Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Status of the Claims
Claims 1-20 are currently pending and under exam herein.
Claims 1-20 are rejected.
Claims 21-34 are canceled.
Priority
The instant application claims priority from provisional applications 63/361,386 filed on 12/15/2021 and 63/326,227 filed on 03/31/2022. Thus, the effective filing date of the instant application is 12/15/2021.
Drawings
The Drawings filed on 12/15/2022 were considered.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 10/02/2023 is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement has been considered by the examiner.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claims recite: (a) mathematical concepts, (e.g., mathematical relationships, formulas or equations, mathematical calculations); and (b) mental processes, i.e., concepts performed in the human mind, (e.g., observation, evaluation, judgement, opinion).
Subject matter eligibility evaluation in accordance with MPEP 2106:
Eligibility Step 1: Claims 1-20 are directed to systems and methods for iterative and scalable population-scale variant analysis and is categorically
[Step 1: YES]
Eligibility Step 2A: First it is determined in Prong One whether a claim recites a judicial exception, and if
so, then it is determined in Prong Two whether the recited judicial exception is integrated into a
practical application of that exception.
Eligibility Step 2A Prong One: In determining whether a claim is directed to a judicial exception,
examination is performed that analyzes whether the claim recites a judicial exception, i.e., whether a
law of nature, natural phenomenon, or abstract idea is set forth or described in the claim.
Independent claim 1 recites the following steps which fall within the mental processes and/or mathematical concepts groupings of abstract ideas:
generating a first cohort file for the first batch by aggregating data from a subset of fields in each of the first plurality of genomic variant call files; (mathematical concept, mental process)
generating a first census file that comprises variant summary statistics and hom-ref blocks of the first batch; (mathematical concept)
generating a second cohort file for the second batch by aggregating data from the subset of fields in each of the second plurality of genomic variant call files; (mathematical concept)
generating a second census file that comprises variant summary statistics and hom-ref blocks of the second batch; (mathematical concept)
generating a global census file by aggregating the first census file and the second census file, wherein the global census file comprises census data from batches of samples received from sequencing devices at different sites; (mathematical concept)
generating a first multi-sample variant call file for the first batch using the first cohort file, the first census file, and the global census file; and (mathematical concept)
generating a second multi-sample variant call file for the second batch using the second cohort file, the second census file, and the global census file (mathematical concept)
Dependent claim 2 recites the following steps which fall within the mental processes and/or mathematical concepts groupings of abstract ideas:
performing a genome-wide sequencing analysis using one or more of the first multi- sample variant call file or the second multi-sample variant call file (mathematical concept)
Dependent claim 3 recites the following steps which fall within the mental processes and/or mathematical concepts groupings of abstract ideas:
wherein the first plurality of genomic variant call files associated with the first batch are split into shards of equal size, and wherein each shard is processed using one of a plurality of computation nodes (mathematical concept)
Dependent claim 4 recites the following steps which fall within the mental processes and/or mathematical concepts groupings of abstract ideas:
generating a third cohort file for the third batch by aggregating data from the subset of fields in each of the third plurality of genomic variant call files; (mathematical concept)
generating a third census file that comprises variant summary statistics and hom-ref blocks of the third batch; (mathematical concept)
updating the global census file by aggregating the third census file with the global census file; (mathematical concept)
and generating a third multi-sample variant call file for the third batch using the third cohort file, the third census file, and the updated global census file. (mathematical concept)
Independent claim 6 recites the following steps which fall within the mental processes and/or mathematical concepts groupings of abstract ideas:
generate, from the one or more genomic variant call files, one or more cohort files and one or more census files; (mathematical concept)
aggregate the one or more census files into a global census file, wherein the global census file comprises census data from batches of samples received from sequencing devices at different sites; (mathematical concept)
generate, based on the global census file, the one or more cohort files, and the one or more census files, at least one multi-sample variant call file; (mathematical concept)
and store the multi-sample variant call file in the memory. (mathematical concept)
Dependent claim 8 recites the following steps which fall within the mental processes and/or mathematical concepts groupings of abstract ideas:
wherein the instructions are further configured to cause the at least one processor to perform parallel processing using multiple compute nodes (mathematical concept)
Dependent claim 9 recites the following steps which fall within the mental processes and/or mathematical concepts groupings of abstract ideas:
wherein the instructions, when executed by the at least one processor, further cause the processor to: perform parallelization and multithreading by regions of sequence data (mathematical concept)
Dependent claim 10 recites the following steps which fall within the mental processes and/or mathematical concepts groupings of abstract ideas:
wherein at least two compute nodes perform at least two levels of parallelization for processing, aggregating, or generating data for a corresponding region of the sequence data, wherein each compute node processes a specific region (mathematical concept)
Dependent claim 11 recites the following steps which fall within the mental processes and/or mathematical concepts groupings of abstract ideas:
wherein the cohort files and the census files in a region are bit compressed and serialized (mathematical concept)
Independent claim 12 recites the following steps which fall within the mental processes and/or mathematical concepts groupings of abstract ideas:
identify, using reference alternate genotype (RAGT) statistics in the plurality of genomic variant call files, a plurality of reference alleles and a plurality of alternate alleles associated with the plurality of samples; (mathematical concept)
count the instances of each of the plurality of reference alleles and each of the plurality of alternate alleles (mathematical concept)
select a normalized reference allele from the plurality of reference alleles, wherein the longest reference allele is selected as the normalized reference allele; (mathematical concept, mental process)
normalize the other reference alleles of the plurality of reference alleles by extending the other reference alleles to correspond to the normalized reference allele; (mathematical concept)
normalize the plurality of alternate alleles by extending each alternate allele the same amount that the respective corresponding reference allele was extended; and (mathematical concept)
generate a multi-sample variant call file using the normalized reference alleles and the normalized alternate alleles. (mathematical concept)
Dependent claim 13 recites the following steps which fall within the mental processes and/or mathematical concepts groupings of abstract ideas:
wherein the instructions further cause the at least one processor to generate a normalized representation of each sample using the normalized reference allele such that each of the plurality of alternate alleles are indexed using the normalized reference allele. (mathematical concept)
Dependent claim 14 recites the following steps which fall within the mental processes and/or mathematical concepts groupings of abstract ideas:
wherein the other reference alleles are extended by adding a respective number of bases to correspond to the normalized reference allele (mathematical concept)
Dependent claim 15 recites the following steps which fall within the mental processes and/or mathematical concepts groupings of abstract ideas:
identify a reference allele and one or more alternate alleles associated with the additional sample (mental process)
update the normalized representation to include the reference allele and the one or more alternate alleles associated with the additional sample (mathematical process)
Dependent claim 16 recites the following steps which fall within the mental processes and/or mathematical concepts groupings of abstract ideas:
determine that the length of the reference allele is shorter than the normalized reference allele; (mathematical process, mental process)
extend the reference allele and the one or more alternate alleles to correspond to the normalized reference allele (mathematical process, mental process)
; and reorder the plurality of reference alleles and the plurality of alternate alleles to include the extended reference allele and the one or more extended alternate alleles. (mathematical process, mental process)
Dependent claim 17 recites the following steps which fall within the mental processes and/or mathematical concepts groupings of abstract ideas:
determine that the length of the reference allele is longer than the normalized reference allele; select the reference allele as an updated normalized reference allele; (mathematical process, mental process)
normalize the plurality of reference alleles and the plurality of alternate alleles by extending to correspond to a length of the updated normalized reference allele; (mathematical process, mental process)
and reorder the plurality of reference alleles and the plurality of alternate alleles to include the updated normalized reference allele and the one or more extended alternate alleles. (mathematical process, mental process)
Dependent claim 18 recites the following steps which fall within the mental processes and/or mathematical concepts groupings of abstract ideas:
wherein the instructions further cause the at least one processor to reorder the genotype of each sample based on the normalized reference allele and the normalized representations (mathematical process, mental process)
Dependent claim 19 recites the following steps which fall within the mental processes and/or mathematical concepts groupings of abstract ideas:
wherein the instructions further cause the at least one processor to generate a mapping for each of the plurality of alternate alleles based on the normalized reference allele. (mathematical process)
Dependent claim 20 recites the following steps which fall within the mental processes and/or mathematical concepts groupings of abstract ideas:
wherein the mapping for each of the plurality of alternate alleles is stored in site information in a census file (mathematical process)
The abstract ideas recited in the claims are evaluated under the broadest reasonable interpretation (BRI) of the claim limitations when read in light of and consistent with the specification. As noted in the foregoing section, the claims are determined to contain limitations that can practically be performed in the human mind with the aid of a pencil and paper, and therefore recite judicial exceptions from the mental process grouping of abstract ideas. Additionally, the recited limitations that are identified as judicial exceptions from the mathematical concepts grouping of abstract ideas are abstract ideas irrespective of whether or not the limitations are practical to perform in the human mind.
