maternal peripheral blood. ctDNA carries its tumor-related molecular characteristics and can be used in liquid biopsy, which has important clinical application value. During pregnancy, most of the cfDNA in the peripheral blood of pregnant women comes from the mother's hematopoietic system, and there is a small amount of cfDNA derived from the apoptosis of placental trophoblasts and released into the mother's blood circulation system. If the mother has a tumor, some tumor apoptosis ctDNA will also be present in the cfDNA.

[0004] Non-invasive prenatal testing (NIPT), or non-invasive prenatal genetic testing, is a non-invasive prenatal screening technology that detects abnormalities in the number of fetal chromosomes by high-throughput sequencing analysis of cell-free DNA fragments (cfDNA) in maternal peripheral blood. Compared with traditional screening methods, non-invasive prenatal genetic testing is safe and convenient; and it can detect Down syndrome (T21), Edwards syndrome (T18), and Patau syndrome (T13) with high sensitivity and high specificity. NIPT began commercial application in 2011. According to statistics from BGI, more than 10 million NIPT tests have been performed worldwide to date. Chromosome Z scores are often used in NIPT tests to assess fetal chromosomal aneuploidy. Generally, the absolute value of the Z score >3 is usually used as the risk threshold.

[0005] Existing studies have shown that tumors are one of the reasons for the failure of non-invasive prenatal genetic testing or false positives; and there are studies reporting cases of accidental discovery of tumor samples in samples with multiple chromosome outliers in NITP data. Bianchi et al. published their results in JAMA, retrospectively analyzing NIPT abnormal samples, i.e., aneuploidy of one or more chromosomes, and studied the incidence of tumors in various types of abnormal NIPT samples, and came to the following conclusions: The incidence of aneuploidy of two or more chromosomes can be as high as 18%, with a 95% confidence interval of 7.5%-33.5%. Ji, X., et al. developed an information analysis algorithm for detecting maternal tumors in NIPT abnormal (multiple staining aneuploidy) samples based on copy number variation (CNV) in the literature (Identifying occult maternal malignancies from 1.93 million pregnant women undergoing noninvasive prenatal screening tests. Genet Med, 2019). Its sensitivity (sensitivity) and specificity (specificity) are 83% and 85%, respectively. If combined with tumor marker information, the positive predictive value (PPV) is increased to 75%. This method has initially solved the problem of tumor prediction, but it cannot give a specific tumor type.

[0006] At present, the detection technologies for tumors mainly include:

[0007] (1) Detection of serological tumor markers, such as CA125, CA19-9, CEA, HGF and other serum proteins, plays a certain role in the diagnosis and detection of tumors.

[0008] (2) CT, MRI and other imaging methods.

[0009] (3) Tumor detection based on next-generation sequencing technology mainly includes the following schemes:

[0010] a) Genomic variation at the SNV level: Recent studies on ctDNA have shown that tumor-specific mutation studies can be used for early tumor screening by detecting tumor-specific somatic mutations through methods such as high-depth targeted sequencing or multiplex PCR.

[0011] b) Copy number variation detection: Whole genome sequencing of ctDNA can detect chromosome-level variations or copy number variations.

[0012] c) Methylation: Studies in recent years have shown that methylation biomarkers can also be used for tumor prediction.

[0013] d) Tumor cfDNA fragments have unique nucleosome-related imprints: cfDNA sequencing can reflect the length of cfDNA fragments wrapped in nucleosomes. The study by Jiang P et al. pointed out that in the detection of tumor fragments in cfDNA of liver cancer patients, it was found that the length of cfDNA fragments in liver cancer patients was partially shorter than that of normal people. Cristiano S et al. used the ratio of short fragments in each interval of cfDNA in the whole genome as a feature to predict tumors and identify their tissue types. The position of nucleosomes and the position of the ends of cfDNA fragments on the genome show a certain correlation with tumors and their tissue sources.

[0014] In existing products and published tumor prediction research results, the above technologies are usually used in combination. For example, Guardant Health's LUNAR-2 (https: / / guardanthealth.com / solutions / #lunar-2) combines the above three schemes a, c, and d to achieve a higher sensitivity in colorectal cancer, but the specific method is unknown.

