Polymorphic gene typing and somatic change detection using sequencing data
US-2016298185-A1 · Oct 13, 2016 · US
US12562237B2 · US · B2
| Field | Value |
|---|---|
| Publication number | US-12562237-B2 |
| Application number | US-202117324793-A |
| Country | US |
| Kind code | B2 |
| Filing date | May 19, 2021 |
| Priority date | May 19, 2020 |
| Publication date | Feb 24, 2026 |
| Grant date | Feb 24, 2026 |
A practical reading order for non-experts. Skip the full description unless you need deep technical detail.
What the patent document calls the invention.
A short plain-language summary of the technical disclosure.
Who owns or filed the patent and who is credited as inventor.
Filing, priority, publication, and grant dates set the timeline.
The legal scope of protection — read this for what is actually claimed.
Technology tags used to group this patent with similar filings.
Prior art links and similar publications in this corpus.
Official abstract text for this publication.
Disclosed are methods, systems and computer-program products for the determination of complex genetic variants. The disclosed methods, systems and computer-program products may include obtaining a mutant scaffold nucleotide sequence that comprises a sequence that includes mutations characteristic of the complex genetic variant; obtaining a wild-type scaffold nucleotide sequence having a wild-type sequence; generating an alignment of at least one sequence from the sample to the mutant scaffold and to the wild-type scaffold; and determining that the sample contains a mutation characteristic of the complex genetic variant based on alignment to the mutant scaffold and not the wild-type scaffold.
Opening claim text (preview).
That which is claimed: 1 . A computer-implemented method for detecting the presence or absence of a complex genetic variant in a sample, comprising: accessing a mutant scaffold that comprises a custom nucleotide sequence that includes: (i) a mutation characteristic of the complex genetic variant within a target region of a genome and (ii) an additional artificial genetic variation not found in either the complex genetic variant or any wild-type sequence within the target region of the genome, wherein the mutant scaffold is constructed in silico as a digital structure representation of the custom nucleotide sequence; accessing a wild-type scaffold that comprises a wild-type nucleotide sequence within the target region of the genome, wherein the wild-type scaffold is constructed in silico as a digital structure representation of the wild-type nucleotide sequence; accessing sequence reads of nucleic acid obtained from the sample for the target region; mapping, by an alignment algorithm, the sequence reads to matching sequences within the digital structure representation of the custom nucleotide sequence of the mutant scaffold; mapping, by the alignment algorithm, the sequence reads to matching sequences within the digital structure representation of the wild-type nucleotide sequence of the wild-type scaffold; counting (i) sequence reads mapped to the custom nucleotide sequence that includes the complex genetic variant and the additional artificial genetic variation and (ii) sequence reads mapped to the wild-type nucleotide sequence, wherein the counting generates a quantification of the sequence reads mapped to the custom nucleotide sequence and a quantification of the sequence reads mapped to the wild-type nucleotide sequence; determining whether the sample contains the mutation based on the quantification of the sequence reads mapped to the custom nucleotide sequence versus the quantification of the sequence reads mapped to the wild-type nucleotide sequence; and outputting a result that the sample contains the presence or absence of the complex genetic variant based on the determination of whether the sample contains the mutation. 2 . The computer-implemented method of claim 1 , wherein: the additional artificial genetic variation serves as a marker for the presence and/or phasing of the mutation characteristic of the complex genetic variant; and mapping the sequence reads to matching the sequences within the digital structure representation of the custom nucleotide sequence comprises identifying an expected mismatch between the sequence reads and the matching sequences based on the additional artificial genetic variation. 3 . The computer-implemented method of claim 1 , further comprising parametrizing the alignment algorithm with a mismatch and gap penalty cost difference such that only the sequence reads that have the mutation characteristic of the complex genetic variant will align to the mutant scaffold. 