# US 2025/0095784 A1 · Automated nucleic acid repeat count calling methods > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 2025/0095784 A1 - Document ID: US20250095784A1 - Status: Published application - Kind: A1 - Application number: 18/781,847 - Filed: 2024-07-23 - Published: 2025-03-20 - Earliest claimed: 2013-11-13 - Assignees: Myriad Women's Health, Inc. - Applicants: Myriad Women's Health, Inc. - Inventors: A. Scott Patterson; Imran S. Haque; Eric A. Evans; Clement Chu - Web page: https://patentgrep.com/patent/US20250095784A1 ## CPC - G16B 40/10: Signal processing, e.g. from mass spectrometry [MS] or from PCR - G16B 20/00: ICT specially adapted for functional genomics or proteomics, e.g. genotype-phenotype associations - G16B 20/20: Allele or variant detection, e.g. single nucleotide polymorphism [SNP] detection - G16B 30/00: ICT specially adapted for sequence analysis involving nucleotides or amino acids - G16B: BIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY ## Abstract The present disclosure relates to processes for determining the number of nucleic acid repeats in a DNA fragment comprising a nucleic acid repeat region. One example method may include receiving DNA size and abundance data generated by resolving DNA amplification products. A set of low-pass data may be generated by applying a low-pass filter to the DNA size and abundance data and a set of band-pass data may be generated by applying a band-pass filter to the DNA size and abundance data. A peak of the DNA size and abundance data representative of a number of nucleic acid repeats in the DNA may be identified based on peaks identified from the low-pass data and the band-pass data. ## Claims ### Claim 1 A computer-implemented method for determining the number of CGG repeats in a DNA comprising a CGG-rich region, the method comprising: a) receiving, by one or more processors, DNA size and abundance data of DNA amplification products generated from the DNA comprising the CGG-rich region by using a primer set comprising a first primer recognizing the CGG-rich region and a second primer recognizing a region outside of the CGG-rich region; b) generating, by the one or more processors, a set of sample data by sampling the DNA size and abundance data at a sampling frequency; c) generating, by the one or more processors, a set of low-pass data by applying a low-pass filter to the set of sample data; d) generating, by the one or more processors, a set of band-pass data by applying a band-pass filter to the set of sample data; e) identifying, by the one or more processors, one or more peaks in the low-pass data; f) identifying, by the one or more processors, one or more peaks in the band-pass data; and g) identifying, by the one or more processors, a final peak representing a number of CGG repeats in the CGG-rich region based on the one or more peaks in the low-pass data and the one or more peaks in the band-pass data. ### Claim 2 (depends on 1) The computer-implemented method of claim 1, further comprising resolving the DNA amplification products to generate the DNA size and abundance data prior to step a). ### Claim 3 (depends on 2) The computer-implemented method of claim 2, wherein the resolving is carried out by capillary electrophoresis. ### Claim 4 (depends on 1) The computer-implemented method of claim 1, further comprising converting, by the one or more processors, the DNA size and abundance data from a time domain to a base-pair length domain prior to step b). ### Claim 5 (depends on 4) The computer-implemented method of claim 4, wherein a DNA ladder is used to convert the DNA size and abundance data from the time domain to the base-pair length domain. ### Claim 6 (depends on 1) The computer-implemented method of claim 1, wherein the sampling frequency is equal to four samples per base-pair. ### Claim 7 (depends on 1) The computer-implemented method of claim 1, wherein the band-pass filter has a low cutoff frequency of 2/13 multiplied by the sampling frequency and a high cutoff frequency of 2/11 multiplied by the sampling frequency. ### Claim 8 (depends on 1) The computer-implemented method of claim 1, wherein the low-pass filter has a cutoff frequency of 1.0*10−5 multiplied by the sampling frequency. ### Claim 9 (depends on 1) The computer-implemented method of claim 1, wherein the low-pass filter and the band-pass filter are zero-phase finite impulse response (FIR) filters implemented using a Hamming window. ### Claim 10 (depends on 1) The computer-implemented method of claim 1, wherein generating the set of sample data by sampling the DNA size and abundance data at the sampling frequency comprises: generating a linear interpolation of the DNA size and abundance data; and sampling the linear interpolation of the DNA size and abundance data at the sampling frequency. ### Claim 11 (depends on 1) The computer-implemented method of claim 1, wherein the set of sample data comprises a signal representing a combination of a CGG series of the CGG-rich region and a full-length amplicon of the DNA comprising the CGG-rich region, the set of band-pass data comprises a signal representing the CGG series of the CGG-rich, and