[0015] Natera's postoperative tumor detection product Signature (https: / / www.natera.com / signatera) is based on the above-mentioned plan A and selects 16 specific SNV sites, which can achieve ultra-high sensitivity in recurrence detection of colorectal cancer and lung cancer.

[0016] In 2018, Joshua D. Cohen's team published a research result in Science. CancerSEEK, a tumor detection method based on serum markers and SNV, showed a specificity of 99% in 1,005 patients with eight different types of tumors, including lung cancer, liver cancer, and colorectal cancer. The sensitivity ranged from 69% to 98% depending on the type of cancer.

[0017] The detection of serological tumor markers has certain value in the diagnosis and management of tumor patients, but because the levels of tumor markers will change significantly during pregnancy, they lack sensitivity and specificity. The levels of commonly used tumor markers CA153, SCC, CA125 and AFP increase during pregnancy; the levels of CEA, CA 19-9, LDH, AMH, and HE-4 generally do not increase. In theory, they play a certain role in the examination of tumors.

[0018] Imaging methods such as CT and MRI have a high risk of false positives and false negatives for early tumor screening, making it difficult to achieve early screening for tumors. In addition, due to the particularity of pregnancy, considering the inherent risks of fetal exposure to supplementary examinations, such as ionizing radiation, it is not easy for doctors to immediately check the cause of these symptoms.

[0019] Based on the next generation sequencing technology, various schemes for tumor detection have their defects and shortcomings. For example, scheme a, genomic variation at the SNV level, not all patients can detect specific variation, and the high experimental cost makes it difficult to achieve large-scale popularization. Scheme b, copy number variation detection, only a small number of individuals have this type of variation. Scheme c, methylation detection, is expensive and difficult to be widely used. Scheme d, tumor cfDNA fragments have unique nucleosome-related imprints, which usually require a high sequencing depth and are difficult to apply to routine clinical testing only in the scientific research exploration stage.

[0020] In summary, there is currently no technology that can effectively predict asymptomatic tumors during pregnancy based on non-invasive prenatal genetic testing. How to use non-invasive prenatal genetic testing sequencing data to provide intermediate results or reference data for the prediction of asymptomatic tumors during pregnancy is an urgent problem to be solved. Summary of the invention

[0021] The purpose of this application is to provide a new analysis method, device and storage medium for non-invasive prenatal genetic testing sequencing data.

[0022] In order to achieve the above objectives, this application adopts the following technical solutions:

[0023] The first aspect of the present application discloses a method for analyzing sequencing data of non-invasive prenatal genetic testing, comprising the following steps:

[0024] The steps of obtaining and aligning chromosome aneuploidy include obtaining the original sequencing results of samples with two or more chromosome aneuploidies (MCA) from the sequencing data of non-invasive prenatal genetic testing, aligning them with the reference genome, and removing mismatched or duplicated reads;

[0025] The steps of calculating chromosome Z scores include calculating the Z scores of chromosomes other than chromosome Y and chromosome 19 according to the NIFTY algorithm, and calculating the average of the top five absolute values ​​of Z scores, which is marked as M TOP5 Z scores;

[0026] The step of assessing the risk of tumor during pregnancy includes comparing the M TOP5 Z scores of the subject to be tested with a threshold value. If the M TOP5 Z scores are greater than the threshold value, the subject to be tested is judged to be a high-risk group for tumors.

[0027] The threshold is used to assess tumor risk by using several tumor samples and several normal samples as training sets, M TOP5 Z scores as input, and whether it is a tumor sample as output.

[0028] It should be noted that this application cleverly uses the average chromosome Z score of MCA samples in NIPT testing for the first time to evaluate tumors during pregnancy, and creatively uses the average of the top five chromosomes with the largest absolute value of the Z score of other chromosomes, except for chromosome Y and chromosome 19, as the threshold for tumor assessment during pregnancy, which has high sensitivity and specificity in detecting asymptomatic maternal cancer. The analysis method of this application is simple and the analysis does not involve additional costs for sequencing or experiments, which further expands the use of NIPT in detecting occult maternal cancers during pregnancy, and is of great significance to expanding the application of NIPT in screening for occult maternal cancers other than fetal trisomy 21, 13, and 18 during pregnancy.

