DETAILED ACTION
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 .
Claim Status
Claims 1-6 are currently pending and under examination herein.
Claims 1-6 are rejected.
Priority
Acknowledgment is made of applicant’s claim for foreign priority under 35 U.S.C. 119 (a)-(d). The certified copy has been filed in parent Application No. KR10-2022-0034590, filed on 03/21/2022.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 7/28/2023 are in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner. A signed copy of a list of references cited from each IDS is included in this Office Action.
Drawings
The drawings filed on 3/09/2023 are accepted.
Specification
The specification filed on 3/09/2023 is accepted.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claim 1-6 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claim 1 recites the limitation "the following Equation I" in line 11-12. There is insufficient antecedent basis for this limitation in the claim. The claim limitation does not refer to an earlier recitation but rather a later recitation and can be amended to refer to an earlier recitation to overcome the rejection. Appropriate correction is required.
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 1-6 are rejected under 35 U.S.C 101 because the claimed invention is directed to an abstract idea and a natural phenomenon without significantly more.
In accordance with MPEP 2106, claims found to recite statutory subject matter (Step 1: YES) are then analyzed to determine if the claims recite any concepts that equate to an abstract idea, law of nature, or natural phenomenon (Step 2A, Prong 1).
Claim 1 recites a method comprising the steps of: obtaining an LLRc value according to the following Equation I by applying an error rate corresponding to the HQS and determining the presence or absence of a false positive variant from the LLRc value using Equation I wherein r denotes read, N denotes total number of reads, S denotes family size, f denotes variant allele frequency, and e denotes error rate.
Claim 4 recites the method according to claim 1, wherein the family size is 2 to 30.
Claim 5 recites the method according to claim 1, wherein the error rate includes all of a context error rate at a specific family size, a nucleotide error rate calculated in an error correction process, and a read error rate calculated in a mapping process.
Claim 6 recites the method according to claim 1, wherein step e) of determining the presence or absence of the false positive variant comprises: obtaining a weighted LLR value by calculating an LLR value for SSCS and an LLR value for DCS; and determining that, when a cut-off value set using a precision-recall curve from the weighted LLR value is 50 or more, the variant in the nucleic acid fragment containing the candidate variant is false positive.
The limitations of obtaining an LLRc value according to the following Equation I by applying an error rate corresponding to the HQS and determining the presence or absence of a false positive variant from the LLRc value using Equation I wherein r denotes read, N denotes total number of reads, S denotes family size, f denotes variant allele frequency, and e denotes error rate; the error rate includes all of a context error rate at a specific family size, a nucleotide error rate calculated in an error correction process, and a read error rate calculated in a mapping process; and step e) of determining the presence or absence of the false positive variant comprises: obtaining a weighted LLR value by calculating an LLR value for SSCS and an LLR value for DCS; and determining that, when a cut-off value set using a precision-recall curve from the weighted LLR value is 50 or more, the variant in the nucleic acid fragment containing the candidate variant is false positive are verbal equivalents of a mathematical calculations and falls under the “mathematical concept” grouping of ideas.
The limitations of the method according to claim 1, wherein the family size is 2 to 30 merely further limits the abstract idea. As such, claims 1-6 recite abstract ideas.
Claims found to recite a judicial exception under Step 2A, Prong 1 are then further analyzed to determine if the claims as a whole integrate the recited judicial exception into a practical application or not (Step 2A, Prong 2). This judicial exception is not integrated into a practical application because the claims do not recite additional elements that reflects an improvement to technology or applies or uses the recited judicial exception in some other meaningful way. Rather, the instant claims recite additional elements that amount to mere instructions to implement the abstract idea in a generic computing environment. Specifically, the claims recite the following additional elements:
Claim 1 recites a method of removing false positive variants in nucleic acid sequencing, the method comprising steps of: a) extracting a nucleic acid fragment containing a candidate variant from a target sample; b) adding a unique molecular identifier (UMI) to an end of the extracted nucleic acid fragment; c) producing a high-quality unique sequence (HQS) by amplifying the nucleic acid fragment to which the UMI has been added.
Claim 2 recites the method according to claim 1, wherein the candidate variant is at least one selected from the group consisting of single-nucleotide variation, nucleotide insertion, and nucleotide deletion.
Claim 3 recites the method according to claim 1, wherein the HQS in step c) is a single-strand consensus sequence (SSCS) or a duplex consensus sequence (DCS).
