Assays and genotyping for hemoglobin A (HBA) detection

Abstract

To provide assays and genotyping methods for the detection of hemoglobin A (HBA). [Solution] This disclosure relates to a hemoglobin A (HBA) assay and an HBA genotype determination tree matrix for implementation in clinical trials. More specifically, the embodiments relate to obtaining raw data from an HBA assay performed on multiple samples, calculating a first set of probe ratios for each sample based on the raw data, identifying the number of reference samples to be combined as a synthetic reference sample based on the first set of probe ratios, calculating a second set of probe ratios for each of the multiple samples based on the raw data and the synthetic reference samples, and determining the HBA genotype of each sample by a decision tree matrix based on the second set of probe ratios for each sample and the copy number call threshold of the sample probe / reference probe ratio associated with each probe of the multiple probes.

Description

[Technical Field]

[0001] Priority Claim This application claims the benefit and priority of U.S. Provisional Application No. 62 / 986,152, filed on March 6, 2020, which is incorporated herein by reference in its entirety for all purposes.

[0002] field This disclosure relates to hemoglobin A (HBA) clinical trials, and more particularly to techniques for HBA assays and decision tree matrices for HBA genotyping for implementation in clinical trials. [Background technology]

[0003] background Hemoglobin is an iron-rich protein in red blood cells that carries oxygen to cells throughout the body. This protein is composed of two α-globin units and two β-globin subunits, the former encoded by the HBA1 and HBA2 genes, and the latter by the HBB gene. When these genes are altered (changed) or deleted, thalassemia develops. The hemoglobin protein subunit affected in alpha-thalassemia (α-thalassemia) is alpha-globin. A person who inherits a defective α-thalassemia gene from one parent but a normal α-thalassemia gene from the other parent is an α-thalassemia carrier. α-thalassemia carriers usually have no signs or symptoms. However, they may pass on their incomplete gene to their children. People with moderate to severe forms of α-thalassemia have inherited multiple incomplete α-thalassemia genes from both parents. These are inherited in an autosomal recessive pattern. Alpha-thalassemia is the most common genetic disorder of hemoglobin synthesis worldwide, with mutation allele frequencies ranging between 1% and 98% across tropical and subtropical regions where malaria is prevalent. While alpha-thalassemia can occur in all ethnic groups, it is more common in people of Southeast Asian descent. The high prevalence of alpha-thalassemia in certain populations is likely due to protection from infection by Plasmodium parasites (multiple species of Plasmodium) resulting from one or two deletion copies of the HBA gene. The American College of Obstetricians and Gynecologists recommends screening for hemoglobin disorders in people of African, Southeast Asian, Mediterranean, Middle Eastern, or West Indian descent, although hemoglobin disorders are becoming more prevalent in mixed populations.

[0004] Alpha-globin is encoded by two genes on chromosome 16 (α-globin genes, HBA1 and HBA2). Each individual requires four functional HBA genes (two from each parent) to produce enough α-globin for the body's hemoglobin to function normally. If one or more of these genes are deficient, various forms of α-thalassemia develop. If one gene is deficient, the individual is a "silent" carrier of the α-thalassemia trait and usually has no signs or symptoms. If two genes are deficient, the individual has the α-thalassemia trait (also called α-thalassemia minor) and may have mild anemia. If three genes are deficient, the individual has hemoglobin H disorder, which can cause moderate to severe anemia. If all four genes are deficient, the individual has major α-thalassemia (also called hemoglobin Bart fetal hydrops or fetal hydrops). This is the most severe type of α-thalassemia. Fetuses with this disorder usually die in the womb, or the child dies shortly after birth because they are unable to produce normal hemoglobin to carry oxygen throughout the body.

[0005] Over 90% of α-thalassemia cases result from the deletion of two or more copies of the α-globin genes (HBA1 and HBA2) on chromosome 16. The HBA1 and HBA2 genes are located within an approximately 30kb α-globin gene cluster on chromosome 16, which includes the following α-globin genes and telomere-to-centromere (pseudogenes) in this order: HBZ, (HBZP1)HBM, (HBAP1), HBA2, HBA1, HBQ1 (see, for example, Figure 1). The coding sequences of HBA1 and HBA2 are identical to the branching sequences located in the introns and the 5' and 3' untranslated regions. Furthermore, deletion of the HS-40 major hypersensitive site located 40kb upstream of the HBZ gene in the promoter region affects the RNA expression of both HBA1 and HBA2, thereby causing the α-thalassemia trait in heterozygotes. Hb Constant Spring point mutations at the first base of the stop codon in HBA2 affect HBA2 RNA expression and cause more severe phenotypes than HBA2 deletion alleles. Finally, gene conversion between HBA1 and HBA2 is common due to their proximity and high homology, but has no clinical significance. Considering these factors, it may be desirable to develop assays for HBA detection that can genotype multiple different loci in the α-globin region to facilitate screening of α-thalassemia. [Overview of the project] [Means for solving the problem]

[0006] Abstract In various embodiments, raw data is obtained from hemoglobin A (HBA) assays performed on multiple samples, wherein the HBA assay is performed using multiple probes capable of detecting a decrease or increase in the copy number within the α-globin gene cluster region of each of the multiple samples, the raw data includes HBA copy number data of multiple probes separated by capillary electrophoresis for each of the multiple samples, a reference sample is selected from the multiple samples, a first set of probe ratios for each of the multiple samples is calculated based on the raw data obtained from the HBA assay and the reference sample, and based on the first set of probe ratios, the multiple samples A computer implementation method is provided, which includes identifying a predetermined number of reference samples to be combined as a synthetic reference sample; generating a synthetic reference sample based on the predetermined number of reference samples; calculating a second set of probe ratios for each of the multiple samples based on the raw data obtained from the HBA assay and the synthetic reference sample; iteratively inputting the second set of probe ratios for each sample into a decision tree matrix; determining the HBA genotype of each sample based on the second set of probe ratios for each sample and the copy number call threshold of the sample probe / reference probe ratio associated with each probe of the multiple probes using the decision tree matrix; and providing the HBA genotype of each sample.

[0007] In some embodiments, calculating a first set of probe ratios includes: (i) comparing the peak height or signal of a control probe in each sample of a plurality of samples with the peak height or signal of a corresponding control probe in a reference sample; (ii) calculating the signal variation between the peak height or signal of the control probe in each sample and the peak height or signal of the corresponding control probe in the reference sample as the standard deviation of the control probe; (iii) determining that a sample of the plurality of samples is unacceptable if any variation index is greater than a predetermined threshold; (iv) determining that a sample of the plurality of samples is not unacceptable if none of the variation indexes are greater than a predetermined threshold; and (v) for each unacceptable sample, comparing the peak height or signal of a test probe in the sample with the peak height of a corresponding test probe in the reference sample, and calculating the probe ratio between the peak height or signal of the test probe in the sample and the peak height or signal of the corresponding test probe in the reference sample.

[0008] In some embodiments, calculating a second set of probe ratios includes: (i) comparing the peak height or signal of a control probe in each sample of a plurality of samples with the peak height or signal of the corresponding control probe in a synthetic reference sample; (ii) calculating the signal variation between the peak height or signal of the control probe in each sample and the peak height or signal of the corresponding control probe in the synthetic reference sample as the standard deviation of the control probe; (iii) determining that a sample of the plurality of samples is unacceptable if any variation index is greater than a predetermined threshold; (iv) determining that a sample of the plurality of samples is not unacceptable if none of the variation indexes are greater than a predetermined threshold; and (v) for each unacceptable sample, comparing the peak height or signal of a test probe in the sample with the peak height of the corresponding test probe in a synthetic reference sample, and calculating the probe ratio between the peak height or signal of the test probe in the sample and the peak height or signal of the corresponding test probe in a synthetic reference sample.

[0009] In some embodiments, determining the HBA genotype for each sample includes (i) determining an abnormal probe ratio pattern for each sample based on a second set of probe ratios for each sample and a copy number call threshold for the sample probe / reference probe ratio associated with each probe among a plurality of probes, and (ii) identifying the HBA genotype for each sample based on the abnormal probe ratio pattern.

[0010] In some embodiments, determining the pattern of abnormal probe ratios and identifying the HBA genotype of each sample includes classifying each sample as normal with copy number variation (CNV) or as polymorphic based on the pattern of abnormal probe ratios, and subclassifying any sample classified as having CNV based on the pattern of abnormal probe ratios as a major targeted deletion, duplication, or “other”.

[0011] In some embodiments, determining the abnormal probe ratio pattern and identifying the HBA genotype of each sample, subclassifying any sample classified as having a large targeted deletion as having a large heterozygous or homozygous deletion, based on the abnormal probe ratio pattern, the following deletions: SEA, FIL / THAI, MED, or α 20.5 For one or more of the following, any sample classified as a large heterozygous deletion or homozygous deletion will be subclassified, and based on the pattern of abnormal probe ratios, large heterozygous deletions and below, i.e., α 3.7 Deletion, α 4.2 Deletion or α 3.7 This further includes subclassifying any sample that has been classified as having one or more of the same characteristics.

[0012] In some embodiments, determining the pattern of abnormal probe ratios and identifying the HBA genotype of each sample is used to subclassify any sample classified as having "other," and based on the pattern of abnormal probe ratios, any sample classified as "other" is classified as α 3.7 Deletion, α 4.2 Deletion, and / or α 3.7 This further includes subclassifying items as having overlaps.

[0013] In some embodiments, the method further includes triggering a confirmation test on each of several samples having an abnormal HBA genotype or not requiring manual review.

[0014] In some embodiments, a system is provided that includes one or more data processors and a non-temporary computer-readable storage medium containing instructions that, when executed on the one or more data processors, cause the one or more data processors to execute all or part of one or more methods or processes disclosed herein.

[0015] In some embodiments, a computer program product is provided which is tangibly embodied in the form of a non-temporary machine-readable storage medium and includes instructions configured to cause one or more data processors to perform some or all of the methods of one or more disclosed herein.

[0016] Some embodiments of this disclosure include a system comprising one or more data processors. In some embodiments, the system includes a non-temporary computer-readable storage medium containing instructions that, when run on one or more data processors, cause one or more data processors to perform some or all of the one or more methods and / or some or all of the one or more processes disclosed herein. Some embodiments of this disclosure include a computer program product tangibly embodied in the form of a non-temporary machine-readable storage medium containing instructions configured to cause one or more data processors to perform some or all of the one or more methods and / or some or all of the one or more processes disclosed herein.

[0017] The terms and expressions used are for illustrative purposes only, not limitation, and in using such terms and expressions, there is no intention to exclude equivalents of the exhibited and described features or any part thereof, but it should be understood that various modifications are possible within the scope of the claimed invention. Accordingly, although the present invention is specifically disclosed by embodiments and optional features, modifications and variations of the concepts disclosed herein are left to those skilled in the art, and it should be understood that such modifications and variations are deemed to fall within the scope of the present invention as defined by the appended claims.

[0018] The present invention will be better understood by considering the following non-limiting figures. [Brief explanation of the drawing]

[0019] [Figure 1] Figure 1 shows the gene data of chromosome 16 in various embodiments.

[0020] [Figure 2] Figure 2 shows block diagrams of HBA assay platforms according to various embodiments.

[0021] [Figure 3A] Figure 3A shows an overview of MLPA assay chemistry in various embodiments.

[0022] [Figure 3B] Figure 3B shows 34 α-globin gene cluster region probes and common HBA deletion locations in various embodiments.

[0023] [Figure 4] Figure 4 shows exemplary flows for HBA assays and HBA genotyping using HBA assay platforms and genotyping technologies in various embodiments.

[0024] [Figure 5] Figure 5 shows an exemplary flow chart for HBA genotyping using an HBA assay platform and genotyping techniques in various embodiments.

[0025] [Figure 6] Figure 6 shows exemplary computing devices in various embodiments.

[0026] [Figure 7] Figure 7 shows probe-specific plots of the magnification change relative to the reference for α3.7HET deletion (sample B09) in various embodiments. [Modes for carrying out the invention]

[0027] In the accompanying drawings, similar components and / or features may have the same reference label. Furthermore, various components of the same type can be distinguished by following the reference label with a dash, and by a second label that distinguishes similar components from each other. Where only the first reference label is used herein, its description is applicable to any similar component having the same first reference label, regardless of the second reference label.

[0028] Detailed explanation The following description provides only preferred exemplary embodiments and is not intended to limit the scope, applicability, or configuration of the Disclosure. Rather, the following description of preferred exemplary embodiments provides a possible description for carrying out various embodiments for those skilled in the art. It will be understood that various modifications can be made to the function and arrangement of the elements without departing from the spirit and scope set forth in the appended claims.

[0029] The following description provides specific details to enable a complete understanding of the embodiments. However, it will be understood that embodiments can be carried out without these specific details. For example, circuits, systems, networks, processes, and other components may be shown as components in block diagram form to avoid unnecessarily detailing and obscuring the embodiments. In other examples, well-known circuits, processes, algorithms, structures, and techniques may be shown in a non-descriptive manner to avoid obscuring the embodiments.

[0030] Furthermore, note that individual embodiments may be described as processes shown as flowcharts, flow diagrams, data flow diagrams, structural diagrams, or block diagrams. While flowcharts or diagrams may describe operations as sequential processes, many operations may be performed in parallel or simultaneously. Moreover, the order of operations can be rearranged. A process terminates when its operation is complete, but it may have additional steps not shown in the diagram. A process may correspond to a method, function, procedure, subroutine, subprogram, etc. If a process corresponds to a function, its termination may correspond to the function's return to the called function or main function.

[0031] I. Introduction DNA analysis of the α-globin region can be performed by targeting multiple different loci using multiplex ligation-dependent probe amplification (MLPA). This method, developed by MRC Holland (product description SALSA® MLPA® probemix P140-C1 HBA), detects genomic deletions and duplications associated with this locus, such as the seven most common types of α-thalassemia deletions (α 3.7 , α 4.2 , SEA, MED, THAI, FIL, and α 20.5 ), as well as Constant Spring point mutations and HBAxHS-40 promoter deletions. Conventionally, HBA MLPA copy number data has been manually reviewed to determine genotypes due to the complexity of the α-globin region and the number of loci analyzed by the MLPA assay. Confirmatory tests can be performed by multiplex PCR and gel electrophoresis or Sanger sequencing. The problems associated with conventional HBA MLPA assays and manual genotyping are that they generate large amounts of MLPA copy number data from the α-globin region and utilize complex tables that lead to manual evaluation of the MLPA copy number data, which requires extensive training experience and time. Furthermore, conventional HBA MLPA assays typically exhibit a higher error rate for the evaluation steps performed during manual genotyping. This error rate gradually degrades the quality of screening tests and has an undesirable impact (e.g., false positives or overdiagnosis) and may incorrectly trigger costly confirmatory tests.