Therefore, claims 1-20 recite an abstract idea as the dependent claims will inherit the abstract ideas from the independent claims.
[Step 2A Prong One: YES]
Eligibility Step 2A Prong Two: In determining whether a claim is directed to a judicial exception, further
examination is performed that analyzes if the claim recites additional elements that when examined as a
whole integrates the judicial exception(s) into a practical application (MPEP 2106.04(d)). A claim that
integrates a judicial exception into a practical application will apply, rely on, or use the judicial exception
in a manner that imposes a meaningful limit on the judicial exception. The claimed additional elements
are analyzed to determine if the abstract idea is integrated into a practical application (MPEP
2106.04(d)(I); MPEP 2106.05(a-h)). If the claim contains no additional elements beyond the abstract
idea, the claim fails to integrate the abstract idea into a practical application (MPEP 2106.04(d)(III)).
The judicial exceptions identified in Eligibility Step 2A Prong One are not integrated into a practical application because of the reasons noted below.
The additional element in independent claim 1 includes:
A computer-implemented method of iterative gVCF genotyping, the method comprising:
receiving a first plurality of genomic variant call files associated with a first batch of sequencing data;
receiving a second plurality of genomic variant call files associated with a second batch of sequencing data;
The additional element in dependent claim 4 includes:
receiving a third plurality of genomic variant call files associated with a third batch of sequencing data;
The additional element in dependent claim 5 includes:
wherein the method is performed on a local computing system or is distributed across a cloud-computing system.
The additional element in dependent claim 6 includes:
A system, comprising: at least one processor; and a computer readable medium comprising instructions that, when executed by the at least one processor, cause the at least one processor to:
receive one or more genomic variant call files associated with one or more samples;
The additional element in dependent claim 7 includes:
wherein the samples comprise samples from a sequencing run, a sequencing cycle, or multiple sequencing runs.
The additional element in independent claim 12 includes:
A system, comprising: at least one processor; and a computer readable medium comprising instructions that, when executed by the at least one processor, cause the at least one processor to:
receive a plurality of genomic variant call files, each of the genomic variant call files associated with a respective sample of a plurality of samples;
The additional element in dependent claim 15 includes:
receive an additional genomic variant call file associated with an additional sample
The additional elements of receiving a first plurality of genomic variant call files associated with a first batch of sequencing data (Claim 1), receiving a second plurality of genomic variant call files associated with a second batch of sequencing data (Claim 1), receiving a third plurality of genomic variant call files associated with a third batch of sequencing data (Claim 4), receive one or more genomic variant call files associated with one or more samples (Claim 6), wherein the samples comprise samples from a sequencing run, a sequencing cycle, or multiple sequencing runs (Claim 7), receive a plurality of genomic variant call files, each of the genomic variant call files associated with a respective sample of a plurality of samples (Claim 12), receive an additional genomic variant call file associated with an additional sample (Claim 15) are insignificant extra-solution activity that are part of the data gathering process used in the recited judicial exceptions (see MPEP 2106.05(g)).