The limitations of removing false positive variants in nucleic acid sequencing, the method comprising steps of: a) extracting a nucleic acid fragment containing a candidate variant from a target sample; b) adding a unique molecular identifier (UMI) to an end of the extracted nucleic acid fragment; c) producing a high-quality unique sequence (HQS) by amplifying the nucleic acid fragment to which the UMI has been added comprise insignificant extra-solution activity, namely, data gathering or data manipulation (see MPEP 2106.05(g)). Of note, the courts have ruled in Electric Power Group, LLC V. Alstom S.A., 830 F.3d 1350, 1354-55, 119 USPQ2d 1739, 1742 (Fed. Cir. 2016) that the collection, analysis, and display of data are considered insignificant extra-solution activity and does not integrate the judicial exception into a practical application.
The limitations of the candidate variant is at least one selected from the group consisting of single-nucleotide variation, nucleotide insertion, and nucleotide deletion and the HQS in step c) is a single-strand consensus sequence (SSCS) or a duplex consensus sequence (DCS) merely further limit the insignificant extra-solution activity or data collection/processing step. As such, claims 1-6 do not integrate a judicial exception into a practical application.
Claims found to be directed to a judicial exception are then further evaluated to determine if the claims recite an inventive concept that provides significantly more than the judicial exception itself (Step 2B). The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the claims recite additional elements that amount to mere instructions to implement the abstract idea in a generic field-of-use and/or technological environment. The instant claims recite the following additional elements:
Claim 1 recites a method of removing false positive variants in nucleic acid sequencing, the method comprising steps of: a) extracting a nucleic acid fragment containing a candidate variant from a target sample; b) adding a unique molecular identifier (UMI) to an end of the extracted nucleic acid fragment; c) producing a high-quality unique sequence (HQS) by amplifying the nucleic acid fragment to which the UMI has been added.
Claim 2 recites the method according to claim 1, wherein the candidate variant is at least one selected from the group consisting of single-nucleotide variation, nucleotide insertion, and nucleotide deletion.
Claim 3 recites the method according to claim 1, wherein the HQS in step c) is a single-strand consensus sequence (SSCS) or a duplex consensus sequence (DCS).
The limitations of extracting a nucleic acid fragment containing a candidate variant from a target sample; adding a unique molecular identifier (UMI) to an end of the extracted nucleic acid fragment; wherein the candidate variant is at least one selected from the group consisting of single-nucleotide variation, nucleotide insertion, and nucleotide deletion; and the HQS in step c) is a single-strand consensus sequence (SSCS) or a duplex consensus sequence (DCS) equate to well-understood, conventional, and routine activity as evidenced by Wang et al. (State of the art methods often employ UMIs for error suppression in “Abstract”; analysis of sequenced variants with UMI identifiers and individual BAM files of SSCS and DCS with enumeration of false positives described on page 4).
The limitations of producing a high-quality unique sequence (HQS) by amplifying the nucleic acid fragment to which the UMI has been added amount to a well-understood, conventional, and routine laboratory technique (see Using polymerase chain reaction to amplify and detect DNA, Genetic Techs. Ltd. v. Merial LLC, 818 F.3d 1369, 1376, 118 USPQ2d 1541, 1546 (Fed. Cir. 2016); Ariosa Diagnostics, Inc. v. Sequenom, Inc., 788 F.3d 1371, 1377, 115 USPQ2d 1152, 1157 (Fed. Cir. 2015); see also Amplifying and sequencing nucleic acid sequences, University of Utah Research Foundation v. Ambry Genetics, 774 F.3d 755, 764, 113 USPQ2d 1241, 1247 (Fed. Cir. 2014) in MPEP 2106.05(d)).
There are no additional elements that comprise an inventive concept when considered individually or as an ordered combination that transforms the claimed judicial exception into a patent-eligible application of the judicial exception. Therefore, the claims do not amount to significantly more than the judicial exception itself (Step 2B: No). As such, claims 1-6 are not patent eligible.
Claim Rejections - 35 USC § 103
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.
The present rejection(s) reference specific passages from cited prior art. However,
Applicant is advised that the rejections are based on the entirety of each cited prior art. That is,
each cited prior art reference “must be considered in its entirety”. (See MPEP 2141.02(VI))
Therefore, Applicant is advised to review all portions of the cited prior art if traversing a
rejection based on the cited prior art.
Claims 1-4 is/are rejected under 35 U.S.C. 103 as being unpatentable over Wang et al. (High efficiency error suppression for accurate detection of low-frequency variants, Nucleic Acids Research, Volume 47, Issue 15, 05 September 2019, Page e87) as filed in the IDS on 3/21/2022 in view of Ni et al. (Improvement in detection of minor alleles in next generation sequencing by base quality recalibration. BMC Genomics 17, 139 (2016)).