[0032] To address these limitations and problems, the various embodiments described herein relate to HBA assay and genotyping techniques that can reduce decision ambiguity and provide a comprehensive analysis of the results of each possible decision, while achieving a minimum error rate with limited processing, memory, and power resources. In some cases, processes have been developed that include a decision tree gating whether a confirmatory test should be performed on a sample based on whether the sample is determined to contain an HBA genotype indicating α-thalassemia. For example, the various embodiments of this disclosure include a system comprising one or more processors and memory coupled to one or more processors. This memory obtains raw data from HBA assays performed on multiple samples, wherein the HBA assay is performed using multiple probes capable of detecting a decrease or increase in the copy number within the α-globin gene cluster region of each of the multiple samples, the raw data includes HBA copy number data (e.g., MLPA copy number data) of multiple probes separated by capillary electrophoresis for each of the multiple samples, a reference sample is selected from the multiple samples, a first set of probe ratios for each of the multiple samples is calculated based on the raw data obtained from the HBA assay and the reference sample, and a synthetic reference sample is selected from the multiple samples based on the first set of probe ratios. It is coded as a set of instructions configured to perform a process including: identifying a predetermined number of reference samples to be combined as; generating a synthetic reference sample based on the predetermined number of reference samples; calculating a second set of probe ratios for each of the multiple samples based on the raw data obtained from the HBA assay and the synthetic reference sample; iteratively inputting the second set of probe ratios for each sample into a decision tree matrix; determining the HBA genotype of each sample based on the second set of probe ratios for each sample and a copy number call threshold of the sample probe / reference probe ratio associated with each probe of the multiple probes using the decision tree matrix; and providing the HBA genotype of each sample.In some cases, the technology may further include triggering a confirmation test on each of multiple samples that have an abnormal HBA genotype or do not require manual review.

[0033] Advantageously, these approaches provide HBA assay and genotyping techniques that can achieve minimum error rates in environments such as sequencing systems with limited processing, memory, and power resources. For example, decision trees can be implemented with a low power budget (e.g., a simple tree of conditions) and provide strong nonlinear classification capabilities in a multidimensional search space. Furthermore, nonlinear classification can be used to gate whether or not a confirmatory test should be performed on a sample, thereby saving the cost of incorrectly performing confirmatory tests and improving the overall robustness of the HBA assay.

[0034] As used herein, the terms “substantially,” “approximately,” and “about” are defined as largely (but not necessarily entirely) of what is specified (and all of what is specified), as understood by those skilled in the art. In any disclosed embodiment, the terms “substantially,” “approximately,” or “about” may be replaced with “within [percentage]” of what is specified, the percentages of which include 0.1, 1, 5, and 10 percent. As used herein, when an action is “based on” something, this means that the action is at least partially based on at least a part of something.

[0035] It will be understood that the HBA genotyping techniques disclosed herein can be applied to evaluate other types of sequencing raw data in comparison with the MLPA copy number data specifically described herein. It will also be understood that other assay methodologies and types of polymerase chain reaction (PCR) or multiplex (PCR) can be contemplated to identify one or more loci within a given chromosome or gene region (e.g., chromosome 16 or the α-globin region). For example, alternatively or additionally, reverse dot blot hybridization (RDB), Southern blot (SB), or Gap-PCR can be used to identify one or more loci within chromosome 16 or the α-globin region.

[0036] II. HBA assay techniques One or more embodiments described herein can be implemented using programmatic modules, engines, or components. These programmatic modules, engines, or components may include programs, subroutines, parts of programs, or software or hardware components capable of performing one or more of the described tasks or functions. Where used herein, a module or component may reside on a hardware component independently of other modules or components. Alternatively, a module or component may be a shared element or process of other modules, programs, or machines. Figure 2 shows a block diagram of an HBA assay platform 100 for detecting deletions and / or duplications in the α-globin region located on chromosome 16 as a potential cause, screening tool, and / or clinical diagnosis of α-thalassemia, and illustrates one or more processor-executable modules, engines, or components (e.g., programs, code, or instructions) that may be used to implement various subsystems of the analyzer system 205 according to various embodiments. The modules, engines, or components may be stored on non-temporary computer media. If necessary, one or more modules, engines, or components can be loaded into system memory (e.g., RAM) and executed by one or more processors of the analyzer system 205. The example shown in Figure 2 illustrates the modules, engines, or components that implement the gene analyzer subsystem 210 and the HBA genotyping subsystem 215.

[0037] Figure 2 also shows a wet laboratory subsystem 220, which includes a laboratory where chemicals, drugs, or other materials or biological substances are tested and analyzed, requiring water, direct ventilation, and dedicated piping utilities. The HBA assay platform 200, in block 230, includes obtaining one or more samples 225 within the wet laboratory subsystem 220. In some cases, the sample 225 contains nucleic acids extracted from human cell lines. In some cases, the sample 225 contains nucleic acids obtained from male or female patients. In some cases, the sample 225 is nucleic acids extracted from whole blood, amniotic fluid, amniotic fluid cell cultures, chorionic villus samples, or chorionic villus sample cell cultures obtained from male or female patients. In certain particular cases, the sample or sample 225 has one or more genomic deletions, point mutations, and / or duplications within the α-globin gene cluster region of chromosome 16.

[0038] In block 235 of the wet laboratory subsystem 220, an HBA assay is performed, which includes DNA analysis of the α-globin gene cluster region (HBA1 / HBA2, OMIM141800 / 141850, 16pter-16p13.3) by targeting multiple different gene loci using a multiplex assay method 250 (e.g., multiplex PCR). The multiplex assay method 250 targets seven of the most common types of α-thalassemia deletions (α 3.7 , α 4.2 SEA, MED, THAI, FIL and α 20.5 ), as well as detecting genomic deletions and duplications associated with this locus, including Constant Spring point mutations and HBAxHS-40 promoter deletions. In certain cases, the HBA assay detects (i)α 3.7 , α 4.2 ,SEA,MED,THAI,FIL,α 20.5(ii) to screen for carriers of HS-40 deletions, to identify at-risk couples by screening the carrier's partner for any of the HBA mutations, and / or (iii) for targeted family and prenatal testing for HBA deletions in which one or both parents have been confirmed to have a pathogenic mutation as described herein. Confirmatory tests can be performed by multiplex assays and gel electrophoresis or Sanger sequencing.

[0039] In various embodiments, the multiplex assay method 250 is MPLA technology (e.g., MPLA method developed by MRC Holland - Product Description SALSA® MLPA® probemix P140-C1 HBA), which is a semi-quantitative ligation-dependent multiplex PCR method that can determine the copy number difference in the target region by measuring the relative signal intensity between sample 225 and synthetic reference sample 240. The HBA assay uses a pool of MLPA oligonucleotides 245 such that a probe is formed when two oligonucleotides that hybridize directly adjacent to each other in the target sequence are ligated together. As shown in Figure 3A, each ligated probe 300 may consist of two oligonucleotides 305 (e.g., from the pool of oligonucleotides 245) with one end containing a hybridization sequence 310 specific to the target sequence and the other end containing a PCR primer 315 (e.g., a labeled universal PCR primer) sequence for multiplexing. In certain cases, stuffer sequences 320 of different lengths can be used to allow for different probe sizes. After sample and reference denaturation, oligonucleotide 305 is hybridized to the target sequence for a predetermined time (e.g., 16-20 hours). Following hybridization, two oligonucleotides 305 that hybridize to directly adjacent sites are ligated together to form a uniquely sized ligated probe 300. This reaction is highly specific and occurs only when there is no gap larger than a nick between the two oligonucleotides 305. The ligated probe 300 is PCR amplified using PCR primer 315. Ligated probes 300 that bind little to no or no to the target sequence due to SNPs or the absence of the target sequence will not be amplified.

[0040] In some embodiments, the HBA assay involves the use of 45 target-specific probes (amplification size 131–481 nucleotides), including 33 probes for detecting deletions and duplications in the α-globin gene cluster region and surrounding sequences, and one probe for the presence of Hb Constant Spring point mutations. Of the 33 probes, there are five single probes specific to either HBA1 or HBA2, and three probes targeting sequences present in both genes. That is, in a normal sample, two or four copies are detected by probe mapping to unique sequences, or by probe mapping to sequences present in both HBA1 and HBA2, respectively. Due to the high homology and proximity of the two genes, there are also five probe pairs that bind to different sequences at the same location in the HBA1 and HBA2 genes, such that one probe in a pair is specific to HBA1 and the other probe is specific to HBA2. These probe pairs are used to detect gene transformations or polymorphisms that may not have clinical significance but could confuse genotyping calls. If polymorphisms are present, a chromosome change in one probe in a pair indicates duplication, while the other indicates deletion. The 45 target-specific probes further include 11 control probes targeting reference sequences on other autosomes besides chromosome 16, used to normalize 33 probes for detecting copy number variations in the HBA region. In some cases, quality control fragments (Q and D fragments) and sex-specific fragments, which are single oligonucleotides, may be included to ensure that MLPA chemistry functions as expected. Figure 3B schematically shows the locations of probes detecting variants in the α-globin gene cluster region and surrounding sequences, as well as the locations of targeted deletions in this test. The locations of paired probes (P) capable of detecting polymorphisms due to gene conversion between HBA1 and HBA2, probes mapped to both HBA1 and HBA2 (thick arrows), and probes for Hb Constant Spring (CS) are shown. FIL and THAI deletions are detected by the same probes and require multiplex PCR for differentiation. In some cases, α 3.7 , α4.2 Furthermore, the deletion boundaries of MEDs may differ, and their detection may require different probes.

[0041] In any block 255, post-PCR cleanup can be performed on the PCR product (e.g., amplified ligated probe). In some cases, post-PCR cleanup includes mixing the PCR product with magnetic beads, washing with a washing solution such as 70% ethanol, air-drying, and eluting the purified PCR product 260 to increase the signal-to-noise ratio. After amplification and post-PCR cleanup, the purified PCR product 260 can be loaded into an analytical instrument system 205 (e.g., a fluorescence-based separation instrument system) for downstream processing.

[0042] In block 265, the multiplex assay product or any purified PCR product 260 is separated using capillary electrophoresis, detected using labeling, e.g., a fluorescent dye, and output as raw data 270, including HBA copy number data. In some cases, the raw data 270 may be generated, collected, and stored in the analyzer system 205 in memory storage. In block 275, the analyzer subsystem 210 retrieves the raw data 270 for each sample from the analyzer system 205, determines the amplicon sizing, and automatically selects the normalized sample with the least variation in peak height ratio and no detected deletions / duplicates as the reference sample. The analyzer subsystem 210 normalizes the raw peak signal of each test probe (normal probe) relative to the raw peak signal of the control probe to minimize preferential amplification of smaller fragments. For example, the control probe peak height or signal in the test sample can be compared to the corresponding control probe peak height in the reference sample. The variation in the ratio of the two signals is calculated as the standard deviation of the control probe, and if the value of the standard deviation of the control probe exceeds a predetermined threshold (e.g., threshold 0.125), the sample may be deemed unacceptable. The analyzer subsystem 210 can also check quality control D and Q fragments to ensure that the PCR reaction meets predetermined quality standards and that any samples that do not meet these standards may be deemed unacceptable.

[0043] Next, the normalized probe peak signal of the test probe in the samples that did not fail is compared with the peak signal of the corresponding test probe in the reference sample. The relative probe ratio, or magnification change between the sample probe signal and the reference probe signal, is then calculated by the analyzer subsystem 210, and any change in the sample probe / reference probe ratio outside the normal range (e.g., copy number call threshold) can be identified by the analyzer subsystem 210 as a deletion or duplication. Thus, the relative probe ratio or magnification change of a sample without deletions or duplications relative to the reference sample is approximately 1, and any decrease or increase in the probe ratio exceeding the copy number call threshold can be interpreted as a deletion or duplication of the target sequence, respectively. The analyzer subsystem 210 can generate and export an initial results file containing the relative probe ratio or magnification change for each sample 225.

[0044] In block 280, relative probe ratio data calculated on the analyzer subsystem 210 is analyzed by the HBA genotyping subsystem 215 for abnormal probe ratio patterns based on deletions and / or duplications, and the genotypes to be tested are identified. More specifically, the HBA genotyping subsystem 215 is configured to serve several purposes: a) to check data quality, b) to select samples for creating a synthetic reference using a negative selector tool, and c) to sequentially parse the relative probe ratio data calculated by the analyzer subsystem 210 via a decision tree matrix for genotype calling. To maximize the number of tests that can be performed in a batch, and because approximately 85-90% of samples for carrier screening will be negative for HBA deletions or duplications, the negative selector tool in the HBA genotyping subsystem 215 was developed to provide a technical advantage for the control sample selection application within the analyzer subsystem 210 in identifying 3 to 6 best-quality samples that have the best quality indicators and are negative for any copy number variation (no deletions / duplications). Next, 3 to 6 best-quality samples are communicated and / or selected by a control sample selection application within the analyzer subsystem 210, which then combines the 3 to 6 best-quality samples to create a synthetic reference sample. The relative probe ratio or magnification change for each sample 225 is then recalculated by the analyzer subsystem 210 using this synthetic reference sample. The recalculation takes into account samples from all parts of the plate, maximizing the number of samples that can be run per plate. In addition, the synthetic reference sample normalizes the magnification change rate across the entire plate, reducing the likelihood of samples failing. The analyzer subsystem 210 can generate and export a new results file containing the newly calculated relative probe ratio or magnification change for each sample 225. The HBA genotyping subsystem 215 uses these newly calculated relative probe ratio or magnification change and decision tree matrix to classify and / or identify the genotype of HBA within each sample 225.

[0045] In various embodiments, after checking the newly calculated relative probe ratio or the multiplier change in data quality, the HBA genotyping subsystem 215 uses a copy number call threshold to identify regions of copy number loss or increase by probes involved in multiple abnormal genotypes and classifies each sample into normal, polymorphic, or copy number variant (CNV) categories. CNV samples can then be classified as either large targeted deletion, duplication, or other. Samples in the large targeted deletion group are examined for zygosity and further classified as SEA, FIL / THAI, MED, or α-20.5. Heterozygous samples are classified as α 3.7 and α 4.2 Further checks will be made regarding the absence of α. Items in the "other" category are also α 3.7 and α 4.2 The HBA genotyping subsystem 215 can check for deletions, and if either is detected, it can check for zygosity. At this point, all samples should be classified as either the targeted genotype or "other". The HBA genotyping subsystem 215 then compares the probe combinations to a table with each possible scenario for identifying compound heterozygotes for the targeted deletions and duplications. All samples may also be analyzed by the HBA genotyping subsystem 215 for HS-40 deletions and Hb Constant Spring point mutations, with any positive results being linked to the previously determined genotype. Samples still classified as "other" are flagged for review by a healthcare professional such as a clinical director, thereby ensuring that the HBA genotyping subsystem 215 does not miss any clinically important results, whether targeted or not.