4 . The computer-implemented method of claim 1 , further comprising: determining the sample contains the mutation characteristic of the complex genetic variant based on the quantification of the sequence reads mapped to the sequences that include the complex genetic variant versus the quantification of the sequence reads mapped to the sequences that include the wild-type nucleotide sequence; outputting the result that the sample contains the presence of the complex genetic variant based on the determination that the sample contains the mutation characteristic of the complex genetic variant; and providing a treatment to a subject associated with the sample in accordance with the presence of the complex genetic variant in the sample. 5 . The computer-implemented method of claim 4 , wherein the treatment is a therapeutic agent or a prescribed dietary change. 6 . The computer-implemented method of claim 1 , further comprising providing a treatment to a subject associated with the sample in accordance with the presence of the complex genetic variant in the sample, wherein the complex genetic variant is in the target region of a cystathionine beta-synthase (CBS) gene, wherein the treatment is a therapeutic agent or a prescribed dietary change, and wherein the therapeutic agent is vitamin B6 or the prescribed dietary change is a low-methionine diet. 7 . The computer-implemented method of claim 1 , wherein the complex genetic variant has two mutations. 8 . The computer-implemented method of claim 7 , further comprising: determining whether the two mutations are on the same chromosome (cis) or on different chromosomes (trans) based on the mapping of the sequence reads to the matching sequences in the mutant scaffold; and outputting the result that the sample contains the presence or absence of the complex genetic variant with notation concerning the two mutations being on the same chromosome (cis) or on different chromosomes (trans) based on the determination of whether the sample contains the mutation characteristic of the complex genetic variant and whether the two mutations are on the same chromosome (cis) or on different chromosomes (trans). 9 . The computer-implemented method of claim 1 , wherein the complex genetic variant is in the target region of a cystathionine beta-synthase (CBS) gene. 10 . The computer-implemented method of claim 9 , wherein the mutant scaffold and wild-type scaffold distinguish (i) a sequence having a 68 bp insertion [844_845ins68] in cis with a c.833T>C mutation, from (ii) a sequence having the 68 bp insertion [844_845ins68] in trans with c.833T>C, from (iii) a sequence having the 68 bp insertion [844_845ins68] without c.833T>C, or from (iv) a sequence having c.833T>C without the 68 bp insertion [844_845ins68]. 11 . A system comprising: one or more processors; a memory coupled to the one or more processors, the memory storing a plurality of instructions executable by the one or more processors, the plurality of instructions comprising instructions that when executed by the one or more processors cause the one or more processors to perform processing comprising: accessing a mutant scaffold that comprises a custom nucleotide sequence that includes: (i) a mutation characteristic of a complex genetic variant within a target region of a genome, and (ii) an additional artificial genetic variation not found in either the complex genetic variant or any wild-type sequence within the target region of the genome, wherein the mutant scaffold is constructed in silico as a digital structure representation of the custom nucleotide sequence; accessing a wild-type scaffold that comprises a wild-type nucleotide sequence within the target region of the genome, wherein the wild-type scaffold is constructed in silico as a digital structure representation of the wild-type nucleotide sequence; accessing sequence reads of nucleic acid obtained from a sample for the target region; mapping, by an alignment algorithm, the sequence reads to matching sequences within the digital structure representation of the custom nucleotide sequence of the mutant scaffold; mapping, by the alignment algorithm, the sequence reads to matching sequences within the digital structure representation of the wild-type nucleotide sequence of the wild-type scaffold; counting (i) sequence reads mapped to the custom nucleotide sequence that includes the complex genetic variant and the additional artificial genetic variation and (ii) sequence reads mapped to the wild-type nucleotide sequence, wherein the counting generates a quantification of the sequence reads mapped to the custom nucleotide sequences and a quantification of the sequence reads mapped to the wild-type nucleotide sequence;
ICT specially adapted for functional genomics or proteomics, e.g. genotype-phenotype associations · CPC title
involving nucleic acid arrays, e.g. sequencing by hybridisation · CPC title
Allele or variant detection, e.g. single nucleotide polymorphism [SNP] detection · CPC title
ICT specially adapted for sequence analysis involving nucleotides or amino acids · CPC title
Related publications grouped by family.
Answers are generated from the same data shown on this page.