[0029] It is understandable that the analysis method of the present application ultimately obtains only the tumor risk of the subject to be tested, which can only be used as intermediate reference data and cannot be directly used for diagnosis; in principle, for the subject to be tested who is judged to be a high-risk group for tumors, further medical examinations are required to determine whether they are sick. Therefore, the analysis method of the present application can be used for extensive screening of occult maternal cancers and provide a scientific reference for the prediction of asymptomatic tumors during pregnancy.

[0030] In one implementation of the present application, the formula for calculating the Z value of a chromosome according to the NIFTY algorithm is: Z value = (cr ij -cr' ij ) / sd j

[0031] Among them, cr ij is the ratio of the number of reads of chromosome j in sample i to the total number of reads in sample i, cr' ij is the ratio of the number of reads of chromosome j in sample i to the total number of reads in sample i after GC correction, sd j is the reference control population (cr ij -cr' ij ) standard deviation. The reference control population refers to the samples tested in the same batch, that is, sd j is the total number of samples tested in the same batch (cr ij -cr' ij )’s standard deviation.

[0032] It should be noted that the Z value of chromosomes calculated according to the NIFTY algorithm in this application can refer to the document: Jiang F, Ren J, Chen F, et al. Noninvasive Fetal Trisomy (NIFTY) test: an advanced noninvasive prenatal diagnosis methodology for fetal autosomal and sex chromosomal aneuploidies. BMC medical genomics, 2012, 5 (1): 1-11. Therefore, all relevant contents about Z value calculation in this document are cited in this application.

[0033] In one implementation of the present application, the calculation formula of M TOP5 Z scores is:

[0034]

[0035] Among them, absolute z scores are the absolute values ​​of Z values.

[0036] In one implementation of the present application, in the step of obtaining and comparing chromosome aneuploidies, the presence of two or more chromosome aneuploidies means that two or more chromosome aneuploidies appear in chromosomes other than chromosome Y and chromosome 19.

[0037] It should be noted that the reason for excluding chromosome Y and chromosome 19 is that studies have found that the copy number abnormality rate of chromosome 19 is too high, and there are fetal sex differences in chromosome Y; therefore, these two chromosomes are excluded when defining MCA and M TOP5 Z scores.

[0038] In one implementation of the present application, the training set includes at least 42 tumor samples and at least 294 normal samples, and the threshold value obtained by training is 5.94.

[0039] It should be noted that the threshold is 5.94, and the training set includes at least 42 tumor samples and at least 294 normal samples, which are the samples and thresholds specifically used in an implementation of the present application. It can be understood that under the inventive concept of the present application, more or fewer samples can be used, and the specific thresholds obtained may also be different, which are not specifically limited here.

[0040] The second aspect of the present application discloses an analysis device for sequencing data of non-invasive prenatal genetic testing, including a chromosome aneuploidy acquisition and comparison module, a chromosome Z value calculation module, a threshold training module and a pregnancy tumor risk assessment module; the chromosome aneuploidy acquisition and comparison module includes a module for obtaining the original sequencing results of samples with two or more chromosome aneuploidies from the sequencing data of non-invasive prenatal genetic testing, comparing it with the reference genome, and removing mismatched or repeated reads; the chromosome Z value calculation module includes a module for calculating the Z values ​​of other chromosomes except chromosome Y and chromosome 19 according to the NIFTY algorithm, and calculating the average of the top five absolute values ​​of the Z values, marked as M TOP5 Zscores; the threshold training module includes a module for taking a number of tumor samples and a number of normal samples as training sets, taking M TOP5 Zscores as input, and whether it is a tumor sample as output, to obtain a threshold for assessing tumor risk; the pregnancy tumor risk assessment module includes a module for comparing the M TOP5 Z scores of the subject to be tested with the threshold obtained by the M TOP5 Z scores threshold training module, and if the M TOP5 Z scores of the subject to be tested are If the scores are greater than the threshold, the subject is judged to be a high-risk group for cancer.

[0041] It should be noted that in the analysis device of the present application, the threshold training module is mainly used to obtain the threshold using the training set; it can be understood that when the threshold has been obtained, the threshold can be used directly; therefore, the threshold training module does not need to be run every time. Of course, in the case of new objects to be tested and their test results, the test results of the new objects to be tested can also be provided to the threshold training module for further training and improvement, so that the threshold obtained can be more accurately and effectively used for tumor risk assessment.