[0046] The HBA genotype for each sample and any risk results for each sample are output by the analyzer system 205 as the final result 285. In some cases, all thresholds and QC parameters, as well as the decision tree matrix, used by the analyzer subsystem 205 and the HBA genotyping subsystem 215 can be maintained in one or more separate configuration files and used across any number of HBA PCR assays.

[0047] III. Genotyping Techniques for HBA Figure 4 shows process 400 for HBA genotyping using an HBA assay platform and genotyping technique (e.g., HBA assay platform 100 described with respect to Figure 1). Process 400 begins in block 405, and raw data are obtained from HBA assays performed on multiple samples. In some cases, the HBA assay is performed using multiple probes (e.g., ligated probes) capable of detecting copy number decreases or increases (e.g., deletions, duplications, and Hb Constant Spring point mutations) in the α-globin gene cluster region of each of the multiple samples. The multiple probes may include one or more control probes and one or more test probes. In some cases, the raw data includes HBA copy number data of the multiple probes separated by capillary electrophoresis for each of the multiple samples. In block 410, a reference sample is selected from the multiple samples. The reference sample may be selected based on the raw data of the multiple probes to obtain a reference sample that has the least variation among the multiple probes and does not have copy number mutations (e.g., no deletions and / or duplications).

[0048] In some cases, the quality of the raw data is checked before selecting a reference probe. This raw data quality check may include verifying the quality of the raw data using one or more of the parameters listed in Table 1. In some cases, one or more of the following quality checks are performed, namely: (i) the total number of probes is equal to a predetermined total number of probes (e.g., 45); (ii) the number of test (normal) probes is equal to a predetermined number of test probes (e.g., 33); (iii) the number of control probes is equal to a predetermined number of control probes (e.g., 11); (iv) the peak signal is above a predetermined peak height threshold (e.g., above 200 RFU after normalization); (v) the Q fragment (a single oligonucleotide (not a ligated probe) that is preferentially amplified when the DNA amount is too small or ligation fails) is below a predetermined threshold, e.g., showing 33% of the signal to a 92nt benchmark fragment; and (vi) the D fragment (a single oligonucleotide (not a ligated probe) that is preferentially amplified when the denaturation reaction is incomplete) is below a predetermined threshold, e.g., showing 50% of the signal to a 92nt benchmark fragment. Based on the results of one or more of these quality checks, the quality of the raw data is evaluated. If the raw data quality is unsatisfactory, the process will stop and, if necessary, may be required to rerun the HBA assay to obtain new raw data. If the raw data quality is satisfactory, the process can continue. [Table 1]

[0049] In block 415, a first set of probe ratios is calculated for each sample of a group of samples (in some examples, the first set of probe ratios is not calculated for a reference sample). In some cases, calculating the first set of probe ratios includes: (i) comparing the control probe peak height or signal in each sample with the corresponding control probe peak height in a selected reference sample; (ii) calculating the variation in the signal between the control probe peak height or signal in each sample and the control probe in the reference sample as the standard deviation of the control probe; (iii) determining that a sample of a group of samples is unacceptable if the standard deviation of the control probe is greater than or equal to a predetermined threshold (e.g., greater than 0.125); (iv) determining that a sample of a group of samples is not unacceptable if the standard deviation of the control probe is less than a predetermined threshold (e.g., less than 0.125); and (v) for each unacceptable sample, comparing the test probe peak height or signal in the sample with the corresponding test probe peak height in a selected reference sample, and calculating the probe ratio between the test probe peak height or signal in the sample and the corresponding test probe peak height in the selected reference sample.

[0050] In block 420, an initial results file is generated and output containing a first set of probe ratios calculated for each sample. This first set of probe ratios includes the relative probe ratio or magnification changes for each sample calculated in step 415 that did not fail (and, if necessary, are not reference samples). In block 425, the initial results file is accessed, and the first set of probe ratios for the samples is parsed to identify a predetermined number (e.g., 3 to 6) of reference samples to be combined as a synthetic reference sample for multiple samples. In certain cases, reference samples are identified based on quality indicators and copy number variations. For example, an identified reference sample should be negative for any copy number variations (e.g., no probes outside the normal range based on the copy number call threshold, and therefore no deletions or duplicates), pass all probe number indicators, and have the lowest standard deviation indicator of control probes on the sample plate. A list containing the identified reference samples can be generated, and a synthetic reference sample file containing the list of identified samples is generated and output. In block 430, a synthetic reference sample file is accessed or uploaded to the computing system, and a synthetic reference sample is generated based on the identified reference samples in the list. In some cases, the synthetic reference sample is created as a functional association of peak height or signal for each of the identified samples in the list. For example, the synthetic reference sample could be the mean, median, or mode of the peak height or signal for each of the identified samples in the list.

[0051] In block 435, a second set of probe ratios is calculated for each of the multiple samples. In some cases, calculating the second set of probe ratios includes: (i) comparing the peak height of the control probe in each sample with the peak height or signal of the corresponding control probe in the synthetic reference sample; (ii) calculating the standard deviation of the control probe as the difference in signal between the peak height or signal of the control probe in each sample and the control probe in the synthetic reference sample; (iii) determining that the samples in the multiple samples are unsuccessful if any variation index is above a predetermined threshold (e.g., threshold 0.125 or higher); (iv) determining that the samples in the multiple samples are not unsuccessful if none of the variation indexes are above a predetermined threshold (e.g., threshold 0.125 or lower); and (v) for each unsuccessful sample, comparing the peak height or signal of the test probe in the sample with the peak height of the corresponding test probe in the synthetic reference sample, and calculating the probe ratio between the peak height or signal of the test probe in the sample and the peak height of the corresponding test probe in the synthetic reference sample.

[0052] In block 440, a new results file is generated and output containing new relative probe ratio data for each sample. The new relative probe ratio data includes the relative probe ratio or magnification change for each sample calculated in step 435 if the sample did not fail. In block 445, the new results file is accessed, and the new relative probe ratio data for each sample is iteratively input into a decision tree matrix to (i) determine the abnormal probe ratio pattern for each sample based on deletions and / or duplications, and (ii) identify the genotype to be tested based on the abnormal probe ratio pattern. Determining the abnormal probe ratio pattern and identifying the genotype to be tested may involve the decision tree matrix identifying regions of copy number loss or increase (e.g., deletions and / or duplications) of one or more, based on the new relative probe ratio data for multiple probes and a copy number call threshold for the normal range or the sample probe / reference probe ratio associated with each probe. For example, any change in the sample probe / reference probe ratio that is outside the normal range (e.g., copy number calling threshold) may be identified as a deletion or duplication and used to identify a region of one or more copies lost or increased. Determining patterns of abnormal probe ratios may further involve classifying the sample as normal, having copy number variation (CNV), or polymorphic based on the identified region of one or more copies decreased or increased. For example, if a sample has no probes outside the normal range, it may be classified as normal. If a sample has one or more probes outside the normal range, it may be classified as a CNV. For a sample with one or more probes outside the normal range, if none of the out-of-normal probes are within a subset of probes indicating a deletion (e.g., a subset of deletion probes identified as important for calling a CNV), it may be classified as polymorphic.

[0053] Determining patterns of abnormal probe ratios and identifying genotypes to be tested may further involve subclassifying samples classified as having CNVs as having large targeted deletions, duplications, or “other” based on identified regions of copy number reduction or increase of one or more. For example, if a sample classified as having a CNV has one or more probes indicating a large targeted deletion that is outside the normal range, the sample may be further classified as having a large targeted deletion. If a sample classified as having a CNV has one or more probes indicating a duplication that is outside the normal range, the sample may be further classified as having a duplication. If a sample classified as having a CNV does not have one or more probes indicating a large targeted deletion or duplication that is outside the normal range, the sample may be further classified as “other.”

[0054] Determining abnormal probe ratio patterns and identifying genotypes to be tested further involves determining the deletion status, zygosity, and duplication status of CNV group samples (e.g., homozygous or heterozygous deletions) based on one or more probes indicating zygosity, as well as identifying deletions outside the normal range (e.g., α). 3.7 and α 4.2 Based on one or more probes indicating the following deletions or duplicates, i.e., α 3.7 and α 4.2 This may include further classifying the sample for one of the following: A large deletion is defined as a deletion encompassing both the HBA1 and HBA2 genes. Samples in the large targeted deletion group may be determined for zygosity (e.g., homozygous or heterozygous large deletions) based on one or more probes indicating zygosity, and include the following deletions: SEA, FIL / THAI, MED, or α 20.5 or deletions outside the normal range: SEA, FIL / THAI, MED, α 20.5 , α 3.7A / α 4.2C An uncertain phasing alpha based on one or more probes showing 3.7A / α 4.2COne of the deletions can be further classified. Samples classified as having large heterozygous deletions are those with deletion α that is outside the normal range. 3.7 and α 4.2 Based on a probe of 1 or more that indicates a smaller α 3.7 and α 4.2 Deletions can be further classified. At this point, the sample should be classified as either the targeted genotype or "other." Table 2 shows examples of targeted genotypes, the results of this process, what these results mean, and possible clinical interpretations. [Table 2-1] [Table 2-2]

[0055] Determining abnormal probe ratio patterns and identifying genotypes to be tested may further involve comparing the new relative probe ratio data with a table containing all possible scenarios for identifying untargeted genotypes, such as compound heterozygotes for targeted deletions and duplications. Samples still classified as “other” after comparison with the table may be flagged for review by healthcare providers, such as clinical directors, thereby ensuring that genotyping techniques do not miss clinically important outcomes, whether targeted or not. Furthermore, all samples (classified as normal, CNV, and polymorphic) may also be analyzed for HS-40 deletions and Hb Constant Spring point mutations based on one or more probes indicating HS-40 deletions and Hb Constant Spring point mutations outside the normal range, and any positive results can be linked to previously determined targeted or untargeted genotypes.

[0056] If necessary, in block 450, the risk score of the subject associated with the sample can be determined using the genotype of each sample determined in block 445. The risk score is calculated as follows: (i) The subject is α 3.7 , α 4.2 ,SEA,MED,THAI,FIL,α 20.5 (ii) α 3.7 , α 4.2 ,SEA,MED,THAI,FIL,α 20.5 and the risk of couples identified as carriers of HS-40 deletion and Hb Constant Spring point mutation, as well as / or (iii)α 3.7 , α 4.2 ,SEA,MED,THAI,FIL,α 20.5 and the risk of fetuses inheriting HS-40 deletion and Hb Constant Spring point mutations can be identified. In block 455, the genotype of each sample determined in block 445 and any risk score determined in block 450 can be output. Outputting the genotype of each sample and any risk score may include providing the output to the end user and / or recording the output in a storage device (e.g., displaying the output on the user interface and / or storing the output in a results file in a database). In block 460, the genotype of the sample determined in block 445 is α3.7 , α 4.2 ,SEA,MED,THAI,FIL,α 20.5If the sample exhibits one or more of the following: and HS-40 deletions, and an Hb Constant Spring point mutation is assigned to the sample, a confirmatory test may be performed on the sample. The confirmatory test can be performed by multiplex assay and gel electrophoresis or Sanger sequencing. If the sample's genotype has not been determined in block 445, a manual review may be performed on the sample. In block 465, if the sample's genotype determined in block 445 indicates that a normal classification has been assigned to the sample, processing of the sample is stopped. In this way, non-linear classification of the decision tree matrix can be used to gate whether or not a confirmatory test should be performed on a sample, thereby saving the cost of incorrectly performing confirmatory tests and improving the robustness of the entire HBA assay.

[0057] Figure 5 shows a decision tree matrix 500 illustrating a genotyping technique that can be implemented to perform HBA genotyping of one or more samples. In block 502, a new results file is accessed, and raw data containing HBA copy number data for each sample of multiple samples is iteratively input into the decision tree matrix to (i) determine the pattern of abnormal probe ratios for each sample based on deletions and / or duplications, and (ii) identify the genotype to be tested based on the pattern of abnormal probe ratios. The raw data includes new relative probe ratio data (described in steps 435, 440, and 445 of Figure 4) for each sample obtained based on a synthetic reference sample (described in steps 425 and 430 of Figure 4). The new relative probe ratio data includes the relative probe ratio or magnification change of each probe of multiple probes, which is used to analyze the α-globin gene cluster region of each sample of multiple samples. In some cases, new relative probe ratio data can be obtained from HBA assays performed using multiple probes (e.g., ligated probes) capable of detecting deletions, duplications, and Hb Constant Spring point mutations in the α-globin gene cluster region of each sample from multiple samples, as described with respect to Figures 1 and 4. Table 3 shows an exemplary list of multiple probes that may be used to perform HBA assays and genotyping. Multiple probes include one or more control probes (e.g., Ctrl_5q31) and one or more test probes (e.g., HBA_HBA1). [Table 3-1] [Table 3-2]

[0058] In block 504, quality checks may be performed by a decision tree matrix to ensure that the raw data is valid for genotyping analysis. Quality checks of the raw data may include a decision tree matrix that checks the quality of the raw data using one or more parameters listed in Table 1. In some cases, the following quality checks may be performed: (i) the total number of probes is equal to a predetermined total number of probes (e.g., 45), (ii) the number of test (normal) probes is equal to a predetermined number of test probes (e.g., 33), (iii) the number of control probes is equal to a predetermined number of control probes (e.g., 11), (iv) the peak signal is above a predetermined peak height threshold (e.g., above 200 RFU after normalization), and (v) the Q fragment (a single oligonucleotide (not a ligated probe) that is preferentially amplified when the DNA amount is too small or ligation fails) is (vi) The D fragment (a single oligonucleotide (not a ligated probe) that preferentially amplifies when the denaturation reaction is incomplete) is below a predetermined threshold, e.g., showing 33% of the signal to the 92nt benchmark fragment, and (vii) any deviation of the standard deviation of the control probe is greater than a predetermined threshold (e.g., threshold 0.125). One or more of these conditions is met, and the quality of the raw data is evaluated based on the result of one or more of these quality checks. If the quality of the raw data is unacceptable, the process stops at block 506, and a request is issued to run the HBA assay again to obtain new raw data, if necessary. If the quality of the raw data is unacceptable, the process proceeds to block 508.

[0059] In block 508, the classification of a sample as normal or having CNV is determined based on the sample probe / reference probe ratio, which shows an abnormal probe ratio pattern associated with CNV. The classification determination may include identifying regions of copy number loss or increase (e.g., deletion, duplication, or point mutation) associated with CNV, based on new relative probe ratio data of the sample probe / reference probe ratio associated with probes of 1 or more and the normal range (copy number call threshold), using a decision tree matrix. In a particular case, the sample probe / reference probe ratio and copy number call threshold used for the analysis include (i) relative probe ratio data for all probes listed in Table 3, (ii) a copy number call threshold of 0.75 and 1.3 or less for predicting the sample as normal, and (iii) a copy number call threshold of less than 0.75 or 1.3 or more for predicting the sample having CNV. If the analysis predicts the sample as normal, the sample is classified as normal. If the analysis predicts the sample has CNV, the sample is classified as having CNV. If the sample is classified as normal, the process proceeds to block 510. If the sample is classified as having CNV, the process proceeds to block 512.