the set of low-pass data comprises a signal representing the full-length amplicon of the DNA comprising the CGG-rich region. ### Claim 12 (depends on 1) The computer-implemented method of claim 1, wherein identifying the final peak representing the number of CGG repeats in the DNA comprising the CGG-rich region comprises: removing peaks from the one or more peaks in the low-pass data having a width less than 4.5 base-pairs and a height less than a threshold value; removing peaks from the one or more peaks in the band-pass data having a width less than 4.5 base-pairs and a height less than the threshold value; removing peaks from the one or more peaks in the band-pass data having a height less than a height of an adjacent peak having a larger base-pair length; in response to a peak of the one or more peaks in the low-pass data having a height less than a height of a peak of the one or more peaks in the band-pass data that is within 3 base-pairs of the peak of the one or more peaks in the low-pass data, setting a center of the peak of the one or more peaks in the low-pass data to a center of the peak of the one or more peaks in the band-pass data, and setting a boundary of the peak of the one or more peaks in the low-pass data to a union of the peak of the one or more peaks in the low-pass data and the peak of the one or more peaks in the band-pass data; merging peaks of the one or more peaks in the low-pass data and the one or more peaks in the band-pass data that have base-pair lengths greater than 165 base-pairs and that are within 30 base-pairs of each other; and merging peaks of the one or more peaks in the low-pass data and the one or more peaks in the band-pass data that are within 15 base-pairs and that are more than a factor of 2 different in height, wherein a remaining peak of the one or more peaks in the low-pass data is the final peak. ### Claim 13 (depends on 1) The computer-implemented method of claim 1, wherein the DNA comprising a CGG-rich region is the 5′-UTR of the fragile X mental retardation 1 gene (FMR1). ### Claim 14 (depends on 1) The computer-implemented method of claim 1, wherein the DNA comprising a CGG-rich region is the 5′-UTR of the fragile X mental retardation 2 gene (FMR2). ### Claim 15 (depends on 1) The computer-implemented method of claim 1, wherein the first primer comprises at least four CGG or CCG repeats. ### Claim 16 (depends on 1) The computer-implemented method of claim 1, wherein the primer set further comprises a third primer recognizing a region outside of the CGG-rich region that is on the opposite side as the region recognized by the second primer. ### Claim 17 A computer-implemented method for determining a genotype associated with Fragile X syndrome in an individual, the method comprising: a) performing DNA amplification reaction using a primer set comprising a first primer recognizing the CGG-rich region on the 5′ UTR of the FMR1 gene and a second primer recognizing a region outside of the CGG-rich region on the 5′ UTR of the FMR1 gene; b) resolving the DNA amplification products to obtain DNA size and abundance data; c) applying a low-pass filter and a band-pass filter to the DNA size and abundance data to identify a peak representing a number of CGG repeats in the CGG-rich region on the 5′ UTR of the FMR1 gene; and d) determining the genotype of the individual based on the identified peak. ### Claim 18 (depends on 17) The computer-implemented method of claim 17, wherein resolving is carried out by capillary electrophoresis. ### Claim 19 (depends on 17) The computer-implemented method of claim 17, further comprising converting, by the one or more processors, the DNA size and abundance data from a time domain to a base-pair length domain prior to step c). ### Claim 20 (depends on 19) The computer-implemented method of claim 19, wherein a DNA ladder is used to convert the DNA size and abundance data from the time domain to the base-pair length domain. ### Claim 21 (depends on 17) The computer-implemented method of claim 17, wherein the method further comprises sampling the DNA size and abundance data at a sampling frequency, and wherein applying the low-pass filter and the band-pass filter to the DNA size and abundance data comprises applying the low-pass filter and the band-pass filter to the sampled DNA size and abundance data. ### Claim 22 (depends on 21) The computer-implemented method of claim 21, wherein the sampling frequency is equal to four samples per base-pair. ### Claim 23 (depends on 21) The computer-implemented method of claim 21, wherein the band-pass filter has a low cutoff frequency of 2/13 multiplied by the sampling frequency and a high cutoff frequency of 2/11 multiplied by the sampling frequency. ### Claim 24 (depends on 21) The computer-implemented method of claim 21, wherein the low-pass filter has a cutoff frequency of 1.0*10−5 multiplied by the sampling frequency. ### Claim 25 (depends on 21) The computer-implemented method of claim 21, wherein sampling the DNA size and abundance data at the sampling frequency comprises: generating a linear interpolation of the DNA size and abundance data; and sampling the linear interpolation