[0042] It should also be noted that the analysis device for non-invasive prenatal genetic testing sequencing data of the present application actually implements each step in the analysis method for non-invasive prenatal genetic testing sequencing data of the present application through each module; therefore, the specific limitations of each module can refer to the analysis method for non-invasive prenatal genetic testing sequencing data of the present application, which will not be repeated here. For example, the NIFTY algorithm, the calculation formula of M TOP5 Z scores, the number of training set samples and thresholds, etc., can all refer to the analysis method for non-invasive prenatal genetic testing sequencing data of the present application.

[0043] The third aspect of the present application discloses an analysis device for non-invasive prenatal genetic testing sequencing data, which includes a memory and a processor; the memory includes a device for storing programs; the processor includes a device for implementing the analysis method for non-invasive prenatal genetic testing sequencing data of the present application by executing the programs stored in the memory.

[0044] The fourth aspect of the present application discloses a computer-readable storage medium, in which a program is stored. The program can be executed by a processor to implement the analysis method of non-invasive prenatal genetic testing sequencing data of the present application.

[0045] Due to the adoption of the above technical solution, the beneficial effects of this application are:

[0046] The analysis method of non-invasive prenatal genetic testing sequencing data in this application uses the average of the top five absolute values ​​of chromosome Z values ​​of MCA samples in NIPT testing for the first time to evaluate tumor conditions during pregnancy; the analysis method of this application can directly use NIPT sequencing data, which is simple and convenient, and has no additional costs other than NIPT sequencing, further expanding the use of NIPT in detecting occult maternal cancers during pregnancy. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] Figure 1 It is a flowchart of the method for analyzing sequencing data of non-invasive prenatal genetic testing in an embodiment of the present application;

[0048] Figure 2 It is a structural block diagram of a device for analyzing sequencing data of non-invasive prenatal genetic testing in an embodiment of the present application;

[0049] Figure 3 This is a graph showing the abnormal ratio of polyploidy and haploidy of chromosome 19 in pregnant women with tumors and healthy pregnant women in the embodiment of the present application;

[0050] Figure 4 This is a comparative analysis chart of the M TOP5 Z scores of 62 tumor samples and 434 normal samples in the embodiment of the present application;

[0051] Figure 5 It is the ROC curve of the training set and the validation set M TOP5 Z scores in the embodiment of the present application. DETAILED DESCRIPTION

[0052] The present application is further described in detail below by specific embodiments in conjunction with the accompanying drawings. In the following embodiments, many detailed descriptions are intended to enable the present application to be better understood. However, those skilled in the art can easily recognize that some of the features can be omitted in different situations, or can be replaced by other devices, materials, and methods. In some cases, some operations related to the present application are not shown or described in the specification in order to avoid the core part of the present application being overwhelmed by too much description, and for those skilled in the art, it is not necessary to describe these related operations in detail, and the related operations can be fully understood according to the description in the specification and the general technical knowledge in the art.

[0053] So far, there is no method that can directly use non-invasive prenatal genetic testing to effectively predict asymptomatic tumors during pregnancy. This application cleverly uses the average chromosome Z score of MCA samples in NIPT testing to evaluate tumors during pregnancy. The method is simple and the analysis does not involve additional costs for sequencing or experiments. It further expands the use of NIPT in detecting occult maternal cancers during pregnancy, and does not require additional costs, which is convenient for product formation and promotion. The basic inventive concept of this application is to use the Z score generated in the NIPT test to determine whether a pregnant woman has a tumor. Specifically, the chromosome Z scores of samples with two or more chromosomal aneuploidies (MCA) in the NIPT test are analyzed. The M TOP5 Z scores refer to the average of the top five chromosomes with the largest absolute values ​​of the Z scores, except for chromosomes Y and 19. The M TOP5 Z scores are used to evaluate the risk of tumors during pregnancy.

[0054] Based on the above ideas, this application creatively proposes a method for analyzing sequencing data of non-invasive prenatal genetic testing, such as Figure 1 As shown, the method includes a chromosome aneuploidy acquisition and comparison step 11, a chromosome Z value calculation step 12 and a pregnancy tumor risk assessment step 13.