[0060] In block 510, for any sample with a classification of "normal" or "polymorphic," check 13<0.85, 14<0.85, and 17<0.85. If true, an abnormal probe is detected, and the sample is reclassified as H abnormal (where H=3). This is essentially a check of the repeat probes 13, 14, and 17 to determine if the repeat probes 13, 14, and 17 are lower than expected. This may indicate a deletion that is not detected by probes 11, 21, or 22 due to substandard performance. If any of the probes have a probe ratio greater than 0.85, the sample is classified as normal. If the sample is classified as normal or classified as H=3 as a genotype, the process proceeds to block 540.

[0061] In block 512, the classification of samples with large deletions is determined based on the sample probe / reference probe ratio, which shows an abnormal probe ratio pattern associated with the large deletion. Large deletions encompass both the HBA1 and HBA2 genes, while small deletions contain only HBA1 or HBA2. The classification determination may involve identifying regions of copy number loss or increase (e.g., deletion, duplication, or point mutation) associated with the large deletion, based on new relative probe ratio data of sample probe / reference probe ratios associated with probes of 1 or more and the normal range (copy number call threshold), using a decision tree matrix. In a particular case, the sample probe / reference probe ratio and copy number call threshold used for the analysis include (i) relative probe ratio data for a first set of probes, including probes 8, 10, 11, 13, 14, and 17 listed in Table 3; (ii) a copy number call threshold less than 0.75 for probe 10 to predict that the sample has a large deletion; and (iii) a copy number call threshold less than 0.75 for probes 8 and 11, and less than 0.63 for probes 13, 14, and 17 to predict that the sample has a large deletion. If the analysis predicts that the sample has a large deletion, the sample is classified as having a large deletion. If the analysis does not predict that the sample has a large deletion, the sample is classified as having a CNV without a large deletion. If the sample is classified as having a large deletion, the process proceeds to block 528. If the sample is classified as having a CNV without a large deletion, the process proceeds to block 516.

[0062] In block 516, the classification of polymorphic samples is determined based on the sample probe / reference probe ratio, which shows an abnormal probe ratio pattern associated with polymorphism. The classification determination may include identifying regions of polymorphic copy number loss or increase (e.g., deletion, duplication, or point mutation) of one or more, based on new relative probe ratio data of the sample probe / reference probe ratio associated with probes of one or more and the normal range (copy number call threshold), using a decision tree matrix. In a particular case, the sample probe / reference probe ratio and copy number call threshold used for the analysis include (i) relative probe ratio data of a second probe set including probes 4, 8, 11, 21, and 22 listed in Table 3, and (ii) the copy number call threshold for predicting that a sample is polymorphic is 0.75 or greater and 1.3 or less for probes 4, 8, 11, 21, and 22. If the analysis predicts that a sample is polymorphic, the sample is classified as polymorphic. If the analysis does not predict that a sample is polymorphic, the sample is classified as having a non-polymorphic CNV. If the sample is classified as polymorphic, the process proceeds to block 540. If the sample is classified as having a non-polymorphic CNV, the process proceeds to block 520.

[0063] In block 520, α 3.7 The classification of samples with deletions and conjugations is α 3.7 The classification is determined based on the sample probe / reference probe ratio, which shows abnormal probe ratio patterns associated with deletions and fusion. The classification is determined by a decision tree matrix based on new relative probe ratio data and the normal range (copy number call threshold) of the sample probe / reference probe ratio associated with probes of 1 or more, α 3.7 This may include identifying one or more regions of copy number loss or increase related to deletions and conjugation (e.g., deletions, duplications, or point mutations). In certain cases, the sample probe / reference probe ratio and copy number call threshold used for the analysis may include (i) α 3.7(ii) For homozygosity, relative probe ratio data for a third probe set including probes 21, 22, and 8 listed in Table 3, and (ii) copy number call threshold is when the sample is α 3.7 To predict the presence of homozygous deletion, check whether 21 < 0.1, 22 < 0.1, and 8 > 0.75, and (iii) α 3.7 For heterozygosity, relative probe ratio data for a fourth probe set including probes 21, 22, and 8 listed in Table 3 are included, and (iv) the copy number call threshold is when the sample is α 3.7 To predict the presence of heterozygous deletion, check whether 21 < 0.75, 22 < 0.75, or 8 > 0.75. Based on the analysis, the sample is α 3.7 If homozygous deletion is predicted, the sample will be α 3.7 It is classified as having a homozygous deletion. Analysis revealed that the sample is α 3.7 If a heterozygous deletion is predicted, the sample will be α 3.7 It is classified as having a heterozygous deletion.

[0064] Furthermore, in block 520, α 3.7 In conjunction with, or before, or after, the determination of the classification of samples with deletions and conjugations, α 4.2 The classification of samples with deletions and conjugations is α 4.2 The classification is determined based on the sample probe / reference probe ratio, which shows abnormal probe ratio patterns associated with deletions and fusion. The classification is determined by a decision tree matrix based on new relative probe ratio data and the normal range (copy number call threshold) of the sample probe / reference probe ratio associated with probes of 1 or more, α 3.7 This may include identifying one or more regions of copy number loss or increase related to deletions and conjugation (e.g., deletions, duplications, or point mutations). In certain cases, the sample probe / reference probe ratio and copy number call threshold used for the analysis may include (i) α 4.2(ii) The relative probe ratio data for a fourth probe set, including probes 11, 21, and 22 listed in Table 3, for heterozygosity and homozygosity, and (ii) the copy number call threshold is when the sample is α 4.2 (iii) The copy number call threshold is checked to see if 11 < 0.1, 21 > 0.75, and 22 > 0.75 in order to predict that the sample has an α4.2 heterozygous deletion. 4.2 If homozygous deletion is predicted, the sample will be α 4.2 It is classified as having a homozygous deletion. Analysis revealed that the sample is α 4.2 If a heterozygous deletion is predicted, the sample will be α 4.2 It is classified as having a heterozygous deletion. Analysis revealed that the sample is α 4.2 Although it could not be predicted that it would have a deletion, α 3.7 The results of the deletion analysis showed that the sample was α 3.7 If it is concluded that the sample has a heterozygous or homozygous deletion, the sample is α 3.7 It is classified as having heterozygous or homozygous deletions. Analysis revealed that the sample is α 4.2 Deletion or α 3.7 If a deletion cannot be predicted, the sample is α 4.2 Heterozygous or homozygous deletion, or α 3.7 It is classified as having CNVs without heterozygous or homozygous deletions. 3.7 Heterozygous or homozygous deletion, or α 4.2 If the sample is classified as having a heterozygous or homozygous deletion, the process proceeds to block 522. 3.7 Heterozygous or homozygous deletion, or α 4.2 If classified as having a CNV without heterozygous or homozygous deletions, the process proceeds to block 524.

[0065] In block 522, α 4.2Samples having heterozygous or homozygous deletions, and / or α 3.7 Classification of samples having duplications is determined based on the sample probe / reference probe ratio showing an abnormal probe ratio pattern related to the duplication. The determination of the classification is based on the new relative probe ratio data of the sample probe / reference probe ratio related to one or more probes and the normal range (copy number call threshold) by a decision tree matrix, α 3.7 and may include identifying one or more regions of loss or increase in copy number (e.g., deletions, duplications or point mutations) related to the duplication of α 3.7 . In certain cases, the sample probe / reference probe ratio and the copy number call threshold used in the analysis include (i) α 4.2 Deletions in the presence of heterozygosity or homozygosity α 3.7 Relative probe ratio data of a fifth probe set including probes 8, 11, 21 and 22 listed in Table 3 for duplications, (ii) the copy number call threshold checks whether 8 < 1.3, > 0.75, whether 11 < 0.75, whether 21 > 1.3, whether 22 > 1.3 to predict that the sample has a duplication. As a result of the analysis, α 3.7 If a sample classified as having heterozygosity or homozygosity deletion is predicted to also have a duplication, the sample is α 4.2 classified as having heterozygosity or homozygosity deletion and α 3.7 a duplication. As a result of the analysis, α 4.2 If a sample classified as having heterozygosity or homozygosity deletion is not predicted to have a duplication, the sample remains α 3.7 classified as having heterozygosity or homozygosity deletion. If the sample is α 4.2 classified as having heterozygosity or homozygosity deletion and α 3.7 a duplication, the process continues to block 540. If the sample is α 4.2 having heterozygosity or homozygosity deletion or α 4.2 heterozygosity or homozygosity deletion and α 3.7 a duplication, the process continues to block 540. If the sample is α 3.7 having heterozygous or homozygous deletion or α 4.2If classified as having a heterozygous or homozygous deletion, the process proceeds to block 540.

[0066] In block 524, α 3.7 Deletion and α 4.2 The classification of samples having composite heterozygotes including deletions is α 3.7 Deletion and α 4.2 The classification is determined based on the sample probe / reference probe ratio, which shows an abnormal probe ratio pattern associated with both deletions. The classification decision is made by a decision tree matrix, based on new relative probe ratio data of the sample probe / reference probe ratio associated with probes of 1 or more, and the normal range (copy number call threshold), α 3.7 This may include identifying one or more regions of copy number loss or increase related to deletions and conjugation (e.g., deletions, duplications, or point mutations). In certain cases, the sample probe / reference probe ratio and copy number call threshold used for the analysis may include (i) α 3.7 Deletion and α 4.2 (ii) The copy number call threshold is determined when the sample is α 3.7 Deletion and α 4.2 To predict the presence of a compound heterozygote containing a deletion, check whether 8 < 1.3, > 0.75, 29 < 1.3, > 0.75, 11 < 0.75, 21 < 0.75, 22 < 0.75, or either 16 < 0.1 or 19 < 0.1. Based on the analysis, if the sample is α 3.7 Deletion and α 4.2 If the sample is predicted to have a composite heterozygote containing a deletion, the sample will be α 3.7 Deletion and α 4.2 It is classified as having a complex heterozygote containing a deletion. The sample is α 3.7 Deletion and α 4.2 If classified as having a composite heterozygote containing a deletion, the process proceeds to block 540.

[0067] Furthermore, in block 524, α 3.7 Deletion and α 4.2 In conjunction with, or prior to, or after, the classification of samples having composite heterozygotes containing deletions, the classification of samples having duplicates is determined based on the sample probe / reference probe ratio, which shows an unusual probe ratio pattern associated with the duplicates. The classification determination may involve identifying regions of copy number loss or increase (e.g., deletion, duplicate, or point mutation) associated with duplicates (e.g., deletion, duplicate, or point mutation) based on new relative probe ratio data of the sample probe / reference probe ratio associated with probes of 1 or more and the normal range (copy number call threshold) using a decision tree matrix. In a particular case, the sample probe / reference probe ratio and copy number call threshold used for the analysis include (i) relative probe ratio data of a seventh probe set, including probes 8, 21, and 22 listed in Table 3, for duplicates, and (ii) the copy number call threshold checks whether 8 > 0.75, 21 > 1.3, and 22 > 1.3 to predict that the sample has duplicates. If the analysis predicts that the sample has duplicates, the sample is classified as having duplicates. If the sample is classified as having duplicates, the process proceeds to block 540. If the results of the analysis indicate that the sample is α 3.7 Deletion and α 4.2 If it is not predictable that the sample will have a composite heterozygote including deletions and / or duplications, the sample is α 4.2 Heterozygous or homozygous deletion, α 3.7 It is classified as having heterozygous or homozygous deletions and / or non-overlapping CNVs. The sample is α 4.2 Deletion of heterozygous or homozygous α 3.7 If it is classified as having heterozygous or homozygous deletions and non-overlapping CNVs, the process proceeds to block 526.

[0068] In block 526, the classification of samples that are H-anomalous CNVs is determined based on the sample probe / reference probe ratio, which shows an abnormal probe ratio pattern associated with H-anomalous CNVs. The classification determination may include identifying regions of copy number loss or increase (e.g., deletion, duplication, or point mutation) associated with H-anomalous CNVs based on new relative probe ratio data of sample probe / reference probe ratios associated with probes of 1 or more and the normal range (copy number call threshold) using a decision tree matrix. In a particular case, the sample probe / reference probe ratio and copy number call threshold used in the analysis include (i) relative probe ratio data for an eighth set of probes, including probes 1, 4-6, 8, 11, 21, 22, 29-37 listed in Table 3, for H anomalous CNVs, and (ii) the copy number call threshold checks whether 8 < 0.75 or > 1.3 for probes 1, 4-6, 8, 11, 21, 22, 29-37 to predict that the sample has H anomalous CNVs (determining how many significant deletion probes are anomalous and providing a count H for those anomalous probes). If the analysis predicts that the sample has H anomalous CNVs, the sample is classified as H anomalous CNV (where H represents how many significant deletion probes are anomalous). If the sample is classified as having H anomalous CNVs, the process proceeds to block 540.

[0069] In block 528, the classification of samples with large homozygous or large heterozygous deletions is determined based on the sample probe / reference probe ratio, which shows an unusual probe ratio pattern associated with large deletion zygotes. The classification determination may include identifying regions of one or more copy number loss or increase (e.g., deletion, duplication, or point mutation) associated with large deletion zygotes, based on new relative probe ratio data of the sample probe / reference probe ratio associated with one or more probes and the normal range (copy number call threshold) using a decision tree matrix. In certain cases, the sample probe / reference probe ratio and copy number call threshold used for analysis include: (i) relative probe ratio data for a ninth probe set, including probes 8, 10, 13, 14, and 17 listed in Table 3, for large homozygous deletions; (ii) a copy number call threshold that checks whether probes 8, 10, or 13, 14, and 17 are <0.1 to predict that the sample has a large homozygous deletion; (iii) relative probe ratio data for a tenth probe set, including probes 8, 11, 13, 14, and 17 listed in Table 3, for large heterozygous deletions; and (iv) a copy number call threshold that checks whether probes 8 and 11 are <0.75 or probes 13, 14, and 17 are <0.63 to predict that the sample has a large heterozygous deletion. If the analysis predicts that the sample has a large homozygous deletion, the sample is classified as having a large homozygous deletion. If the analysis predicts that the sample has a large heterozygous deletion, the sample is classified as having a large heterozygous deletion. If the sample is classified as having a large homozygous deletion, the process proceeds to block 530. If the sample is classified as having a large heterozygous deletion, the process proceeds to block 532.