Regarding claim 1, Wang teaches:
A method of removing false positive variants in nucleic acid sequencing (method of singleton correction incorporation in existing UMI-based error suppression workflows in “Abstract”; see page 6 in Fig. 1 for singleton removal), the method comprising steps of:
a) extracting a nucleic acid fragment containing a candidate variant from a target sample (extraction explicitly performed in “Materials and Methods” details, see “Targeted panel design” in Col. 1 on page 2);
b) adding a unique molecular identifier (UMI) to an end of the extracted nucleic acid fragment (reads were condensed into single strand consensus sequences and assigned UMIs; see “Barcodes used in UMIs” in Col.1 on page 3);
c) producing a high-quality unique sequence (HQS) by amplifying the nucleic acid fragment to which the UMI has been added in (ligated fragments amplified on page 2 Col. 2 under “Next-generation sequencing library preparation”; reads are collapsed to form SSCS which is equivalent to HQS in “Analysis of single strand UMIs” in Col. 1 on page 3);
Wang does not teach obtaining an LLRc value according to the following Equation I by applying an error rate corresponding to the HQS; and determining the presence or absence of a false positive variant from the LLRc value using Equation I, wherein r denotes read, N denotes total number of reads, S denotes family size, f denotes variant allele frequency, and e denotes error rate. Ni teaches calculating a likelihood ratio comparing a variant hypothesis against an error/no-variant hypothesis wherein the likelihood incorporates variant allele frequency and sequencing error probabilities (see Logarithm Likelihood Ratio as defined under “Methods” which will end up being LLR = log (L(f̂)/L(0)) wherein L(f) = ∏lj = 1[(1 − f)ε j + f(1 − ε j )]∏kj = 1[(1 − f)(1 − ε j ) + fε j ] such that ε j is the error; page 9) The Examiner notes that the logarithmic base and natural logarithm can be used interchangeably for the purposes of scale as log is base 10 and ln is base e, wherein ln is a subset of a logarithmic formula. In addition, taking the natural log of the formula of the product notation (∏) transforms the formula into a summation (∑) via logarithmic properties as evidenced by Western Oregon University (see attached formula sheet). Furthermore, although Ni uses the generic epsilon term ε j to account for the error, Ni is silent as to the incorporation of family size in the computation of the error value. However, Wang already includes SSCS family size metadata in his pipeline (family size explicitly used in processing wherein SSCS is generated from a family size greater than 2 and error suppression depends on how many reads support a molecule; see “Analysis of single strand UMIs” on page 3). Therefore, it would have been obvious before the effective filing date of the claimed invention to incorporate Ni’s variant likelihood ratio with Wang’s false positive variants removal method in order to integrate error correction tools into the existing next generation sequencing pipelines to improve the accuracies in base quality as recited by Ni (see “Background” on pages 1-2). This could be accomplished with a reasonable expectation of success as both are in the same field of endeavor in error calculation for the detection of false variants.
Regarding claim 2, Wang as modified teaches:
The method according to claim 1, wherein the candidate variant is at least one selected from the group consisting of single-nucleotide variation, nucleotide insertion, and nucleotide deletion (Files detect single nucleotide variants in Col. 2 on page 4 under “Analysis of Patient Samples”).
Regarding claim 3, Wang as modified teaches:
The method according to claim 1, wherein the HQS in step c) is a single-strand consensus sequence (SSCS) or a duplex consensus sequence (DCS) (reads are collapsed to form SSCS which is equivalent to HQS under “Analysis of single strand UMIs” in Col. 1 on page 3).
Regarding claim 4, Wang as modified teaches:
The method according to claim 1, wherein the family size is 2 to 30 (family size explicitly used in processing wherein SSCS is generated from a family size greater than 2 and error suppression depends on how many reads support a molecule; see “Analysis of single strand UMIs” on page 3).
Claim(s) 5 is/are rejected under 35 U.S.C. 103 as being unpatentable over Wang et al. (High efficiency error suppression for accurate detection of low-frequency variants, Nucleic Acids Research, Volume 47, Issue 15, 05 September 2019, Page e87,) as filed in the IDS on 3/21/2022 and Ni et al. (Improvement in detection of minor alleles in next generation sequencing by base quality recalibration. BMC Genomics 17, 139 (2016)), as applied to claim 1 above, and further in view of Xu et al. (smCounter2: an accurate low-frequency variant caller for targeted sequencing data with unique molecular identifiers, Bioinformatics, Volume 35, Issue 8, April 2019).