The additional elements of A computer-implemented method of iterative gVCF genotyping, the method comprising (Claim 1), wherein the method is performed on a local computing system or is distributed across a cloud-computing system (Claim 5), A system, comprising: at least one processor; and a computer readable medium comprising instructions that, when executed by the at least one processor, cause the at least one processor to (Claim 6),A system, comprising: at least one processor; and a computer readable medium comprising instructions that, when executed by the at least one processor, cause the at least one processor to (Claim 12), fail to integrate a judicial exception into a practical application merely reciting the words "apply it" (or an equivalent) with the judicial exception, or merely including instructions to implement an abstract idea on a computer, or merely using a computer as a tool to perform an abstract idea, as discussed in MPEP § 2106.05(f).
Thus, the additionally recited elements merely invoke a computer as a tool, and/or amount to insignificant extra-solution data gathering activity, and as such, when all limitations in claims 1-20 have been considered as a whole, the claims are deemed to not recite any additional elements that would integrate a judicial exception into a practical application, and therefore claims 1-20 are directed to an abstract idea (MPEP 2106.04(d)).
[Step 2A Prong Two: NO]
Eligibility Step 2B: Because the claims recite an abstract idea, and do not integrate that abstract idea into a practical application, the claims are probed for a specific inventive concept. The judicial exception alone cannot provide that inventive concept or practical application (MPEP 2106.05). Identifying whether the additional elements beyond the abstract idea amount to such an inventive concept requires considering the additional elements individually and in combination to determine if they amount to significantly more than the judicial exception (MPEP 2106.05A i-vi).
The claims do not include any additional elements that are sufficient to amount to significantly more than the judicial exception(s) because of the reasons noted below.
The additional elements recited in claims 1-20 are identified above, and carried over from Step 2A: Prong Two along with their conclusions for analysis at Step 2B. Any additional element or combination of elements that was considered to be insignificant extra-solution activity at Step 2A: Prong Two was re-evaluated at Step 2B, because if such re-evaluation finds that the element is unconventional or otherwise more than what is well-understood, routine, conventional activity in the field, this finding may indicate that the additional element is no longer considered to be insignificant; and all additional elements and combination of elements were evaluated to determine whether any additional elements or combination of elements are other than what is well-understood, routine, conventional activity in the field, or simply append well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception, per MPEP 2106.05(d).
The additional elements of receiving a first plurality of genomic variant call files associated with a first batch of sequencing data (Claim 1), receiving a second plurality of genomic variant call files associated with a second batch of sequencing data (Claim 1), receiving a third plurality of genomic variant call files associated with a third batch of sequencing data (Claim 4), receive one or more genomic variant call files associated with one or more samples (Claim 6), wherein the samples comprise samples from a sequencing run, a sequencing cycle, or multiple sequencing runs (Claim 7), receive a plurality of genomic variant call files, each of the genomic variant call files associated with a respective sample of a plurality of samples (Claim 12), receive an additional genomic variant call file associated with an additional sample (Claim 15) are conventional and part of the data gathering process used in the recited judicial exceptions (see MPEP 2106.05(g)). Evidence for conventionality is shown by is that simply appending well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception, e.g., a claim to an abstract idea requiring no more than a generic computer to perform generic computer functions that are well-understood, routine and conventional activities previously known to the industry, as discussed in Alice Corp., 573 U.S. at 225, 110 USPQ2d at 1984 (see MPEP § 2106.05(d)). As well as iv. Recording, transmitting, and archiving digital images by use of conventional or generic technology in a nascent but well-known environment, without any assertion that the invention reflects an inventive solution to any problem presented by combining a camera and a cellular telephone, TLI Communications, 823 F.3d at 611-12, 118 USPQ2d at 1747. As there is no specific mention on how the data gets acquired in the broadest reasonable interpretation it can be understood to be simply receiving data over a network. As the claim limitation does not recite how the data is acquired under the broadest reasonable interpretation it can simply be received over a network. In addition, sequencing technologies are conventional evidence for conventionality is shown by Metzker et al. (Metzker, M. L. Sequencing Technologies — the next Generation. Nature Reviews Genetics 2010, 11 (1), 31–46.) which is a review of sequencing technologies showing sequencing is a conventional data gathering step.