[0055] Among them, the chromosome aneuploidy acquisition and comparison step 11 includes obtaining the original sequencing results of samples with two or more chromosome aneuploidies from the sequencing data of non-invasive prenatal genetic testing, comparing them with the reference genome, and removing mismatched or duplicated reads.

[0056] In one implementation of the present application, bwa is used to compare with the reference genome hg19 to remove unmatched reads and duplicate reads.

[0057] The chromosome Z score calculation step 12 includes calculating the Z scores of other chromosomes except the Y chromosome and chromosome 19 according to the NIFTY algorithm, and calculating the average of the top five absolute values ​​of the Z scores, which is marked as M TOP5 Z scores.

[0058] In one implementation of the present application, the specific calculation formula is: Z value = (cr ij -cr' ij ) / sd j

[0059] Among them, cr ij is the ratio of the number of reads of chromosome j in sample i to the total number of reads in sample i, cr' ijis the ratio of the number of reads of chromosome j in sample i to the total number of reads in sample i after GC correction, sd j is the reference control population (cr ij -cr' ij ) standard deviation. The reference control population refers to the samples tested in the same batch, that is, sd j is the total number of samples tested in the same batch (cr ij -cr' ij ) standard deviation. For detailed description and explanation of the Z-score calculation formula, please refer to Jiang F, Ren J, Chen F, et al. Noninvasive Fetal Trisomy (NIFTY) test: an advanced noninvasive prenatal diagnosis methodology for fetal autosomal and sex chromosomal aneuploidies. BMC medical genomics, 2012, 5(1): 1-11.

[0060] In the samples of pregnancy tumors (n=62) and normal controls (n=434) in this application, the proportions of chr19 deletion (Z value <-3) and chr19 amplification (Z value > 3) in normal pregnant samples were 53.92% and 21.89%, respectively. The proportions of chr19 deletion (Z value <-3) and chr19 amplification (Z value > 3) in tumor pregnant samples were 22.58% and 45.16%, respectively. Figure 3 As shown. Given the high rate of chr19 copy number abnormalities and the existence of fetal sex differences in the Y chromosome, these two chromosomes are excluded when defining MCA and M TOP5 Zscores in this application. MCA is defined as the absolute value of the Z score of at least two chromosomes other than the Y chromosome and chromosome 19 > 3.0.

[0061] The step 13 of assessing the risk of tumor during pregnancy includes comparing the M TOP5 Z scores of the subject to be tested with a threshold. If the M TOP5 Z scores are greater than the threshold, the subject to be tested is judged to be a high-risk group for tumors. The threshold is a threshold for assessing tumor risk obtained by using a number of tumor samples and a number of normal samples as a training set, the M TOP5 Z scores as input, and whether it is a tumor sample as output.

[0062] In one implementation of the present application, the training set includes 42 tumor samples and 294 normal samples, and the threshold of M TOP5 Zscores is determined to be 5.94. If the MTOP5Zscores calculated for the sample to be tested is greater than 5.94, it means that the sample belongs to a high-risk group for tumors, and a medical examination is recommended.

[0063] Those skilled in the art will appreciate that all or part of the functions of the above method can be implemented by hardware or by computer program. When all or part of the functions in the above method are implemented by computer program, the program can be stored in a computer-readable storage medium, and the storage medium can include: read-only memory, random access memory, disk, CD, hard disk, etc., and the program is executed by a computer to implement the above functions. For example, the program is stored in the memory of the device, and when the program in the memory is executed by the processor, all or part of the above functions can be implemented. In addition, when all or part of the functions in the above implementation are implemented by computer program, the program can also be stored in a storage medium such as a server, another computer, disk, CD, flash disk or mobile hard disk, and saved in the memory of the local device by downloading or copying, or the system of the local device is updated, and when the program in the memory is executed by the processor, all or part of the functions in the above method can be implemented.

[0064] Therefore, based on the analysis method of non-invasive prenatal genetic testing sequencing data of the present application, the present application proposes an analysis device for non-invasive prenatal genetic testing sequencing data, such as Figure 2 As shown, it includes a chromosome aneuploidy acquisition and comparison module 21, a chromosome Z value calculation module 22, a threshold training module 23 and a pregnancy tumor risk assessment module 24.

