DETAILED ACTION This is in response to the application No. 18/ 476,232 filed on September 27 , 2023. C laims 1-2 0 are submitted for examination and claims 1, 9 and 15 are independent. Notice of Pre-AIA or AIA Status 2. The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA. Priority 3 . This application filed on 09/27/2023 Claims Priority from Provisional Application 63377846 , filed on 09/30/2022 . Information Disclosure Statement 4 . The information disclosure statements (IDS) submitted on 02/29/2024; 04/25/2024; 07/25/2024; 12/09/2024; 03/13/2025; 05/08/2025; 16/17/2025; 08/15/2025 and 10/30/2025 ha ve been considered. The submission is in-compliance with the provisions of 37 CFR 1.97. Form PTO-1449 is signed and attached hereto. Drawings 5 . The drawings filed on September 27 , 2023 are accepted. Specification 6 . The specification filed on September 27 , 2023 is also accepted. Claim Rejections - 35 USC § 102 7 . The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action: A person shall be entitled to a patent unless – (a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale or otherwise available to the public before the effective filing date of the claimed invention. (a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention. 8 . Cla ims 1 -20 are rejected under 35 U.S.C. 102 (a)( 1 ) as being anticipated by NPL document, titled, “ PostSV: A Post–Processing Approach for Filtering Structural Variation s” by Eman Alzaid et al (herein after referred as Alzaid ) ( Vol. 14: 2020) (This prior art is cited and provided with the IDS] The following is referring to independent claim s 1, 9 and 15 : As per independent claim 1 , a system comprising: at least one processor; and a non-transitory computer readable medium comprising instructions that, when executed by the at least one processor, cause the system to [Page 6, column 2, paragraph 2 ]: determine, for one or more genomic coordinates of a genomic sample, an initial structural variant call based on nucleotide reads corresponding to the genomic sample [ “the SV predictions as a 3-tuple : chromosome name, start position and end position”, at least page 2 , column 1 , paragraph 2 ] identify sequencing metrics corresponding to one or more of the initial structural variant call or the one or more genomic coordinates [“read-depth”; page 3, column 1, paragraph 3]; generate, utilizing a structural variant refinement machine-learning model based on the sequencing metrics, a false positive likelihood indicating a likelihood that the initial structural variant call is a false positive ( “Classification of SV predictions into true positive and false positives ”, page 3, column 2, paragraph 3, the likelihood for false positive has to be determined in order to perform classification] ; and determine a modified structural variant call for the one or more genomic coordinates of the genomic sample based on the false positive likelihood [ See abstract, “Several classifiers are employed to classify the candidate predictions and remove false positive”] As per independent claim 9 , independent claim 9 is rejected for same reason as that of the above independent claim 1. As per independent claim 15 , independent claim 15 is rejected for same reason as that of the above independent claim 1. The following is referring to dependent claims 2-8, 10-14 and 16-20 : As per dependent claim 2 , Alzaid di scloses the method /system as applied to claim 1 above. Furthermore, Alzaid di scl oses the method/device , further comprising instructions that, when executed by the at least one processor, cause the system to determine the initial structural variant call by determining a deletion of more than a threshold number of base pairs, an insertion of more than the threshold number of base pairs, a duplication of more than the threshold number of base pairs, an inversion, a translocation, or a copy number variation (CNV) [ Page 1, column 1, paragraph 1, under introduction, “These rearrangements have several forms including insertions, deletions, translocations, inversions, duplications, and copy number variations (CNVs)”] . As per dependent claim 3 , Alzaid di scloses the method /system as applied to claim 1 above. Furthermore, Alzaid di scl oses the method/device , further comprising instructions that, when executed by the at least one processor, cause the system to determine the initial structural variant call by determining a structural variant call of a number of base pairs within a threshold range of base pairs [Page 2, column 2, paragraph 3, “(2) the distance between the breakpoints of a single-end signature and the corresponding SV breakpoints does not exceed a defined threshold”] . As per dependent claim 4 , Alzaid di scloses the method /system as applied to claim 1 above. Furthermore, Alzaid di scl oses the method/device , further comprising instructions that, when executed by the at least one processor, cause the system to identify the sequencing metrics corresponding to the initial structural variant call by identifying one or more of read-based sequencing metrics, reference-based sequencing metrics, or variant region quality sequencing metrics [ Page 3, column 1, paragraph 2-3: read depth, genome mean coverage] . As per dependent claim 5 , Alzaid di scloses the method /system as applied to claim 4 above. Furthermore, Alzaid di scl oses the method/device , further comprising instructions that, when executed by the at least one processor, cause the system to identify the read-based sequencing