[0070] In block 530, SEA, MED1, MED2, THAI, FIL and α 20.5The classification of samples with specific large homozygous deletions is determined based on the sample probe / reference probe ratio, which shows an abnormal probe ratio pattern associated with specification deletions. The classification determination may involve identifying regions of one or more copy number loss or increase (e.g., deletion, duplication, or point mutation) associated with specification deletions, based on new relative probe ratio data of the sample probe / reference probe ratio associated with one or more probes and the normal range (copy number call threshold) using a decision tree matrix.In certain cases, the sample probe / reference probe ratio and copy number call threshold used for analysis include: (i) relative probe ratio data for an 11th probe set including probes 8, 31, 32, 5, 6, 33, and 34 listed in Table 3 for large SEA homozygous deletions; (ii) the copy number call threshold checks whether 8 < 0.1, 31 < 0.1, 32 < 0.1, 5 > 0.75, 6 > 0.75, 33 > 0.75, and 34 > 0.75 to predict that the sample has a large SEA homozygous deletion; (iii) relative probe ratio data for a 12th probe set including probes 8, 30, 31, 5, 6, 32, and 33 listed in Table 3 for large MED1 homozygous deletions; and (iv) the copy number call threshold checks whether 8 < 0.1 to predict that the sample has a large MED1 homozygous deletion. (v) Relative probe ratio data for the 13th probe set, including probes 5, 6, 30, 4, 31 and 32 listed in Table 3, for MED2 homozygosity deletion, and (vi) copy number call threshold for samples with large MED2 homozygosity To predict the presence of a deletion, check whether 5<0.1, 6<0.1, 30<0.1, 4>0.75, 31>0.75, 32>0.75, (vii) relative probe ratio data for a 14th probe set including probes 8, 6, 29 and 30 listed in Table 3 for large α20.5 homozygous deletions, and (viii) copy number call threshold for large α samples. 20.5(ix) Relative probe ratio data for a 15th probe set including probes 6, 8, 31, 32, 5, 33 and 34 listed in Table 3 for large FIL / THAI homozygous deletions, (x) Copy number call thresholds are checked to see if 6 < 0.1, 8 < 0.1, 31 < 0.1, 32 < 0.1, 5 > 0.75, 33 > 0.75, 34 > 0.75 in order to predict that the sample has a large FIL / THAI homozygous deletion, (xi) α 3.7A / α 4.2C The relative probe ratio data for the 16th set of probes, including probes 9, 22, 6, 8, 29, and 30 listed in Table 3 for homozygous deletions, is included, and (xii) the copy number call threshold is when the sample is α 3.7A / α 4.2C To predict the presence of homozygous deletion, check whether 9 < 0.1, 22 < 0.1, 6 > 0.75, 8 > 0.75, 29 > 0.75, 30 > 0.75, and (xiii)α 4.2 The relative probe ratio data for the 17th probe set, including probes 11, 21, and 22 listed in Table 3, for homozygous deletions, and the (xiv) copy number call threshold is used when the sample is α 4.2 To predict the presence of homozygous deletion, check whether 11 < 0.1, 21 > 0.75, and 22 > 0.75, and then (xv)α 4.2 The relative probe ratio data for heterozygous deletions includes the 18th probe set, which includes probes 8, 21, 22, and 11 listed in Table 3, and the (xvi) copy number call threshold is used for samples with a large α 4.2 To predict the presence of a heterozygous deletion, check whether 8 < 0.75, > 0.25, 21 < 0.75, > 0.25, 22 < 0.75, > 0.25, and 11 < 0.1.

[0071] If the analysis predicts that the sample has a large SEA homozygous deletion, the sample is classified as having a large SEA homozygous deletion. If the analysis predicts that the sample has a large MED1 homozygous deletion, the sample is classified as having a large MED1 homozygous deletion. If the analysis predicts that the sample has a large MED2 homozygous deletion, the sample is classified as having a large MED2 homozygous deletion. If the analysis predicts that the sample has a large α 20.5 If homozygous deletion is predicted, the sample will have a large α 20.5 It is classified as having a homozygous deletion. If the analysis predicts that the sample has a large FIL / THAI homozygous deletion, the sample is classified as having a large FIL / THAI homozygous deletion. If the analysis predicts that the sample has a large α 3.7A / α 4.2C If homozygous deletion is predicted, the sample will have a large α 3.7A / α 4.2C It is classified as having a homozygous deletion. Analysis revealed that the sample is α 4.2 If homozygous deletion is predicted, the sample will be α 4.2 It is classified as having a homozygous deletion. Analysis revealed that the sample has a large α 4.2 If a heterozygous deletion is predicted, the sample will have a large α 4.2 It is classified as having a heterozygous deletion. If the sample is classified as having a large homozygous deletion, the process continues to block 530. If the sample has a large SEA, MED1, MED2, α 20.5 , FIL / THAI, or α 3.7A / α 4.2C Deletion, or α 4.2 Homozygous deletion, or large α 4.2 If classified as having a heterozygous deletion, the process proceeds to block 540.

[0072] At this point, the sample is still classified as a nonspecific homozygous deletion (large SEA, MED1, MED2, α 20.5 , FIL / THAI, or α 3.7A / α4.2C Deletion, or α 4.2 Homozygous deletion, or large α 4.2 If it is not a heterozygous deletion, the process proceeds to block 530, α 3.7 , α 4.2 SEA, MED1, MED2, THAI, FIL and α 20.5The classification of samples with specific large homozygous deletions is determined based on the sample probe / reference probe ratio, which shows other anomalous probe ratio patterns associated with specification deletions, including the above. The classification determination may include identifying regions of one or more copy number loss or increase (e.g., deletion, duplication, or point mutation) associated with specification deletions based on new relative probe ratio data of the sample probe / reference probe ratio associated with one or more probes and the normal range (copy number call threshold) using a decision tree matrix. In certain cases, the sample probe / reference probe ratio and copy number call threshold used for analysis include: (i) relative probe ratio data for a 19th probe set, including probes 8, 13, 14, 17, 32, 6, and 33 listed in Table 3, for large SEA / MED1 homozygous deletions; (ii) the copy number call threshold checks whether 8 < 0.1, 13 < 0.1, 14 < 0.1, 17 < 0.1, 32 < 0.75, > 0.25, 6 > 0.75, 33 > 0.75, and (iii) large S (iv) The copy number call threshold is checked to predict that the sample has a large SEA / (MED2 / DUTCH) homozygous deletion, by checking whether 8<0.1, 13<0.1, 14<0.1, 17<0.1, 30<0.1, 31<0.75, >0.25, 5<0.75, >0.25, 6>0.75, 33>0.75, and (v) a large SEA / α 20.5 The relative probe ratio data for the 21st probe set, including probes 8, 13, 14, 29, 30, 31, 32, 8 and 33 listed in Table 3, for homozygous deletions, and (vi) the copy number call threshold is set for samples with a large SEA / α 20.5To predict the presence of homozygous deletion, check whether 8<0.1, 13<0.1, 14<0.1, 29<0.75, >0.25, 30<0.75, >0.25, 31<0.75, 0.25, 32<0.75, >0.25, 6>0.75, 33>0.75, and (vii) large SEA / (FIL / THA i) Relative probe ratio data for the 22nd probe set, including probes 8, 13, 14, 17, 32, 8, 6, and 33 listed in Table 3 for homozygous deletions, and (viii) copy number call thresholds are whether 8 < 0.1, 13 < 0.1, 14 < 0.1, 17 < 0.1, and 32 < 0.1 in order to predict that the sample has a large SEA / (FIL / THAI) homozygous deletion. (ix) Relative probe ratio data for the 23rd probe set, including probes 8, 13, 14, 17, 30, 31, 5, 6, 4 and 32 listed in Table 3, for large MED1 / (MED2 / DUTCH) homozygous deletions, and (x) copy number call threshold for the sample is large MED1 / (MED2 / DUTCH) H) To predict that homozygous deletion is present, check whether 8<0.1, 13<0.1, 14<0.1, 17<0.1, 30<0.1, 31<0.75, >0.25, 5<0.75, >0.25, 6<0.75, >0.25, 4>0.75, 32>0.75, and (xi) a large MED1 / α 20.5 The data includes relative probe ratio data for the 24th probe set, including probes 8, 13, 14, 17, 31, 6, and 32 listed in Table 3 for homozygous deletions, and (xii) the copy number call threshold is for samples with a large MED1 / α 20.5To predict the presence of homozygous deletions, check whether 8<0.1, 13<0.1, 14<0.1, 17<0.1, 31<0.75, >0.25, 6>0.75, and 32>0.75, and (xiii) relative probe ratio data for the 25th probe set, including probes 8, 13, 14, 17, 31, 32, 6, 5, and 33 listed in Table 3, for large MED1 / (FIL / THAI) homozygous deletions. (xiv) The copy number call threshold is checked to see if 8 < 0.1, 13 < 0.1, 14 < 0.1, 17 < 0.1, 31 < 0.1, 32 < 0.75, > 0.25, 6 < 0.75, > 0.25, 5 > 0.75, 33 > 0.75, and (xiii) a large (MED2 / DUTCH) / α 20.5 The data includes relative probe ratio data for the 26th probe set, including probes 13, 14, 17, 5, 6, 29, 30, 31, and 4 listed in Table 3 for homozygous deletions, and the (xiv) copy number call threshold is (MED2 / DUTCH) / α for larger samples. 20.5To predict the presence of homozygous deletions, check whether 13<0.1, 14<0.1, 17<0.1, 5<0.75, >0.25, 6<0.75, >0.25, 29<0.75, >0.25, 30<0.75, >0.25, 31>0.75, 4>0.75, and for (xv) large (MED2 / DUTCH) / (FIL / THAI) homozygous deletions, probes 8, 13, 14, 17, 6 are listed in Table 3. The 27th probe set includes relative probe ratio data, including 31, 5, and 33, and (xvi) the copy number call threshold is checked to see if 8 < 0.1, 13 < 0.1, 14 < 0.1, 17 < 0.1, 6 < 0.75, > 0.25, 31 < 0.75, > 0.25, 5 > 0.75, 33 > 0.75, and (xvii) large α 20.5 The (FIL / THAI) homozygous deletion includes relative probe ratio data for the 28 probe set, including probes 8, 13, 14, 17, 6, 29, 5 and 33 listed in Table 3, and (xviii) copy number call threshold for samples with large α 20.5 To predict that a gene has a homozygous deletion of / (FIL / THAI), check whether 8<0.1, 13<0.1, 14<0.1, 17<0.1, 6<0.75, >0.25, 29<0.75, >0.25, 5>0.75, and 33>0.75.

[0073] If the analysis predicts that the sample has a large SEA / MED1 homozygous deletion, the sample is classified as having a large SEA / MED1 homozygous deletion. If the analysis predicts that the sample has a large SEA / (MED2 / DUTCH) homozygous deletion, the sample is classified as having a large SEA / (MED2 / DUTCH) homozygous deletion. If the analysis predicts that the sample has a large SEA / (MED2 / DUTCH) homozygous deletion, the sample is classified as having a large SEA / (MED2 / DUTCH) homozygous deletion. If the analysis predicts that the sample has a large SEA / α 20.5 If homozygous deletion is predicted, the sample will have a large SEA / α 20.5 It is classified as having a homozygous deletion. If the analysis predicts that the sample has a large SEA / (FIL / THAI) homozygous deletion, the sample is classified as having a large SEA / (FIL / THAI) homozygous deletion. If the analysis predicts that the sample has a large MED1 / (MED2 / DUTCH) homozygous deletion, the sample is classified as having a large MED1 / (MED2 / DUTCH) homozygous deletion. If the analysis predicts that the sample has a large MED1 / α 20.5 If homozygous deletion is predicted, the sample will have a large MED1 / α 20.5 It is classified as having a homozygous deletion. If the analysis predicts that the sample has a large MED1 / (FIL / THAI) homozygous deletion, the sample is classified as having a large MED1 / (FIL / THAI) homozygous deletion. If the analysis predicts that the sample has a large (MED2 / DUTCH) / α 20.5 If homozygous deletion is predicted, the sample is large (MED2 / DUTCH) / α 20.5 It is classified as having a homozygous deletion. If the analysis predicts that the sample has a large (MED2 / DUTCH) / (FIL / THAI) homozygous deletion, the sample is classified as having a large (MED2 / DUTCH) / (FIL / THAI) homozygous deletion. If the analysis predicts that the sample has a large α 20.5 If a sample is predicted to have a homozygous deletion of / (FIL / THAI), the sample will have a large α 20.5It is classified as having a homozygous deletion (FIL / THAI). At this point, the sample is still classified as a nonspecific homozygous deletion (large SEA, MED1, MED2, α 20.5 , FIL / THAI, or α 3.7A / α 4.2C Deletion, or α 4.2 Homozygous deletion, or large α 4.2 If the sample is not heterozygous (not a deletion), the process continues to block 540. 20.5 , FIL / THAI, or α 3.7A / α 4.2C Deletion, or α 4.2 Homozygous deletion, or large α 4.2 If classified as having a heterozygous deletion, the process proceeds to block 540.