[0065] Among them, the chromosome aneuploidy acquisition and comparison module 21 includes a module for obtaining the original sequencing results of samples with two or more chromosome aneuploidies from the sequencing data of non-invasive prenatal genetic testing, comparing them with the reference genome, and removing mismatched or duplicated reads. For example, the reference bwa is compared with the reference genome hg19.

[0066] The chromosome Z score calculation module 22 includes a module for calculating the Z scores of other chromosomes except the Y chromosome and chromosome 19 according to the NIFTY algorithm, and calculating the average of the top five absolute values ​​of the Z scores, which is marked as M TOP5 Z scores.

[0067] For example, the calculation formula for M TOP5 Z scores is,

[0068]

[0069] Among them, absolute z scores are the absolute values ​​of Z values.

[0070] The threshold training module 23 includes a module for obtaining a threshold for assessing tumor risk by using a number of tumor samples and a number of normal samples as training sets, M TOP5Z scores as input, and whether or not the sample is a tumor as output.

[0071] For example, 42 tumor samples and 294 normal samples were used as training sets, and the threshold of M TOP5 Zscores was finally determined to be 5.94.

[0072] The pregnancy tumor risk assessment module 24 includes a module for comparing the M TOP5 Z scores of the subject to be tested with the threshold value obtained by the threshold training module. If the M TOP5 Z scores of the subject to be tested is greater than the threshold value, the subject to be tested is determined to be a high-risk group for tumors.

[0073] Another implementation of the present application provides an analysis device for sequencing data of non-invasive prenatal genetic testing, the device comprising a memory and a processor; the memory comprising a device for storing a program; the processor comprising a device for executing the program stored in the memory to implement the following method: a chromosome aneuploidy acquisition and comparison step, comprising obtaining the original sequencing results of samples with two or more chromosome aneuploidies (Multiple Chromosomes Aneuploidies, MCA) from the sequencing data of the non-invasive prenatal genetic testing, comparing the original sequencing results with the reference genome, and removing mismatched or repeated reads; a chromosome Z value calculation step, comprising calculating the Z values ​​of other chromosomes except the Y chromosome and chromosome 19 according to the NIFTY algorithm, and calculating the average of the top five absolute values ​​of the Z values, marked as M TOP5 Z scores; a pregnancy tumor risk assessment step, comprising comparing the M TOP5 Z scores of the subject to be tested with a threshold value, and if the M TOP5 Z scores are greater than the threshold value, judging that the subject to be tested is a high-risk population for tumors; wherein the threshold value is a training set of a number of tumor samples and a number of normal samples, and a training set of M TOP5 Z scores. Scores are input, whether there is a tumor sample is output, and the threshold used to assess tumor risk is obtained.

[0074] Another implementation of the present application also provides a computer-readable storage medium, which includes a program that can be executed by a processor to implement the following method: a chromosome aneuploidy acquisition and comparison step, including obtaining the original sequencing results of samples with two or more chromosome aneuploidies (Multiple chromosome aneuploidies, MCA) from the sequencing data of non-invasive prenatal genetic testing, comparing them with the reference genome, and removing unmatched or duplicated reads; a chromosome Z value calculation step, including calculating the Z values ​​of other chromosomes except chromosome Y and chromosome 19 according to the NIFTY algorithm, and calculating the average of the top five absolute values ​​of the Z values, marked as M TOP5 Zscores; a pregnancy tumor risk assessment step, including comparing the M TOP5 Z scores of the subject to be tested with a threshold, if the M TOP5 Z scores are greater than the threshold, then judging that the subject to be tested is a high-risk population for tumors; wherein the threshold is a threshold for assessing tumor risk obtained by using a number of tumor samples and a number of normal samples as a training set, the M TOP5 Z scores as input, and whether it is a tumor sample as output.