metrics by determining, for the initial structural variant call, one or more of: one or more base-call quality scores; a fraction of nucleotide reads supporting an alternate contiguous sequence from a reference genome; a number of split nucleotide reads from the nucleotide reads corresponding to the initial structural variant call; a coverage depth of the nucleotide reads corresponding to the initial structural variant call; an additional structural variant call located within a threshold number of base pairs from the initial structural variant call within the genomic sample; an alignment of a contiguous sequence corresponding to the nucleotide reads with a reference sequence of a reference genome modified to include a structural variant corresponding to the initial structural variant call; a deletion length in nucleotide bases based on one or more soft clipped nucleotide reads; a number of the nucleotide reads exhibiting a mapping quality metric that fails to satisfy a threshold mapping quality metric; an insert size representing a length of nucleotide-read fragments corresponding to the initial structural variant call; or a structural-variant likelihood representing a ratio of the initial structural variant call to a reference call for the one or more genomic coordinates based on the insert size [Page 1, column 2, paragraph 1, “split reads (SRs), are one of the main sources of information used to refine SV breakpoints” Page 3, column 1, paragraph 2-3: read depth, genome mean coverage] . As per dependent claim 6 , Alzaid di scloses the method /system as applied to claim 4 above. Furthermore, Alzaid di scl oses the method/device , further comprising instructions that, when executed by the at least one processor, cause the system to identify the variant region quality sequencing metrics by determining one or more of: a number of nucleotide reads that comprise at least a threshold number of base calls and correspond to a target genomic region for the initial structural variant call; or a number of nucleotide bases in an alternate contiguous sequence corresponding to the target genomic region from a reference genome for which base calls for the nucleotide reads fail to satisfy a threshold base call quality score [ Page1, column 1, paragraph 2: minimum and maximum thresholds for insert sizes for identifying SV regions] . As per dependent claim 13 , dependent claim 13 is rejected for same reason as that of the above dependent claim 6. As per dependent claim 7 , Alzaid di scloses the method /system as applied to claim 4 above. Furthermore, Alzaid di scl oses the method/device , further comprising instructions that, when executed by the at least one processor, cause the system to identify the reference-based sequencing metrics by identifying, within one or more genomic regions of a reference genome corresponding to the one or more genomic coordinates of the genomic sample, one or more of: a tandem repeat length in nucleotide bases; a permutation entropy of nucleotide bases; a cytosine quadruplex (C-quadruplex); or a guanine quadruplex (G-quadruplex) [Page 4, column 1, paragraph 4] . As per dependent claim 14 , dependent claim 14 is rejected for same reason as that of the above dependent claim 7. As per dependent claim 8 , Alzaid di scloses the method /system as applied to claim 4 above. Furthermore, Alzaid di scl oses the method/device , further comprising instructions that, when executed by the at least one processor, cause the system to: generate the false positive likelihood by determining the initial structural variant call is a false positive call or a true positive call based on the sequencing metrics; and determine the modified structural variant call by: changing the initial structural variant call from a positive structural variant call to a negative structural variant call based on the initial structural variant call being the false positive call; or changing the initial structural variant call from a negative structural variant call to a positive structural variant call based on the initial structural variant call being the true positive call [“Classification of SV predications into true positives and false positives ” page 3, column 2, paragraph 3, the likelihood for false positive has to be determined in order to perform classification and See abstract, “Several classifiers are employed to classify the candidate predictions and remove false positive] . As per dependent claim 17 , dependent claim 17 is rejected for same reason as that of the above dependent claim 8 . As per dependent claim 10 , Alzaid di scloses the method /system as applied to claim 9 above. Furthermore, Alzaid di scl oses the method/device : determining the initial structural variant call comprises utilizing a call generation model to determine base calls corresponding to the one or more genomic coordinates of the genomic sample indicate a structural variant in relation to a reference genome; and determining the modified structural variant call comprises correcting the initial structural variant call for the one or more genomic coordinates based on the false positive likelihood generated by the structural variant refinement machine-learning model [ See at least abstract, “Several classifiers are employed to classify the candidate predictions and remove false positive ] . As per dependent claim s 11-12 , Alzaid di scloses the method /system as applied to claim 9 above. Furthermore, Alzaid di scl oses the method/device : , wherein identifying the