The additional elements of A computer-implemented method of iterative gVCF genotyping, the method comprising (Claim 1), wherein the method is performed on a local computing system or is distributed across a cloud-computing system (Claim 5), A system, comprising: at least one processor; and a computer readable medium comprising instructions that, when executed by the at least one processor, cause the at least one processor to (Claim 6),A system, comprising: at least one processor; and a computer readable medium comprising instructions that, when executed by the at least one processor, cause the at least one processor to (Claim 12), fail to integrate a judicial exception into a practical application merely reciting the words "apply it" (or an equivalent) with the judicial exception, or merely including instructions to implement an abstract idea on a computer, or merely using a computer as a tool to perform an abstract idea, as discussed in MPEP § 2106.05(f).
Therefore, when taken alone, all additional elements in claims 1-20 do not amount to significantly more than the above-identified judicial exception(s). Even when evaluated as a combination, the additional elements fail to transform the exception(s) into a patent-eligible application of that exception. Thus, claims 1-20 are deemed to not contribute an inventive concept, i.e., amount to significantly more than the judicial exception(s) (MPEP 2106.05(II)).
[Step 2B: NO]
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claims 1-20 are rejected under 35 U.S.C. 103 as being unpatentable over Lin et al. (Lin et al. GLnexus: joint variant calling for large cohort sequencing, arxiv, June 11, 2018) in view of Tan et al. (Tan, A.; Abecasis, G. R.; Kang, H. M. Unified Representation of Genetic Variants. Bioinformatics 2015, 31 (13), 2202–2204.). The italicized text corresponds to the instant claim limitations.
With respect to the limitations of Claims 1, 3, 4, 5, 6, 12, 20 Lin et al. teaches gVCF files are loaded into a database using separate compute nodes for each shard (pg. 4, col. 2, paragraph 1, receiving a first plurality of genomic variant call files associated with a first batch of sequencing data (Claim 1), receive one or more genomic variant call files associated with one or more samples (Claim 6), receive a plurality of genomic variant call files, each of the genomic variant call files associated with a respective sample of a plurality of samples (Claim 12) Lin et al. also teaches to expedite access by genome position, GLnexus loads the gVCF corpus into an ordered key-value database supporting efficient scans of contiguous key ranges. Records from each gVCF file are assigned to a 30-kilobase genome position bin. Bins from each participant are keyed so that all records overlapping a given genome position can be retrieved with a database key range scan. The database values include gVCF records in htslib’s binary format, including genotype likelihoods, and a position search index (pg. 4, col. 2, paragraph 1, generating a first cohort file for the first batch by aggregating data from a subset of fields in each of the first plurality of genomic variant call files (Claim 1) generate, from the one or more genomic variant call files, one or more cohort files and one or more census files (Claim 6) Lin et al. also teaches example abbreviated gVCF records for four participants, giving genome position, reference and alternate alleles, and initial called genotypes. Gray records indicate sequencing coverage for regions with no apparent variation (pg. 2, Figure 1 Caption, generating a first census file that comprises variant summary statistics and hom-ref blocks of the first batch (Claim 1) Lin et al. also teaches distributed joint calling cloud workflow, illustrated with two “shards” of the cohort. gVCF files are loaded into a database using separate compute nodes for each shard. Alleles are simultaneously recorded and sent to a central process for unification into pVCF sites. These sites are genotyped across the cohort shards by revisiting records stored in the gVCF database, producing pVCF shards with corresponding rows, suitable for loading into a parallel analytics environment such as Apache Hadoop or Spark. N pVCF shards from N input shards each genotyped against the same global site list. Figure 2 visualizes this process. Multiple pVCF shards are produced in parallel, one per cohort shard. GLnexus combines scalable joint calling algorithms with a persistent database that grows efficiently as additional participants are sequenced. GLnexus combines scalable joint calling algorithms with a persistent database that grows efficiently as additional participants are sequenced. (pg. 4, col. 1, paragraph 1, receiving a second plurality of genomic variant call files associated with a second batch of sequencing data; generating a second cohort file for the second batch by aggregating data from the subset of fields in each of the second plurality of genomic variant call files; generating a second census file that comprises variant summary statistics and hom-ref blocks of the second batch; generating a global census file by aggregating the first census file and the second census file, wherein the global census file comprises census