[0075] Example

[0076] This example uses NIPT sequencing data from 62 tumor samples and 434 normal samples. All samples are samples with NIPT test results of MCA, that is, except for chromosome Y and chromosome 19, at least two chromosomes have an absolute value of Z score greater than 3.0. The 62 tumor samples and 434 normal samples are divided into two groups, one for the training set and the other for the validation set. Among them, the training set contains 42 tumor samples and 294 normal samples, and the validation set contains 20 tumors and 140 normal samples. This example calculates the M TOP5 Z scores of each sample, uses the training set to obtain the threshold, and uses the validation set to verify the analysis method of this non-invasive prenatal genetic testing sequencing data and the accuracy of tumor risk assessment. The details are as follows:

[0077] (1) Obtain NIPT data from 62 tumor samples and 434 normal subjects;

[0078] (2) For the sequencing data of each sample, use bwa to align with the reference genome hg19 and remove unmatched reads and duplicate reads;

[0079] (3) The NIFTY algorithm reported in the literature by Jiang F, Ren J, Chen F, et al. Noninvasive Fetal Trisomy (NIFTY) test: an advanced noninvasive prenatal diagnosis methodology for fetal autosomal and sex chromosomal aneuploidies. BMC medical genomics, 2012, 5(1): 1-11 was used to calculate the Z score of each chromosome except chromosome Y and chromosome 19, and the average of the top five absolute values ​​of the Z score in each sample was calculated, which was marked as M TOP5 Z scores.

[0080] The formula for the Z value is,

[0081] Z value = (cr ij -cr' ij ) / sd j

[0082] Among them, cr ij is the ratio of the number of reads of chromosome j in sample i to the total number of reads in sample i, cr' ij is the ratio of the number of reads of chromosome j in sample i to the total number of reads in sample i after GC correction, sd j is the reference control population (cr ij -cr' ij ) standard deviation. The reference control population refers to the samples tested in the same batch, that is, sd j is the total number of samples tested in the same batch (cr ij -cr' ij ). For example, for the training set, it is all samples tested in the same batch of 42 tumor samples and 294 normal samples; for the validation set, it is all samples tested in the same batch of 20 tumor samples and 140 normal samples.

[0083] The calculation formula for M TOP5 Z scores is:

[0084]

[0085] Among them, absolute z scores are the absolute values ​​of Z values.

[0086] Using 42 tumor samples and 294 normal samples in the training set, with M TOP5 Z scores as input and whether it is a tumor sample as output, we obtain the threshold for assessing tumor risk. In this example, the specific threshold of M TOP5 Z scores is 5.94. If the M TOP5 Z scores calculated for the sample to be tested is greater than 5.94, it means that the sample belongs to a high-risk group for tumors, and medical examination is recommended.

[0087] Based on the obtained threshold value of 5.94, tumor risk assessment was performed on 20 tumors and 140 normal samples in the validation set. The tumor risk assessment results were compared with the actual situation to verify the analysis method of the non-invasive prenatal genetic testing sequencing data in this case and the accuracy of the tumor risk assessment.

[0088] The effectiveness of the analysis method in this example in screening for malignant tumors during pregnancy in the training set and validation set is as follows: Figure 4 , Figure 5 And as shown in Table 1.

[0089] Table 1 Evaluation of the effect of M TOP5 Z scores in screening for tumors during pregnancy in the training set and validation set

[0090]

[0091] In Table 1, the values ​​in brackets are the 95% confidence intervals of the corresponding parameters.

[0092] Figure 4 Comparison of M TOP5 Z scores of 62 tumor samples and 434 normal samples. Figure 5 ROC curve for the training set and validation set M TOP5 Z scores. Figure 4 , Figure 5 The results in Table 1 show that compared with normal people, tumor patients have higher M TOP5 Z scores; the ROC curve of the training set shows that the training set AUC is 90.56%, and the ROC curve of the validation set shows that the validation set AUC is 88.14%.

[0093] It can be seen that the analysis method of the sequencing data of non-invasive prenatal genetic testing in this case can predict asymptomatic tumors during pregnancy, with a sensitivity of more than 85%, and the highest sensitivity of the 95% confidence interval can reach more than 96%; and the specificity is more than 80%, and the highest specificity of the 95% confidence interval can reach more than 88%. Therefore, the analysis method of the sequencing data of non-invasive prenatal genetic testing in this case can be used for early screening of occult maternal cancer, further expanding the application of NIPT.

[0094] The above contents are further detailed descriptions of the present application in combination with specific implementation methods, and it cannot be determined that the specific implementation of the present application is limited to these descriptions. For ordinary technicians in the technical field to which the present application belongs, several simple deductions or substitutions can be made without departing from the concept of the present application.