sequencing metrics corresponding to the initial structural variant call comprises identifying one or more of read-based sequencing metrics, reference-based sequencing metrics, or variant region quality sequencing metrics [ See at least page 14 ] . As per dependent claim 16 , Alzaid di scloses the method /system as applied to claim 15 above. Furthermore, Alzaid di scl oses the method/device , wherein the structural variant refinement machine-learning model comprises one or more gradient boosted decision trees [gradient boosted decision tree are an obvious alternative to random forests as used by page 3, paragraph 4] . As per dependent claim 18 , dependent claim 18 is rejected for same reason as that of the above independent claim 15. As per dependent claim 1 9 , Alzaid di scloses the method /system as applied to claim 15 above. Furthermore, Alzaid di scl oses the method/device , further comprising instructions that, when executed by the at least one processor, cause the computing device to determine the ground truth structural variant call is incorrectly labeled based on the structural variant criteria by: parsing a Concise Idiosyncratic Gapped Alignment Report (CIGAR) string to identify a truth set nucleotide read of the truth dataset that satisfies a threshold mapping quality metric; determining a portion of the CIGAR string comprising a starting index of a corresponding structural variant call generated by a call generation model; and determining that the starting index corresponds to a structural variant and matches a length of the corresponding structural variant call generated by the call generation model [ See page 14, paragraph 3: CIGAR string ] . As per dependent claim 20 , Alzaid di scloses the method /system as applied to claim 15 above. Furthermore, Alzaid di scl oses the method/device , further comprising instructions that, when executed by the at least one processor, cause the computing device to generate the false positive likelihood utilizing the structural variant refinement machine-learning model based on the sequencing metrics and the initial structural variant call as inputs [ Classification of SV predications into true positives and false positives ” page 3, column 2, paragraph 3, the likelihood for false positive has to be determined in order to perform classification and page 6, paragraph 2] . Conclusion 9 . The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. A. US Publication No. 20160232291 A1 to Kyriazopoulou-Panagiotopoulou discloses Systems and methods for determining structural variation and phasing using variant call data obtained from nucleic acid of a biological sample are provided. Sequence reads are obtained, each comprising a portion corresponding to a subset of the test nucleic acid and a portion encoding a barcode independent of the sequencing data. Bin information is obtained. Each bin represents a different portion of the sample nucleic acid. Each bin corresponds to a set of sequence reads in a plurality of sets of sequence reads formed from the sequence reads such that each sequence read in a respective set of sequence reads corresponds to a subset of the nucleic acid represented by the bin corresponding to the respective set. Binomial tests identify bin pairs having more sequence reads with the same barcode in common than expected by chance. Probabilistic models determine structural variation likelihood from the sequence reads of these bin pairs. B. US Publication No. 20220277811 A1 DePristo discloses a method for detecting false positive variant calls in a next generation sequencing analysis pipeline involves obtaining a plurality of read pileup windows associated with a first sample genome. The method also involves obtaining, for each reference nucleotide position represented in the plurality of read pileup windows, a label indicating that the reference nucleotide position is either (i) a known variant or (ii) a non-variant. The method further involves training a neural network based on data indicative of the plurality of read pileup windows and the labels. Additionally, the method involves receiving a read pileup window associated with a second sample genome. Further, the method involves determining, using the trained neural network, a likelihood that the read pileup window associated with the second sample genome represents a variant. C. See the other cited prior arts. Any inquiry concerning this communication or earlier communications from the examiner should be directed to FILLIN "Examiner name" \* MERGEFORMAT SAMSON B LEMMA whose telephone number is 571-272-3806. The examiner can normally be reached on FILLIN "Work schedule?" \* MERGEFORMAT M-F 8am-10pm . If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Shaw Yin Chen can be reached on to 571-272-8878 . The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300. Information regarding the status of an application may be obtained from the Patent Application Information Retrieval (PAIR) system. Status information for published applications may be obtained from either Private PAIR or Public PAIR. Status information for unpublished applications is available through Private PAIR only. For more information about the PAIR system, see http://pair-direct.uspto.gov. Should you have questions on access to the Private PAIR system, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative or access to the automated information system, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. /SAMSON B LEMMA/ Primary Examiner, Art Unit 2498