data from batches of samples received from sequencing devices at different sites (Claim 1) generating a first multi-sample variant call file for the first batch using the first cohort file, the first census file, and the global census file; and generating a second multi-sample variant call file for the second batch using the second cohort file, the second census file, and the global census file (Claim 1) wherein the first plurality of genomic variant call files associated with the first batch are split into shards of equal size, and wherein each shard is processed using one of a plurality of computation nodes (Claim 3) receiving a third plurality of genomic variant call files associated with a third batch of sequencing data; generating a third cohort file for the third batch by aggregating data from the subset of fields in each of the third plurality of genomic variant call files; generating a third census file that comprises variant summary statistics and hom-ref blocks of the third batch; updating the global census file by aggregating the third census file with the global census file; and generating a third multi-sample variant call file for the third batch using the third cohort file, the third census file, and the updated global census file (Claim 4, GLnexus can add N plurality of genomic variant files from new sequencing data) wherein the method is performed on a local computing system or is distributed across a cloud-computing system (Claim 5) aggregate the one or more census files into a global census file, wherein the global census file comprises census data from batches of samples received from sequencing devices at different sites; generate, based on the global census file, the one or more cohort files, and the one or more census files, at least one multi-sample variant call file; and store the multi-sample variant call file in the memory. (Claim 6), wherein the mapping for each of the plurality of alternate alleles is stored in site information in a census file (Claim 20))
With respect to the limitations of Claims 2, Lin et al. teaches VCF can present genotypes for an entire cohort, in a 2-D matrix of variant sites and study participants, filled with the diploid genotypes and quality-control (QC) measures – referred to as a Project VCF (pVCF). The pVCF's matrix format facilitates downstream calculation of allele frequencies and association testing statistics in the cohort or any phenotype-defined subsets of it. This is an example of genome wide sequencing analysis (pg. 1, col. 2, paragraph 1) and Genome-wide association studies of multiple separate cohorts can be aggregated through meta-analysis of summary statistics (pg. 7, col. 2, paragraph 5, performing a genome-wide sequencing analysis using one or more of the first multi- sample variant call file or the second multi-sample variant call file (Claim 2)
With respect to the limitations of Claims 7, Lin et al. teaches genome-wide association studies of multiple separate cohorts can be aggregated through meta-analysis of summary statistics, with much less risk to the participants’ genetic privacy compared to sharing full genotypes. This increases discovery power through larger N than otherwise feasible owing to cost, recruitment challenges, and data-sharing policy restrictions. These meta-analysis techniques, which rely on genotype data summaries such as site covariance to control potential confounders, may be challenging to fully extend from microarray- to sequencing-based studies, which inherently ascertain different sites in different cohorts, among other distinctive batch effects. GLnexus’ sharding scheme harmonizes the representation of all discovered variants through exchange of similar summary information between cohort subsets on different compute nodes. Although presently implemented to scale within one datacenter, we plan to extend this to harmonize sequenced cohorts held in separate repositories, without centralizing individual-level genotypes, to facilitate federated association meta-analysis. (pg. 7, col. 2, paragraph 5 – pg. 8, col. 1, paragraph 1, wherein the samples comprise samples from a sequencing run, a sequencing cycle, or multiple sequencing runs (Claim 7)
With respect to the limitations of Claims 8, 9, 10, Lin et al. teaches teaches to expedite access by genome position, GLnexus loads the gVCF corpus into an ordered key-value database supporting efficient scans of contiguous key ranges. Records from each gVCF file are assigned to a 30-kilobase genome position bin. Bins from each participant are keyed so that all records overlapping a given genome position can be retrieved with a database key range scan. The database values include gVCF records in htslib’s binary format, including genotype likelihoods, and a position search index. Amd distributed joint calling cloud workflow, illustrated with two “shards” of the cohort. gVCF files are loaded into a database using separate compute nodes for each shard (pg. 4, Figure 2 caption, wherein the instructions are further configured to cause the at least one processor to perform parallel processing using multiple compute nodes (Claim 8), wherein the instructions, when executed by the at least one processor, further cause the processor to: perform parallelization and multithreading by regions of sequence data (Claim 9), wherein at least two compute nodes perform at least two levels of parallelization for processing, aggregating, or generating data for a corresponding region of the sequence data, wherein each compute node processes a specific region (Claim 10) wherein the cohort files and the census files in a region are bit compressed and serialized (Claim 11)