Claims

1. A method for analyzing sequencing data of non-invasive prenatal genetic testing, characterized in that: The following steps are included: The steps of obtaining and aligning chromosome aneuploidy include obtaining the original sequencing results of samples with two or more chromosome aneuploidies from the sequencing data of non-invasive prenatal genetic testing, aligning them with the reference genome, and removing mismatched or duplicated reads; The steps of calculating the chromosome Z score include calculating the Z scores of chromosomes other than chromosome Y and chromosome 19 according to the NIFTY algorithm, and calculating the average of the top five absolute values ​​of the Z scores, which is marked as M TOP5Z scores; The step of assessing the risk of cancer during pregnancy includes comparing the MTOP5 Z scores of the subject to be tested with a threshold value. If the MTOP5 Z scores are greater than the threshold value, the subject to be tested is judged to be a high-risk group for cancer. The threshold is a threshold used to assess tumor risk, obtained by using a number of tumor samples and a number of normal samples as training sets, M TOP5 Z scores as input, and whether or not a tumor sample is output; The formula for calculating the Z value of chromosomes according to the NIFTY algorithm is: Z value = (cr ij - cr' ij ) / sd j Among them, cr ij is the ratio of the number of reads of chromosome j in sample i to the total number of reads in sample i, cr' ij is the ratio of the number of reads of chromosome j in sample i to the total number of reads in sample i after GC correction, sd j is the reference control population (cr ij -cr' ij )’s standard deviation; The calculation formula of the M TOP5 Z scores is: Among them, absolute z scores are the absolute values ​​of Z values; In the step of obtaining and comparing chromosome aneuploidy, the occurrence of two or more chromosome aneuploidies means that two or more chromosome aneuploidies occur in chromosomes other than chromosome Y and chromosome 19.

2. A device for analyzing sequencing data of non-invasive prenatal genetic testing, characterized in that: It includes a chromosome aneuploidy acquisition and comparison module, a chromosome Z value calculation module, a threshold training module, and a pregnancy tumor risk assessment module; The chromosome aneuploidy acquisition and comparison module includes a module for obtaining the original sequencing results of samples with two or more chromosome aneuploidies from the sequencing data of non-invasive prenatal genetic testing, comparing them with the reference genome, and removing mismatched or duplicated reads; The chromosome Z score calculation module includes a module for calculating the Z scores of other chromosomes except the Y chromosome and chromosome 19 according to the NIFTY algorithm, and calculating the average of the top five absolute values ​​of the Z scores, which is marked as M TOP5 Z scores; The threshold training module includes a module for obtaining a threshold for assessing tumor risk by using a number of tumor samples and a number of normal samples as training sets, using M TOP5 Zscores as input, and whether or not the sample is a tumor as output; The pregnancy tumor risk assessment module includes a module for comparing the M TOP5 Z scores of the subject to be tested with the threshold value obtained by the threshold training module, and if the M TOP5 Z scores of the subject to be tested is greater than the threshold value, the subject to be tested is judged to be a high-risk group for tumors; The formula for calculating the Z value of chromosomes according to the NIFTY algorithm is: Z value = (cr ij - cr' ij ) / sd j Among them, cr ij is the ratio of the number of reads of chromosome j in sample i to the total number of reads in sample i, cr' ij is the ratio of the number of reads of chromosome j in sample i to the total number of reads in sample i after GC correction, sd j is the reference control population (cr ij -cr' ij )’s standard deviation; The calculation formula of the M TOP5 Z scores is: Among them, absolute z scores are the absolute values ​​of Z values; In the chromosome aneuploidy acquisition and comparison module, the occurrence of two or more chromosome aneuploidies means that two or more chromosome aneuploidies occur in chromosomes other than chromosome Y and chromosome 19.

3. A device for analyzing sequencing data of non-invasive prenatal genetic testing, characterized in that: The analysis device comprises: Memory, used to store programs; A processor, configured to implement the method for analyzing sequencing data of non-invasive prenatal genetic testing as claimed in claim 1 by executing the program stored in the memory.

4. A computer-readable storage medium, characterized in that: It includes a program that can be executed by a processor to implement the analysis method of non-invasive prenatal genetic testing sequencing data as described in claim 1.

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