[0074] In block 532, SEA, MED1, MED2, THAI, FIL and α 20.5The classification of samples with specific large heterozygous deletions is determined based on the sample probe / reference probe ratio, which shows an unusual probe ratio pattern associated with specification deletions. The classification determination may involve identifying regions of one or more copy number loss or increase (e.g., deletion, duplication, or point mutation) associated with specification deletions, based on new relative probe ratio data of the sample probe / reference probe ratio associated with one or more probes and the normal range (copy number call threshold) using a decision tree matrix. In certain cases, the sample probe / reference probe ratio and copy number call threshold used for analysis include: (i) relative probe ratio data for a 29th set of probes, including probes 8, 31, 32, 5, 6, 33, and 34 listed in Table 3, for large SEA heterozygosity deletions; (ii) the copy number call threshold checks whether 8 < 0.75, 31 < 0.75, 32 < 0.75, 5 > 0.75, 6 > 0.75, 33 > 0.75, 34 > 0.75, to predict that the sample has a large SEA heterozygosity deletion; (iii) relative probe ratio data for a 30th set of probes, including probes 8, 30, 31, 5, 6, 32, and 33 listed in Table 3, for large MED1 heterozygosity deletions; and (iv) (v) For large MED2 heterozygosity deletions, relative probe ratio data for the 31st set of probes, including probes 5, 6, 30, 4, 31 and 32 listed in Table 3, is included; (vi) For large MED2 heterozygosity deletions, the copy number call threshold is checked to see if 5 < 0.75, 6 < 0.75, 30 < 0.75, 4 > 0.75, 31 > 0.75, 32 > 0.75; (vii) For large α 20.5(viii) The copy number call threshold is large for the sample. 20.5 To predict the presence of heterozygous deletions, check whether 8 < 0.75, 6 > 0.75, 29 > 0.75, 30 > 0.75, (ix) relative probe ratio data for the 33rd probe set, including probes 6, 8, 31, 32, 5, 33 and 34 listed in Table 3, for large FIL / THAI heterozygous deletions, and (x) copy number call threshold for samples with large α 3.7A / α 4.2C To predict the presence of heterozygous deletion, check whether 6 < 0.75, 85 < 0.75, 31 < 0.75, 32 < 0.75, 5 > 0.75, 33 > 0.75, 34 > 0.75, and (xi) a large α 3.7A / α 4.2C The relative probe ratio data for the 34th set of probes, including probes 9, 22, 6, 8, 29, and 30 listed in Table 3 for heterozygous deletions, (xii) the copy number call threshold is checked to see if 9 < 0.75, 22 < 0.75, 6 > 0.75, 8 > 0.75, 29 > 0.75, 30 > 0.75, and (xiii) α 4.2 The relative probe ratio data for the 35th set of probes, including probes 11, 21, and 22 listed in Table 3, for homozygous deletions, and the (xiv) copy number call threshold is used when the sample is α 4.2 To predict the presence of homozygous deletion, check whether 11 < 0.1, 21 > 0.75, and 22 > 0.75, and (xv) large α 3.7 The relative probe ratio data for heterozygous deletions includes the 36th probe set, which includes probes 21, 22, and 11 listed in Table 3, and the (xvi) copy number call threshold is for samples with a large α 3.7To predict the presence of heterozygous deletion, check whether 21 < 0.15, 22 < 0.15, 11 < 0.75, > 0.25, and (xvii)α 3.7 The relative probe ratio data for homozygous deletions includes the 37 probe set, including probes 21, 22, and 11 listed in Table 3, and (xviii) the copy number call threshold is when the sample is α 3.7 To predict the presence of homozygous deletion, check whether 21 < 0.15, 22 < 0.15, 11 < 0.75, > 0.25, and (xix) large α 4.2 The relative probe ratio data for heterozygous deletions includes the 38 sets of probes, including probes 8, 21, 22, and 11 listed in Table 3, and (xviii) copy number call threshold for samples with large α 4.2 To predict the presence of a heterozygous deletion, check whether 8 < 0.75, > 0.25, 21 < 0.75, > 0.25, 22 < 0.75, > 0.25, and 11 < 0.1.

[0075] If the analysis predicts that the sample has a large SEA heterozygosity deletion, the sample is classified as having a large SEA heterozygosity deletion. If the analysis predicts that the sample has a large MED1 heterozygosity deletion, the sample is classified as having a large MED1 heterozygosity deletion. If the analysis predicts that the sample has a large MED2 heterozygosity deletion, the sample is classified as having a large MED2 heterozygosity deletion. If the analysis predicts that the sample has a large α 20.5 If a heterozygous deletion is predicted, the sample will have a large α 20.5 It is classified as having a heterozygous deletion. If the analysis predicts that the sample has a large FIL / THAI heterozygous deletion, the sample is classified as having a large FIL / THAI heterozygous deletion. If the analysis predicts that the sample has a large α 3.7A / α 4.2C If a heterozygous deletion is predicted, the sample will have a large α 3.7A / α 4.2CIt is classified as having a heterozygous deletion. Analysis revealed that the sample is α 4.2 If homozygous deletion is predicted, the sample will be α 4.2 It is classified as having a homozygous deletion. Analysis revealed that the sample has a large α 3.7 If a heterozygous deletion is predicted, the sample will have a large α 3.7 It is classified as having a heterozygous deletion. Analysis revealed that the sample is α 3.7 If homozygous deletion is predicted, the sample will be α 3.7 It is classified as having a homozygous deletion. Analysis revealed that the sample has a large α 4.2 If a heterozygous deletion is predicted, the sample will have a large α 4.2 It is classified as having a heterozygous deletion. If the sample is classified as having a large heterozygous deletion, the process proceeds to block 534. If the sample has a large SEA, MED1, MED2, α 20.5 , FIL / THAI, or α 3.7A / α 4.2C , or α 4.2 Homozygous deletion, or large α 3.7 Heterozygous deletion, or α 3.7 Homozygous deletion, or large α 4.2 If classified as having a heterozygous deletion, the process proceeds to block 536.

[0076] In block 534, there is an unspecified large deletion and α 3.7 The classification of samples with compound heterozygous genotypes including deletions is based on large deletions and α 3.7 The classification is determined based on the sample probe / reference probe ratio, which shows an abnormal probe ratio pattern associated with both deletions. The classification decision is made by a decision tree matrix, based on new relative probe ratio data of the sample probe / reference probe ratio associated with probes of 1 or more, and the normal range (copy number call threshold), α 3.7This may include identifying one or more regions of copy number loss or increase related to deletions and conjugation (e.g., deletions, duplications, or point mutations). In certain cases, the sample probe / reference probe ratio and copy number call threshold used for the analysis may include (i) α 3.7 (ii) The relative probe ratio data for deletions includes the 39th probe set, which includes probes 8, 29, 11, 21, 22, 16 and 19 listed in Table 3, and (ii) the copy number call threshold is determined when the sample has unspecified large deletions and α 3.7 To predict the presence of a compound heterozygote containing a deletion, check whether 8<0.75, 29<0.75, 11<0.75, 21<0.1, 22<0.1, or any of 16<0.1 or 19<0.1. Based on the analysis, if the sample is α 3.7 If the sample is predicted to have a composite heterozygote containing a deletion, the sample is α 3.7 It is classified as a large heterozygous deletion containing a compound heterozygote with the deletion. Analysis revealed that the sample is α 3.7 If a sample is predicted not to contain a compound heterozygote including a deletion, it is classified as a large heterozygous deletion.

[0077] Furthermore, in block 534, there is an unspecified large deletion and α 4.2 The classification of samples with compound heterozygous genotypes including deletions is based on large deletions and α 4.2 The classification is determined based on the sample probe / reference probe ratio, which shows an abnormal probe ratio pattern associated with both deletions. The classification decision is made by a decision tree matrix, based on new relative probe ratio data of the sample probe / reference probe ratio associated with probes of 1 or more, and the normal range (copy number call threshold), α 4.2 This may include identifying one or more regions of copy number loss or increase related to deletions and conjugation (e.g., deletions, duplications, or point mutations). In certain cases, the sample probe / reference probe ratio and copy number call threshold used for the analysis may include (i) α 4.2(ii) The relative probe ratio data for deletions includes the 40th probe set, which includes probes 8, 29, 11, 21, 22, 16 and 19 listed in Table 3, and (ii) the copy number call threshold is used when the sample has unspecified large deletions and α 4.2 To predict the presence of a compound heterozygote containing a deletion, check whether 8<0.75, 29<0.75, 11<0.1, 21<0.75, or 22<0.75. Analysis results indicate that the sample has α 4.2 If the sample is predicted to have a composite heterozygote containing a deletion, the sample will be α 4.2 It is classified as a large heterozygous deletion containing a compound heterozygote with the deletion. Analysis revealed that the sample is α 4.2 If a sample is predicted not to contain a compound heterozygote including a deletion, it is classified as a large heterozygous deletion.

[0078] Furthermore, in block 534, α 3.7 Deletion and α 4.2 In conjunction with, or prior to, or after, the classification of samples having composite heterozygotes with deletions is determined based on the sample probe / reference probe ratio, which shows an unusual probe ratio pattern associated with the duplication. The classification determination may involve identifying regions of copy number loss or increase (e.g., deletion, duplication, or point mutation) associated with the duplication, based on new relative probe ratio data of the sample probe / reference probe ratio associated with probes of 1 or more and the normal range (copy number call threshold) using a decision tree matrix. In a particular case, the sample probe / reference probe ratio and copy number call threshold used for analysis include (i) relative probe ratio data of a 41st probe set, including probes 8, 21, and 22 listed in Table 3, for duplication, and (ii) the copy number call threshold checks whether 8 < 0.75, 21 > 0.75, or 22 > 0.75 to predict that the sample has duplication.

[0079] Analysis revealed that the sample was α 3.7If a sample is predicted to have a large, unspecified heterozygous deletion combined with a deletion, or if the sample is α 3.7 It is classified as a large, unspecified heterozygous deletion combined with a deletion. 4.2 If the sample is classified as a large unspecified heterozygous deletion with a compound heterozygote containing the deletion, the process proceeds to block 540. If the sample is classified as a large unspecified heterozygous deletion combined with a duplication, the sample is classified as having a large unspecified deletion and duplication, and the process proceeds to block 540. If the analysis predicts that the sample does not have a duplication with a large heterozygous deletion, the sample is classified as a large heterozygous deletion. If the sample is classified as a large heterozygous deletion, the process proceeds to block 540.

[0080] In block 536, a large deletion and α were specifically targeted. 3.7 The classification of samples containing compound heterozygotes with deletions is based on the presence of specifically targeted large deletions, α 3.7 The classification is determined based on the sample probe / reference probe ratio, which shows an abnormal probe ratio pattern associated with both deletions. The classification decision is made by a decision tree matrix, based on new relative probe ratio data of the sample probe / reference probe ratio associated with probes of 1 or more, and the normal range (copy number call threshold), α 3.7 This may include identifying one or more regions of copy number loss or increase related to deletions and conjugation (e.g., deletions, duplications, or point mutations). In certain cases, the sample probe / reference probe ratio and copy number call threshold used for the analysis may include (i) α 3.7 (ii) The copy number call threshold is determined when the sample is α 3.7To predict the presence of a compound heterozygote containing a deletion, check whether 8<0.75, 29<0.75, 11<0.75, 21<0.1, 22<0.1, or either 16<0.1 or 19<0.1. Based on the analysis, if the sample is α 3.7 If a sample is predicted to have a composite heterozygote containing a deletion, the sample is α 3.7 Certain large heterozygous deletions having compound heterozygotes containing the deletion (e.g., large SEA, MED1, MED2, α 20.5 , FIL / THAI, or α 3.7A / α 4.2C It is classified as α. The analysis results show that the sample is α 3.7 If the sample is not expected to contain deletions, it will contain certain large heterozygous deletions (e.g., large SEA, MED1, MED2, α). 20.5 , FIL / THAI or α 3.7A / α 4.2C It is classified as such.

[0081] Furthermore, in block 536, there is a specifically targeted large deletion and α 4.2 The classification of samples containing compound heterozygotes with deletions is based on the specific targeting of large deletions and α 4.2 The classification is determined based on the sample probe / reference probe ratio, which shows an abnormal probe ratio pattern associated with both deletions. The classification decision is made by a decision tree matrix, based on new relative probe ratio data of the sample probe / reference probe ratio associated with probes of 1 or more, and the normal range (copy number call threshold), α 4.2 This may include identifying one or more regions of copy number loss or increase related to deletions and conjugation (e.g., deletions, duplications, or point mutations). In certain cases, the sample probe / reference probe ratio and copy number call threshold used for the analysis may include (i) α 3.7 (ii) The copy number call threshold is determined when the sample is α 4.2To predict the presence of a compound heterozygote containing a deletion, check whether 8<0.75, 29<0.75, 11<0.1, 21<0.75, or 22<0.75. Analysis results indicate that the sample has α 4.2 If a sample is predicted to have a composite heterozygote containing a deletion, the sample is α 4.2 Certain large heterozygous deletions having compound heterozygotes containing the deletion (e.g., large SEA, MED1, MED2, α 20.5 , FIL / THAI, or α 3.7A / α 4.2C It is classified as α. The analysis results show that the sample is α 3.7 If the sample is not expected to contain deletions, it will contain certain large heterozygous deletions (e.g., large SEA, MED1, MED2, α). 20.5 , FIL / THAI or α 3.7A / α 4.2C It is classified as such.

[0082] Furthermore, in block 536, there is a specific large deletion and α 3.7 Deletion or α 4.2In conjunction with, or prior to, or after, the classification of samples with specific large deletions and overlaps is determined based on the sample probe / reference probe ratio, which shows an unusual probe ratio pattern associated with the overlap, in conjunction with the classification determination of samples with compound heterozygous deletions including deletions. The classification determination may involve identifying regions of copy number loss or increase (e.g., deletion, overlap, or point mutation) associated with overlaps, based on new relative probe ratio data of the sample probe / reference probe ratio associated with probes of 1 or more and the normal range (copy number call threshold) using a decision tree matrix. In a particular case, the sample probe / reference probe ratio and copy number call threshold used for analysis include (i) relative probe ratio data of a 44th probe set, including probes 8, 21, and 22 listed in Table 3, for overlaps, and (ii) the copy number call threshold checks whether 8 > 0.1, 21 > 0.75, or 22 > 0.75 to predict that the sample has specific large deletions and overlaps.

[0083] Analysis revealed that the sample had certain large deletions and α 3.7 If the sample is predicted to have a composite heterozygote containing a deletion, the sample is α 3.7 It is classified as a specific large heterozygous deletion having a compound heterozygote containing a deletion. If the analysis predicts that the sample has a specific large deletion and a compound heterozygote containing a duplicate, the sample is classified as a specific large heterozygous deletion having a compound heterozygote containing a duplicate. If the analysis predicts that the sample has a specific large deletion and α 4.2 If a sample is predicted to have a complex heterozygote containing overlaps, it is classified as a specific large heterozygous deletion with a complex heterozygote containing overlaps. 3.7 Deletion, α 4.2 If it is classified as a specific large heterozygous deletion with a compound heterozygote containing deletions or duplications, the process proceeds to block 540. Analysis reveals that samples with a specific large heterozygous deletion are classified as α 3.7 Deletion, α 4.2If no deletions or overlaps are predicted, the sample is classified as a specific large heterozygous deletion. If the sample is classified as a specific large heterozygous deletion, the process proceeds to block 540.

[0084] In block 540, the classification of samples having HS40 homozygous or heterozygous deletions is determined based on the sample probe / reference probe ratio, which shows an abnormal probe ratio pattern associated with HS40 deletion zygosity. The classification determination may include identifying regions of one or more copy number loss or increase (e.g., deletion, duplication, or point mutation) associated with HS40 deletion zygosity, based on new relative probe ratio data of the sample probe / reference probe ratio associated with one or more probes and the normal range (copy number call threshold) using a decision tree matrix. In certain cases, the sample probe / reference probe ratio and copy number call threshold used for analysis include: (i) relative probe ratio data for a 45th probe set including probes 1, 4, 2, and 3 listed in Table 3 for HS40 heterozygosity deletions; (ii) the copy number call threshold checks whether 1 > 0.75, < 1.3, 4 > 0.75, < 1.3, 2 < 0.1, and 3 < 0.1 to predict that the sample has an HS40 heterozygosity deletion; (iii) relative probe ratio data for a 45th probe set including probes 1, 4, 2, and 3 listed in Table 3 for HS40 heterozygosity deletions; and (iv) the copy number call threshold checks whether 1 > 0.75, < 1.3, 4 > 0.75, < 1.3, 2 < 0.75, and 3 < 0.75 to predict that the sample has a large heterozygosity deletion. Furthermore, if a sample is classified as having a CNV where H is abnormal, the sample probe / reference probe ratio and copy number call threshold used for analysis include (i) relative probe ratio data for a 42nd probe set, including probes 2 and 3 listed in Table 3, for further abnormal probes, and (ii) the copy number call threshold checks whether 2 > 0.75, 3 < 0.75, or 2 > 0.75, 3 < 0.75 to predict that the sample has further abnormal probes, and the number of abnormal probes H is updated (if any of these is true, 1 is added to any number H (1-17)).