With respect to the limitations of Claims 12, Lin et al. teaches abbreviated gVCF records for four participants, giving genome position, reference and alternate alleles, and initial called genotypes. Gray records indicate sequencing coverage for regions with no apparent variation (pg. 2, Figure 1 caption,
identify, using reference alternate genotype (RAGT) statistics in the plurality of genomic variant call files, a plurality of reference alleles and a plurality of alternate alleles associated with the plurality of samples (Claim 12) Lin et al. also teaches to formulate a genotype prior with Hardy Weinberg equilibrium genotype frequencies implied by the empirical allele frequencies estimated from the gVCF cohort.(pg. 3, col. 2, paragraph 2, count the instances of each of the plurality of reference alleles and each of the plurality of alternate alleles (Claim 12) Lin et al. also teaches joint calling a set of gVCFs to pVCF involves, first, deriving a set of "unified" variant sites representing all discovered alleles passing QC thresholds (also shown in Figure 1) (pg. 2, col. 2, paragraph 2, select a normalized reference allele from the plurality of reference alleles, wherein the longest reference allele is selected as the normalized reference allele (Claim 12), Lin et al. also teaches these sites are genotyped across the cohort shards by revisiting records stored in the gVCF database, producing pVCF shards with corresponding rows (pg. 4, Figure 2 Caption, and generate a multi-sample variant call file using the normalized reference alleles and the normalized alternate alleles (Claim 12)
With respect to the limitations of Claims 13, Lin et al. teaches input alleles, genotype calls and (not shown) QC measures from the input gVCF records must be “projected” onto the pVCF site representation (pg. 2, Figure 1 Caption, wherein the instructions further cause the at least one processor to generate a normalized representation of each sample using the normalized reference allele such that each of the plurality of alternate alleles are indexed using the normalized reference allele (Claim 13)
With respect to the limitations of Claims 15, Lin et al. teaches GLnexus combines scalable joint calling algorithms with a persistent database for querying the gVCF data corpus that grows efficiently as additional participants are sequenced. It is designed to receive additional files and identify reference alleles in those samples. It will then update the previous data based on the new addition (pg. 2, col. 1, paragraph 1, receive an additional genomic variant call file associated with an additional sample; identify a reference allele and one or more alternate alleles associated with the additional sample; and update the normalized representation to include the reference allele and the one or more alternate alleles associated with the additional sample (Claim 15))
With respect to the limitations of Claims 16, Lin et al. teaches schematic view of the alternate alleles seen across the four gVCF inputs; they cluster into two sites except for a spanning deletion allele. (C) Example pVCF representation for these variants, with two multiallelic sites and a third “monoallelic” site representing the deletion allele which could not be unified into the multiallelic sites without introducing phase constraints artificially. When new shorter-reference alleles “cluster” into an existing unified site they must be brought into the multi-allelic representation by being extended to the site’s full reference range, then incorporated into the site’s allele table which directly mirrors the claim (pg. 2, Figure 1 caption, determine that the length of the reference allele is shorter than the normalized reference allele; extend the reference allele and the one or more alternate alleles to correspond to the normalized reference allele; and reorder the plurality of reference alleles and the plurality of alternate alleles to include the extended reference allele and the one or more extended alternate alleles (Claim 16)
With respect to the limitations of Claims 18, Lin et al. teaches input alleles, genotype calls and (not shown) QC measures from the input gVCF records must be “projected” onto the pVCF site representation. Projected inherently includes reindexing/ reordering each sample’s genotype call against the new normalized site allele ordering (pg. 2, Figure 1 Caption, wherein the instructions further cause the at least one processor to reorder the genotype of each sample based on the normalized reference allele and the normalized representations (Claim 18))