of the DNA size and abundance data at the sampling frequency. ### Claim 26 (depends on 17) The computer-implemented method of claim 17, wherein the low-pass filter and the band-pass filter are zero-phase finite impulse response (FIR) filters implemented using a Hamming window. ### Claim 27 (depends on 17) The computer-implemented method of claim 17, wherein the DNA size and abundance data comprises a signal representing a combination of a CGG series of the FMR1 gene and a full-length amplicon of the 5′ UTR of the FMR1 gene, the set of band-pass data comprises a signal representing the CGG series of the FMR1 gene, and the set of low-pass data comprises a signal representing the full-length amplicon of the 5′ UTR of the FMR1 gene. ### Claim 28 (depends on 17) The computer-implemented method of claim 17, wherein identifying the peak representing the number of CGG repeats in the CGG-rich region on the 5′ UTR of the FMR1 gene comprises: removing peaks from the one or more peaks in an output of the low-pass filter having a width less than 4.5 base-pairs and a height less than a threshold value; removing peaks from the one or more peaks in an output of the band-pass filter data having a width less than 4.5 base-pairs and a height less than the threshold value; removing peaks from the one or more peaks in the output of the band-pass filter having a height less than a height of an adjacent peak having a larger base-pair length; in response to a peak of the one or more peaks in the output of the low-pass filter having a height less than a height of a peak of the one or more peaks in the output of the band-pass filter that is within 3 base-pairs of the peak of the one or more peaks in the output of the low-pass filter, setting a center of the peak of the one or more peaks in the output of the low-pass filter to a center of the peak of the one or more peaks in the output of the band-pass filter, and setting a boundary of the peak of the one or more peaks in the output of the low-pass filter to a union of the peak of the one or more peaks in the output of the low-pass filter and the peak of the one or more peaks in the output of the band-pass filter; merging peaks of the one or more peaks in the output of the low-pass filter and the one or more peaks in the output of the band-pass filter that have base-pair lengths greater than 165 base-pairs and that are within 30 base-pairs of each other; and merging peaks of the one or more peaks in the output of the low-pass filter and the one or more peaks in the output of the band-pass filter that are within 15 base-pairs and that are more than a factor of 2 different in height, wherein a remaining peak of the one or more peaks in the output of the low-pass filter is the final peak. ### Claim 29 (depends on 17) The computer-implemented method of claim 17, further comprising determining whether the individual is a carrier for fragile X syndrome based on the genotype of the individual, wherein a number of CGG repeats in the CGG-rich region on the 5′ UTR of the FMR1 gene between 5-44 repeats is indicative of a normal allele, a number of CGG repeats in the CGG-rich region on the 5′ UTR of the FMR1 gene between 45-54 repeats is indicative of a an intermediate allele, a number of CGG repeats in the CGG-rich region on the 5′ UTR of the FMR1 gene between 55-200 repeats is indicative of a premutation allele, and wherein a number of CGG repeats in the CGG-rich region on the 5′ UTR of the FMR1 gene greater than 200 repeats is indicative of a full mutation allele. ### Claim 30 A computer-implemented method for determining the number of nucleic acid repeats in a DNA comprising a nucleic acid repeat region, the method comprising: a) receiving, by one or more processors, DNA size and abundance data of DNA amplification products generated from the DNA comprising the nucleic acid repeat region by using a primer set comprising a first primer recognizing the nucleic acid repeat region and a second primer recognizing a region outside of the nucleic acid repeat region; b) generating, by the one or more processors, a set of sample data by sampling the DNA size and abundance data at a sampling frequency; c) generating, by the one or more processors, a set of low-pass data by applying a low-pass filter to the set of sample data; d) generating, by the one or more processors, a set of band-pass data by applying a band-pass filter to the set of sample data; e) identifying, by the one or more processors, one or more peaks in the low-pass data; f) identifying, by the one or more processors, one or more peaks in the band-pass data; and g) identifying, by the one or more processors, a final peak representing a number of nucleic acid repeats in the nucleic acid repeat region based on the one or more peaks in the low-pass data and the one or more peaks in the band-pass data. ### Claim 31 (depends on 1) A non-transitory computer-readable storage medium comprising computer-executable instructions for carrying out any one of the computer-implemented methods of claim 1. ### Claim 32 (depends on 1) A system comprising a processor configured to carry out any one of the computer-implemented methods of claim 1.