[0085] Furthermore, in block 540, for any sample classified as "normal" or "polymorphic," check if 13<0.85, 14<0.85, and 17<0.85. If true, an abnormal probe is detected, and the sample is reclassified as H abnormal (where H=3). For any sample classified as "H abnormal CNV," the algorithm checks if the probe is 13<0.85, 14<0.85, and 17<0.85. If true, an additional abnormal probe is detected, and the number of abnormal probes H is updated (add 3 to any number H (1-17)).

[0086] Furthermore, in block 540, all samples are checked for the classification of samples containing Hb Constant Spring single nucleotide variants (SNVs). The presence or absence of SNVs is determined by the presence or absence of the Constant Spring SNV probe. In certain cases, the sample probe / reference probe ratio and copy number call threshold used for analysis include (i) positive probe signal data for probe 18 listed in Table 3 for HS40 homozygous deletions, and (ii) this probe signal is >0.

[0087] If the analysis predicts that the sample has an HS40 homozygous deletion, the sample's previous classification will be linked to HS40 homozygous deletion. If the analysis predicts that the sample has an HS40 heterozygous deletion, the sample's previous classification will be linked to HS40 heterozygous deletion. If the analysis predicts that the sample does not have an HS40 homozygous or heterozygous deletion, the sample's previous classification will not be changed. If the analysis predicts that the sample has additional anomalous probes, the number of anomalous probes will be updated, and the classification will remain as H anomalous CNV. If the analysis predicts that the sample has an Hb Constant Spring mutation, the sample's previous classification will be linked to Hb Constant Spring. If the analysis predicts that the sample does not have Hb Constant Spring, the sample's previous classification will not be changed.

[0088] The result of this step 540 is the final classification. At this point, all samples are classified as normal, containing only polymorphisms and one or more identifiable mutations (e.g., α 3.7 , α 4.2 SEA, MED1, MED2, THAI, FIL and / or α 20.5 ), should have CNVs with H-abnormal probes or large, unclassifiable deletions. If a sample has CNVs with H-abnormal probes or large, unclassifiable deletions, the sample should be manually reviewed.

[0089] In block 545, the HBA genotype of each sample is determined based on the final classification of each sample. For example, HETα 3.7 or α 4.2 Deletion and HET SEA, FIL, MED, THAI or α 20.5 For samples with classification, the genotype is determined as -- / -α (see, for example, Table 2). In the optional block 550, a risk score can be calculated based on the HBA genotype determined for each sample and the results shown, as shown in Table 2. In some cases, the risk score is (i) the subject is α 3.7 , α 4.2 ,SEA,MED,THAI,FIL,α 20.5 (ii) α 3.7 , α 4.2 ,SEA,MED,THAI,FIL,α 20.5 and the risk of couples identified as carriers of HS-40 deletion and Hb Constant Spring point mutation, as well as / or (iii)α 3.7 , α 4.2 ,SEA,MED,THAI,FIL,α 20.5 This may also help identify the risk of fetuses inheriting HS-40 deletion and Hb Constant Spring point mutations.

[0090] In block 555, the HBA genotype and any risk score determined for each allele can be output. Providing the output of the HBA genotype and any risk score determined for each allele may include providing the output to the end user and / or recording the output in a storage device (e.g., displaying the output on a user interface and / or storing the output in a results file in a database).

[0091] Figure 6 shows an exemplary computing device 600 suitable for use in a system and method for HBA genotyping using the HBA assay platform and genotyping techniques of this disclosure. The exemplary computing device 600 includes a processor 605 that communicates with memory 610 and other components of the computing device 600 using one or more communication buses 615. The processor 605 is configured to execute processor-executable instructions stored in memory 610 to perform one or more methods for searching and identifying HBA peaks present in raw data, determining the genotype of HBA in a specimen, and / or determining a patient's risk score, according to different examples such as some or all of the exemplary processes 400 or 500 described above with respect to Figures 4 and 5. In this example, memory 610 stores processor-executable instructions that provide HBA peak analysis 620 and HBA genotyping 625, as previously described with respect to Figures 1, 2, 4, and 5.

[0092] The computing device 600 also includes, in this example, one or more user input devices 630, such as a keyboard, mouse, touchscreen, or microphone, to accept user input. The computing device 600 also includes a display 635 for providing visual output to the user, such as a user interface. The computing device 600 also includes a communication interface 640. In some examples, the communication interface 640 may enable communication over one or more networks, such as a local area network ("LAN"), a wide area network ("WAN") such as the Internet, a metropolitan area network ("MAN"), or point-to-point or peer-to-peer connections. Communication with other devices can be achieved using any suitable network protocol. For example, one suitable network protocol may include the Internet Protocol ("IP"), Transmission Control Protocol ("TCP"), User Datagram Protocol ("UDP"), or a combination thereof, such as TCP / IP or UDP / IP. [Examples]

[0093] IV. Examples The systems and methods implemented in various embodiments can be better understood by referring to the following examples.

[0094] Example 1: HBA assay and HBA genotype determination tree matrix Sample collection, data collection, HBA assay analysis Genomic DNA was extracted from 224 blood samples, and 41 prenatal specimens and two cell lines (Coriell NA03433, NA10797) were used in this exemplary experiment. Of the blood samples, 49 were either fresh or stored. Before deidentification, any α-thalassemia genotype information was retained for each sample, where available. All samples were anonymized before use in this exemplary experiment. Raw data were collected using an ABI3730XL gene analyzer with ABI Foundation Data Collection software v3.0 and uploaded to GeneMarker software v2.7.0 for sample quality analysis, synthetic reference generation, and normalization of sample signals to synthetic reference signals for detecting deletions and duplications. Quality indicators for analysis are listed in Table 1. In this experiment, the manufacturer-recommended threshold for relative probe ratio (magnification change vs. reference) in the absence of deletions or duplications was used. The standard deviation threshold for the control probe was experimentally determined.

[0095] Analytical sensitivity and specificity To establish analytical sensitivity and specificity, 69 specimens and cell lines of known genotypes (39 positive and 30 negative, Table 4) were tested with the HBA MLPA assay, as described with respect to Figures 1–3. Genotype calling was performed both by the HBA genotype determination tree matrix (described with respect to Figures 4 and 5) and by manual review. All samples were quantified using a SpectraMax M2 Fluorometer, with inputs ranging from 12.5 ng to 100 ng. Genotypes were blinded to operators before use. [Table 4]

[0096] quality indicators The overall mean control probe standard deviation was 0.048 ± 0.030. Of the 69 samples tested, 6 initially failed to pass the sample quality indicators (6 / 69, 8.7%, Table 5) and were repeated with the same DNA aliquots. The input amounts for three of these samples were 15 ng, 16 ng, and 29 ng, which were below the lower limit (50–100 ng) recommended by the manufacturer. The other three samples had been cryopreserved for at least 15 years, and information on the extraction method used was unavailable. Upon retesting, all 6 samples passed the quality indicators and were considered acceptable for genotype calling (Table 5). [Table 5]

[0097] Genotype Call All samples were analyzed using the quality check thresholds shown in Table 1. No false negatives were detected, and all 30 negative samples were correctly called, achieving 100% specificity, using either the HBA genotype decision tree matrix (explained in relation to Figures 4 and 5) or manual analysis. Of the 39 positive samples, 35 and 37 samples were identified for their targeted genotypes using the HBA genotype decision tree matrix and manual analysis, respectively (Table 6). For samples where mutations were detected but the genotype was not specifically called, two were duplicates and were not the targeted mutants.

[0098] Manual analysis of the two duplicate samples revealed that one was heterojunction α 3.7 As a duplicate (sample ZZ-59), the other is heterojunction α 4.2 It was correctly identified as a duplicate (sample ZZ-48). The HBA genotype decision tree matrix also detected duplicates, but was unable to assign one of the targeted genotypes to them, and instead flagged these samples for manual review. That is, in the case of ZZ-59, α 3.7All probes except for one region exceeded the threshold of 1.30 for calling duplicates, and instead of calling this normal, the HBA genotype determination tree matrix flagged it for manual review. α 4.2 For ZZ-48, which has overlapping genotypes, the HBA genotype determination tree matrix was not programmed to call this particular genotype. Importantly, for both samples, the HBA genotype determination tree matrix did not miss any calls and instead defaulted to manual review.

[0099] Two samples that were heterozygous for BRIT deletions, although not one of the intended targeted mutations for this assay, were included in this experiment to test the HBA genotype determination tree matrix. These samples were referred to as heterozygous SEA deletions because the same MLPA probe detected either SEA or BRIT deletions in both the HBA genotype determination tree matrix and manual analysis. Multiplex PCR did not identify SEA deletions in either sample. The SEA deletion calls by HBA MLPA for these samples should not be considered false positives, as BRIT deletions are not the targeted mutations of the assay, and both calling methods detected large deletions of approximately the same size as BRIT deletions. Because the HBA MLPA assay can detect any number of large deletions other than those targeted for this test, which may have clinical significance, the HBA genotype determination tree matrix was designed to ensure that any copy-number variations detected by multiple probes were not missed and were instead subjected to manual review. Therefore, all targeted mutations were identified in positive samples, and 100% assay sensitivity was achieved using either an HBA genotype determination tree matrix or manual methods. [Table 6]

[0100] reproducibility For intra-assay reproducibility, three samples were tested in triplicate using the same assay run. These same samples were also used for inter-assay reproducibility using a second lot of reagent, a different operator, and a different day. Data analysis was performed by both manual analysis and HBA genotype determination tree matrices. For both intra-assay and inter-assay reproducibility, all samples except one (G05 - intra-assay 1) passed the QC index of the control probe standard deviation (Table 7), but the reproducibility of this passing sample suggested that sample quality was not the issue. MLPA lane scores or quality control fragments did not detect any problems with the MLPA reaction, and no evaporation was visually detected for this sample. In passing samples, the magnification change pair reference for each probe was reproducible (see, for example, Figure 7 - single probes (No. 15, 16, 19-23) consistently detected deletions with a magnification change of approximately 0.5, while duplicate probes (No. 13, 14, 17) detected deletions with a magnification change of approximately 0.75. Polymorphic probe No. 12 also detected deletions with a magnification change of approximately 0.75, and this particular α 3.7 Algorithmic genotype calling (indicating a possible deletion range) was 100% identical to manually performed calling. Based on this data, the assay was reproducible with each run. [Table 7]

[0101] Performance of the HBA genotype determination tree matrix The performance of the HBA genotyping determination tree matrix was further evaluated using 267 blinded samples. Genotype calls were compared with genotype calls obtained by manual review and / or from previous tests by other laboratories. Overall, the HBA genotyping determination tree matrix and manual / previous test results were consistent for 261 samples (261 / 267, 97.8%, Table 8) when first passing the HBA MLPA assay. Two samples with minimal genotyping information (one labeled "Edema" and the other "HemoH") were identified by the HBA genotyping determination tree matrix as homozygous SEA deletion and α, respectively. 3.7The SEA deletion in the trans-trans gene was genotyped and confirmed by multiplex PCR. In addition, as mentioned above, two samples with BRIT deletions indistinguishable from SEA deletions by the HBA MLPA assay were not identified as either SEA or any other targeted deletion by the multiplex PCR assay. These samples will be repeated in the MLPA assay for confirmatory testing in the clinical laboratory. [Table 8]

[0102] The HBA genotype determination tree matrix was trained to detect patterns of magnification changes in normalized sample probes, regardless of whether one of the targeted genotypes could be assigned, and as shown in Table 9, all six samples marked by the algorithm for review by the clinical director were due to inconsistencies in the configuration of relative probe ratios in the regions. In addition, the HBA genotype determination tree matrix is ​​designed to produce errors on the susceptible side (i.e., false positives) rather than missing calls (i.e., false negatives). Therefore, the HBA genotype determination tree matrix is ​​particularly α 3.7 Although it did not call duplicates, it detected an anomaly with one probe and flagged the sample for manual review rather than missing a call. Similarly, in three normal samples, the HBA genotype determination tree matrix identified irregularities using the relative probe ratios of multiple probes and designated them for manual review instead of miscalling the genotype. [Table 9]

[0103] Further consideration The above description provides specific details to enable a complete understanding of the embodiments. However, it is understood that embodiments can be carried out without these specific details. For example, circuits may be shown in block diagrams to avoid unnecessarily obscuring the embodiments with excessive detail. In other examples, well-known circuits, processes, algorithms, structures, and techniques may be shown in a non-excessively detailed manner to avoid obscuring the embodiments.

[0104] The techniques, blocks, steps, and means described above can be implemented in various ways. For example, these techniques, blocks, steps, and means can be implemented in hardware, software, or a combination thereof. In the case of hardware implementation, the processing unit can be implemented in one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field-programmable gate arrays (FPGAs), processors, controllers, microcontrollers, microprocessors, other electronic units designed to perform the functions described above, and / or combinations thereof.

[0105] Furthermore, it should be noted that this embodiment may be described as a process shown as a flowchart, flow diagram, data flow diagram, structure diagram, or block diagram. While flowcharts may describe operations as sequential processes, many operations may be performed in parallel or simultaneously. Moreover, the order of operations can be rearranged. A process terminates when its operations are complete, but it may have additional steps not shown in the diagram. A process may correspond to a method, function, procedure, subroutine, subprogram, etc. If a process corresponds to a function, its termination may correspond to the function's return to the called function or main function.

[0106] Furthermore, embodiments can be implemented by hardware, software, scripting languages, firmware, middleware, microcode, hardware description languages, and / or any combination thereof. When implemented by software, firmware, middleware, scripting languages, and / or microcode, program code or code segments for performing the required tasks can be stored in a machine-readable medium such as a storage medium. Code segments or machine-executable instructions can represent procedures, functions, subprograms, programs, routines, subroutines, modules, software packages, scripts, classes, or any combination of instructions, data structures, and / or program statements. Code segments can be coupled to other code segments or hardware circuits by passing and / or receiving information, data, arguments, parameters, and / or memory contents. Information, arguments, parameters, data, etc., can be passed, transferred, or transmitted via any suitable means, including memory sharing, message passing, ticket passing, network transmission, etc.