With respect to the limitations of Claims 18, Lin et al. teaches the pertinent gVCF alleles, genotypes, likelihoods, and QC measures are "projected" onto the unified sites, including reference homozygous calls where applicable, sometimes using multiple gVCF records to inform one pVCF matrix entry and vice-versa (wherein the instructions further cause the at least one processor to generate a mapping for each of the plurality of alternate alleles based on the normalized reference allele (Claim 19)
Lin et al. does not explicitly teach
A computer-implemented method of iterative gVCF genotyping, the method comprising: (Claim 1)
A system, comprising: at least one processor; and a computer readable medium comprising instructions that, when executed by the at least one processor, cause the at least one processor to (Claim 6)
A system, comprising: at least one processor; and a computer readable medium comprising instructions that, when executed by the at least one processor, cause the at least one processor to (Claim 12)
normalize the other reference alleles of the plurality of reference alleles by extending the other reference alleles to correspond to the normalized reference allele; normalize the plurality of alternate alleles by extending each alternate allele the same amount that the respective corresponding reference allele was extended; (Claim 12)
wherein the other reference alleles are extended by adding a respective number of bases to correspond to the normalized reference allele (Claim 14))
determine that the length of the reference allele is longer than the normalized reference allele; select the reference allele as an updated normalized reference allele; normalize the plurality of reference alleles and the plurality of alternate alleles by extending to correspond to a length of the updated normalized reference allele; and reorder the plurality of reference alleles and the plurality of alternate alleles to include the updated normalized reference allele and the one or more extended alternate alleles (Claim 17)
With respect to the limitations of Claims 1, 6, 12, Tan et al. teaches running the program on a computer as they provide source code for their application and ran their application on a computer (abstract. A computer-implemented method of iterative gVCF genotyping, the method comprising: (Claim 1), A system, comprising: at least one processor; and a computer readable medium comprising instructions that, when executed by the at least one processor, cause the at least one processor to (Claim 6), A system, comprising: at least one processor; and a computer readable medium comprising instructions that, when executed by the at least one processor, cause the at least one processor to (Claim 12))
With respect to the limitations of Claims 12, 14, Tan et al. teaches a normalization algorithm that extents all alleles by 1 nucleotide to the left is any allele has a length of zero (pg. 2203, Algorithm 1 Normalize a VCF entry Table, normalize the other reference alleles of the plurality of reference alleles by extending the other reference alleles to correspond to the normalized reference allele; normalize the plurality of alternate alleles by extending each alternate allele the same amount that the respective corresponding reference allele was extended; (Claim 12), wherein the other reference alleles are extended by adding a respective number of bases to correspond to the normalized reference allele (Claim 14))
With respect to the limitations of Claims 17, Tan et al. teaches A VCF entry is normalized if and only if it is left aligned and parsimonious. A VCF entry is left aligned if and only if its base position is smallest among all potential VCF entries having the same allele length and representing the same variant. A VCF entry is parsimonious if and only if the entry has the shortest allele length among all VCF entries representing the same variant. When a new variant arrives that whose reference span exceeds the existing one, renormalization the entry requires selecting a common allele-length representation and extending all other alleles to match. (pg. 2202, col. 2, paragraph 3, determine that the length of the reference allele is longer than the normalized reference allele; select the reference allele as an updated normalized reference allele; normalize the plurality of reference alleles and the plurality of alternate alleles by extending to correspond to a length of the updated normalized reference allele; and reorder the plurality of reference alleles and the plurality of alternate alleles to include the updated normalized reference allele and the one or more extended alternate alleles (Claim 17)
A person having ordinary skill in the art would be motivated to combine Lin et al. with Tan et al. as both are in the exact same field of endeavor of population-scale joint variant calling from gVCF files, which is the exact field of the application. Each reference addresses the same problem of producing accurate multi-sample VCFs from large numbers of gVCFs at scale. A person of ordinary skill in the art would naturally combine the teachings to address the different sub-problems. Each component works individually so when combined without changing the function there is a reasonable expectation of success.
Conclusion
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/C.H.B./Examiner, Art Unit 1687
/Karlheinz R. Skowronek/Supervisory Patent Examiner, Art Unit 1687
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