Regarding claim 5,
Wang and Ni teach the claimed invention substantially as stated above.
Although Wang as modified does mention generally the incorporation of nucleotide error rates, he does not explicitly teach the method according to claim 1, wherein the error rate includes all of a context error rate at a specific family size, a nucleotide error rate calculated in an error correction process, and a read error rate calculated in a mapping process. Xu teaches the explicit decomposition of all error sources (misincorporation which is a nucleotide error, oxidation damage which is a context error, and misalignment which is a mapping error in “2.2 Estimation of background error rates” on page 1301). Therefore, it would have been obvious before the effective filing date of the claimed invention to incorporate Xu’s recitation of common background errors with Wang’s false positive variants removal method in order to integrate error correction tools into the existing next generation sequencing pipelines to improve overall accuracy using the smCounter2 tool as evidenced by Xu (see “Abstract”; page 1299). This could be accomplished with a reasonable expectation of success as both are in the same field of endeavor in error correction using unique molecular identifiers.
Claim(s) 6 is/are rejected under 35 U.S.C. 103 as being unpatentable over Wang et al. (High efficiency error suppression for accurate detection of low-frequency variants, Nucleic Acids Research, Volume 47, Issue 15, 05 September 2019, Page e87,) as filed in the IDS on 3/21/2022 and Ni et al. (Improvement in detection of minor alleles in next generation sequencing by base quality recalibration. BMC Genomics 17, 139 (2016)), as applied to claim 1 above, and in view of Xu (smCounter2: an accurate low-frequency variant caller for targeted sequencing data with unique molecular identifiers, Bioinformatics, Volume 35, Issue 8, April 2019) further in view of Gezsi et al. (VariantMetaCaller: automated fusion of variant calling pipelines for quantitative, precision-based filtering. BMC Genomics. 2015 Oct 28;16:875.)
Regarding claim 6,
Wang as modified by Ni teaches the method according to claim 1, wherein step e) of determining the presence or absence of the false positive variant comprises: obtaining a weighted LLR value by calculating an LLR value for SSCS and an LLR value for DCS (reads are collapsed to form SSCS and SSCS condensed to form DCS on page 3 under “Analysis of duplex barcodes” in Col. 2 and subsequently used throughout the entire pipeline for error; values can be calculated using the formula provided by Ni). Wang does not teach determining that, when a cut-off value set using a precision-recall curve from the weighted LLR value is 50 or more, the variant in the nucleic acid fragment containing the candidate variant is false positive. Xu teaches selecting variant calling thresholds based on a target false positive rate which is implemented via P-value likelihood cutoffs and further evaluated (false positive thresholding described on page 1302; log-likelihood explicitly used in Xu’s method; see Fig. 3b and page 1304, and specificity-sensitivity curves on.) Although Xu teaches p-value thresholding and has the necessary parameters to construct a precision-recall curve, he does not explicitly teach when a cut-off value set using a precision-recall curve from the weighted LLR value is 50 or more, the variant in the nucleic acid fragment containing the candidate variant is false positive. Gezsi explicitly teaches selecting variant-calling thresholds based on precision-recall analysis and using score-based filtering to determine a threshold for variant classification (VariantMetaCaller supports a quantitative, precision based filtering of variants under wider conditions where the probabilities like likelihood can be used to estimate precision which can be translated to the number of true called variants and the number of false calls using given thresholds; see page 1; precision-recall curves shown in Fig. 4). Therefore, it would have been obvious before the effective filing date of the claimed invention to incorporate Geszi’s filtering program and Xu’s p-value thresholding with Wang as modified’s false positive variants removal method in order to integrate error correction tools into the existing next generation sequencing pipelines to increase significantly higher sensitivity and precision than individual variant callers as recited by Gezsi (page 1; in “Abstract” under “Results”) and Xu (page 1209 in “Abstract”; improvements to overall accuracy compared to existing models due to incorporation of error correction). This could be accomplished with a reasonable expectation of success as Geszi’s and Xu’s statistical methods operate in the same field of endeavor of bioinformatics in relation to variant error correction.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Grant et al. discusses scanning for occurrences of a given motif in a protein sequence (FIMO: scanning for occurrences of a given motif, Bioinformatics, Volume 27, Issue 7, April 2011, Pages 1017–1018).
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/P.N./Examiner, Art Unit 1685
/OLIVIA M. WISE/Supervisory Patent Examiner, Art Unit 1685
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