[0107] In the case of firmware and / or software implementations, the method may be implemented in a module (e.g., a procedure, a function, etc.) that performs the functions described herein. When implementing the method described herein, any machine-readable medium that materializes the instructions may be used. For example, software code may be stored in memory. Memory may be implemented within or outside the processor. As used herein, the term “memory” means any type of long-term storage medium, short-term storage medium, volatile storage medium, non-volatile storage medium, or other storage medium, and is not limited to any specific type of memory or number of memories, or the type of medium in which the memory is stored.

[0108] Furthermore, as disclosed herein, the terms “storage medium,” “storage device,” or “memory” may refer to one or more memories for storing data, such as read-only memory (ROM), random access memory (RAM), magnetic RAM, core memory, magnetic disk storage devices, optical storage devices, flash memory devices, and / or other machine-readable media for storing information. The term “machine-readable media” includes, but is not limited to, portable or fixed storage devices, optical storage devices, wireless channels, and / or various other storage media capable of storing or holding instructions and / or data.

[0109] While the principles of this disclosure have been described in relation to specific apparatuses and methods, it should be clearly understood that this description is provided for illustrative purposes only and is not intended to limit the scope of this disclosure. In certain embodiments, for example, the following items are provided: (Item 1) Obtaining raw data from hemoglobin A (HBA) assays performed on multiple samples, wherein the HBA assay is performed using multiple probes capable of detecting a decrease or increase in the copy number within the α-globin gene cluster region of each of the multiple samples, and the raw data includes HBA copy number data of the multiple probes separated by capillary electrophoresis for each of the multiple samples. Selecting a reference sample from the aforementioned multiple samples, Based on the raw data obtained from the HBA assay and the reference sample, calculate a first set of probe ratios for each of the multiple samples. Based on the first set of probe ratios, identify a predetermined number of reference samples to be combined as a synthetic reference sample for the plurality of samples. To generate the synthetic reference sample based on the predetermined number of reference samples, Based on the raw data obtained from the HBA assay and the synthetic reference sample, calculate a second set of probe ratios for each of the multiple samples. The second set of probe ratios for each sample is iteratively input into the decision tree matrix. Based on the decision tree matrix, the genotype of HBA in each sample is determined based on the second set of probe ratios for each sample and the copy number call threshold of the sample probe / reference probe ratio associated with each probe of the plurality of probes, and A method comprising providing the genotype of the HBA for each sample. (Item 2) The method according to item 1, wherein calculating the first set of probe ratios includes (i) comparing the peak height or signal of a control probe in each of the plurality of samples with the peak height or signal of a corresponding control probe in the reference sample; (ii) calculating the signal variation between the peak height or signal of the control probe in each sample and the peak height or signal of the corresponding control probe in the reference sample as the standard deviation of the control probe; (iii) determining that a sample of the plurality of samples is unacceptable if any variation index is greater than a predetermined threshold; (iv) determining that a sample of the plurality of samples is not unacceptable if none of the variation indexes are greater than the predetermined threshold; and (v) for each unacceptable sample, comparing the peak height or signal of a test probe in the sample with the peak height of a corresponding test probe in the reference sample, and calculating the probe ratio between the peak height or signal of the test probe in the sample and the peak height or signal of the corresponding test probe in the reference sample. (Item 3) The method according to item 1 or 2, wherein calculating the second set of probe ratios includes (i) comparing the peak height or signal of the control probe in each of the plurality of samples with the peak height or signal of the corresponding control probe in the synthetic reference sample; (ii) calculating the signal variation between the peak height or signal of the control probe in each sample and the peak height or signal of the corresponding control probe in the synthetic reference sample as the standard deviation of the control probe; (iii) determining that a sample of the plurality of samples is unacceptable if any variation index is greater than the predetermined threshold; (iv) determining that a sample of the plurality of samples is not unacceptable if none of the variation indexes are greater than the predetermined threshold; and (v) for each unacceptable sample, comparing the peak height or signal of the test probe in the sample with the peak height of the corresponding test probe in the synthetic reference sample, and calculating the probe ratio between the peak height or signal of the test probe in the sample and the peak height or signal of the corresponding test probe in the synthetic reference sample. (Item 4) The method according to item 1, 2, or 3, wherein determining the genotype of the HBA for each sample includes (i) determining a pattern of abnormal probe ratios for each sample based on the second set of probe ratios for each sample and the copy number call threshold for the sample probe / reference probe ratio associated with each probe among the plurality of probes, and (ii) identifying the genotype of the HBA for each sample based on the pattern of abnormal probe ratios. (Item 5) Determining the pattern of the abnormal probe ratio and identifying the genotype of the HBA in each sample is Each sample is classified either as a normal sample with copy number variation (CNV) or as a polymorphism based on the pattern of the abnormal probe ratio, and The method according to item 4, comprising subclassifying any sample classified as having the CNV as a major targeted deletion, duplication, or “other” based on the abnormal probe ratio pattern. (Item 6) Determining the pattern of the abnormal probe ratio and identifying the genotype of the HBA in each sample is Any sample classified as having the aforementioned large targeted deletion is subclassified as having a large heterozygous deletion or a homozygous deletion. Based on the aforementioned abnormal probe ratio pattern, the following deletions were identified: SEA, FIL / THAI, MED, or α 20.5 For one or more of these, any sample classified as a large heterozygous deletion or homozygous deletion is to be subclassified, Based on the aforementioned abnormal probe ratio pattern, the following applies: α 3.7 Deletion, α 4.2 Deletion and / or α 3.7 The method of item 5, further comprising subclassifying any sample classified as having the large heterozygous deletion for one or more of the overlaps. (Item 7) Determining the pattern of the abnormal probe ratio and identifying the genotype of the HBA in each sample is Based on the aforementioned abnormal probe ratio pattern, any sample classified as "other" is α 3.7 Deletion, α 4.2 Deletion, and / or α 3.7 The method of item 5, further comprising subclassifying as having overlap. (Item 8) The method according to any one of items 1 to 7, further comprising triggering the performance of a confirmatory test on each of the plurality of samples having an abnormal HBA genotype or not requiring manual review. (Item 9) One or more data processors, When executed on the aforementioned 1 or more data processors, the following applies to the aforementioned 1 or more data processors: Obtaining raw data from hemoglobin A (HBA) assays performed on multiple samples, wherein the HBA assay is performed using multiple probes capable of detecting a decrease or increase in the copy number within the α-globin gene cluster region of each of the multiple samples, and the raw data includes HBA copy number data of the multiple probes separated by capillary electrophoresis for each of the multiple samples. Selecting a reference sample from the aforementioned multiple samples, Based on the raw data obtained from the HBA assay and the reference sample, calculate a first set of probe ratios for each of the multiple samples. Based on the first set of probe ratios, identify a predetermined number of reference samples to be combined as a synthetic reference sample for the plurality of samples. To generate the synthetic reference sample based on the predetermined number of reference samples, Based on the raw data obtained from the HBA assay and the synthetic reference sample, calculate a second set of probe ratios for each of the multiple samples. The second set of probe ratios for each sample is iteratively input into the decision tree matrix. Based on the decision tree matrix, the genotype of HBA in each sample is determined based on the second set of probe ratios for each sample and the copy number call threshold of the sample probe / reference probe ratio associated with each probe of the plurality of probes, and To provide the genotype of the HBA for each sample, A system including a non-temporary computer-readable storage medium containing instructions for performing an action including the above. (Item 10) The system according to item 9, wherein calculating the first set of probe ratios includes: (i) comparing the peak height or signal of a control probe in each of the plurality of samples with the peak height or signal of a corresponding control probe in the reference sample; (ii) calculating the signal variation between the peak height or signal of the control probe in each sample and the peak height or signal of the corresponding control probe in the reference sample as the standard deviation of the control probe; (iii) determining that a sample of the plurality of samples is unacceptable if any variation index is greater than a predetermined threshold; (iv) determining that a sample of the plurality of samples is not unacceptable if none of the variation indexes are greater than the predetermined threshold; and (v) for each unacceptable sample, comparing the peak height or signal of a test probe in the sample with the peak height of a corresponding test probe in the reference sample, and calculating the probe ratio between the peak height or signal of the test probe in the sample and the peak height or signal of the corresponding test probe in the reference sample. (Item 11) The system according to item 9 or 10, wherein calculating the second set of probe ratios includes (i) comparing the peak height or signal of the control probe in each of the plurality of samples with the peak height or signal of the corresponding control probe in the synthetic reference sample; (ii) calculating the signal variation between the peak height or signal of the control probe in each sample and the peak height or signal of the corresponding control probe in the synthetic reference sample as the standard deviation of the control probe; (iii) determining that a sample of the plurality of samples is unacceptable if any variation index is greater than the predetermined threshold; (iv) determining that a sample of the plurality of samples is not unacceptable if none of the variation indexes are greater than the predetermined threshold; and (v) for each unacceptable sample, comparing the peak height or signal of the test probe in the sample with the peak height of the corresponding test probe in the synthetic reference sample, and calculating the probe ratio between the peak height or signal of the test probe in the sample and the peak height or signal of the corresponding test probe in the synthetic reference sample. (Item 12) The system according to item 9, 10, or 11, wherein determining the genotype of the HBA for each sample includes (i) determining a pattern of abnormal probe ratios for each sample based on the second set of probe ratios for each sample and the copy number call threshold for the sample probe / reference probe ratio associated with each probe among the plurality of probes, and (ii) identifying the genotype of the HBA for each sample based on the pattern of abnormal probe ratios. (Item 13) Determining the pattern of the abnormal probe ratio and identifying the genotype of the HBA in each sample is Each sample is classified either as a normal sample with copy number variation (CNV) or as a polymorphism based on the pattern of the abnormal probe ratio, and The system according to item 12, comprising subclassifying any sample classified as having the CNV as a major targeted deletion, duplication, or “other” based on the abnormal probe ratio pattern. (Item 14) Determining the pattern of the abnormal probe ratio and identifying the genotype of the HBA in each sample is Any sample classified as having the aforementioned large targeted deletion is subclassified as having a large heterozygous deletion or a homozygous deletion. Based on the aforementioned abnormal probe ratio pattern, the following deletions were identified: SEA, FIL / THAI, MED, or α 20.5 For one or more of these, any sample classified as a large heterozygous deletion or homozygous deletion is to be subclassified, Based on the aforementioned abnormal probe ratio pattern, the following deletions were identified, namely, α 3.7 Deletion and α 4.2 The system according to item 12, further comprising subclassifying any sample classified as having the large heterozygous deletion with respect to one or more of the deletions. (Item 15) The system according to any one of items 9 to 14, further comprising triggering the performance of a confirmation test on each of the plurality of samples having an abnormal HBA genotype or not requiring manual review. (Item 16) For one or more data processors, Obtaining raw data from hemoglobin A (HBA) assays performed on multiple samples, wherein the HBA assay is performed using multiple probes capable of detecting a decrease or increase in the copy number within the α-globin gene cluster region of each of the multiple samples, and the raw data includes HBA copy number data of the multiple probes separated by capillary electrophoresis for each of the multiple samples. Selecting a reference sample from the aforementioned multiple samples, Based on the raw data obtained from the HBA assay and the reference sample, calculate a first set of probe ratios for each of the multiple samples. Based on the first set of probe ratios, identify a predetermined number of reference samples to be combined as a synthetic reference sample for the plurality of samples. To generate the synthetic reference sample based on the predetermined number of reference samples, Based on the raw data obtained from the HBA assay and the synthetic reference sample, calculate a second set of probe ratios for each of the multiple samples. The second set of probe ratios for each sample is iteratively input into the decision tree matrix. Based on the decision tree matrix, the genotype of HBA in each sample is determined based on the second set of probe ratios for each sample and the copy number call threshold of the sample probe / reference probe ratio associated with each probe of the plurality of probes, and To provide the genotype of the HBA for each sample, A computer program product tangibly embodied in a non-temporary, machine-readable storage medium, including instructions configured to perform an action that includes [a specific action]. (Item 17) The computer program product according to item 16, wherein calculating the first set of probe ratios includes: (i) comparing the peak height or signal of a control probe in each of the plurality of samples with the peak height or signal of a corresponding control probe in the reference sample; (ii) calculating the signal variation between the peak height or signal of the control probe in each sample and the peak height or signal of the corresponding control probe in the reference sample as the standard deviation of the control probe; (iii) determining that a sample of the plurality of samples is unacceptable if any variation index is greater than a predetermined threshold; (iv) determining that a sample of the plurality of samples is not unacceptable if none of the variation indexes are greater than the predetermined threshold; and (v) for each unacceptable sample, comparing the peak height or signal of a test probe in the sample with the peak height of a corresponding test probe in the reference sample, and calculating the probe ratio between the peak height or signal of the test probe in the sample and the peak height or signal of the corresponding test probe in the reference sample. (Item 18) A computer program product according to item 17 or 17, wherein calculating the second set of probe ratios includes: (i) comparing the peak height or signal of the control probe in each of the plurality of samples with the peak height or signal of the corresponding control probe in the synthetic reference sample; (ii) calculating the signal variation between the peak height or signal of the control probe in each sample and the peak height or signal of the corresponding control probe in the synthetic reference sample as the standard deviation of the control probe; (iii) determining that a sample of the plurality of samples is unacceptable if any variation index is greater than the predetermined threshold; (iv) determining that a sample of the plurality of samples is not unacceptable if none of the variation indexes are greater than the predetermined threshold; and (v) for each unacceptable sample, comparing the peak height or signal of the test probe in the sample with the peak height of the corresponding test probe in the synthetic reference sample, and calculating the probe ratio between the peak height or signal of the test probe in the sample and the peak height or signal of the corresponding test probe in the synthetic reference sample. (Item 19) The computer program product according to item 16, 17, or 18, wherein the operation further comprises determining a risk score for a subject associated with the sample based on the AGG genotype generated for a first allele, a second allele, or both the first and second alleles, the risk score identifying the subject's risk of developing a late-onset neurodegenerative disease, fragile X-related tremor / ataxia syndrome (FXTAS), or fragile X-related primary ovarian failure (FXPOI), or the risk of transmitting a fully mutant allele to offspring, or any combination thereof. (Item 20) A computer program product according to item 16, 17, or 18, wherein determining the genotype of the HBA for each of the samples includes (i) determining a pattern of abnormal probe ratios for each sample based on the second set of probe ratios for each sample and the copy number call threshold for the sample probe / reference probe ratio associated with each probe among the plurality of probes, and (ii) identifying the genotype of the HBA for each sample based on the pattern of abnormal probe ratios. (Item 21) The computer program product according to any one of items 16 to 20, further comprising triggering the performance of a confirmation test on each of the plurality of samples having an abnormal HBA genotype or not requiring manual review.

Claims

[Claim 1] The invention described in the specification.

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