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US 12,706,175 B2Granted
Methods and processes for non-invasive assessment of genetic variations
AssigneeSequenom, Inc.
InventorsZeljko Dzakula, Amin R. Mazloom, Cosmin Deciu, Huiquan Wang
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Abstract
Provided herein are methods, processes and apparatuses for non-invasive assessment of genetic variations.
Claims28
A method for determining sex chromosome karyotype for a fetus, comprising:
- (I) sequencing circulating cell-free nucleic acid in a test sample from a pregnant subject bearing a fetus by genome-wide massively parallel sequencing, thereby generating sequence reads;
- (II) mapping, using a microprocessor, the sequence reads to portions of a reference genome;
- (III) counting, using a microprocessor, the sequence reads mapped to the portions of the reference genome, thereby generating counts of the sequence reads;
- (IV) normalizing the counts of the sequence reads according to a process comprising:
- (a) determining, using a microprocessor, a guanine and cytosine (GC) bias coefficient for the test sample based on a linear regression of
- (i) the counts of the sequence reads mapped to each of the portions, and
- (ii) a GC content for each of the portions, wherein the GC bias coefficient is a slope of the linear regression;
- (b) for each portion, receiving onto memory model parameters comprising a slope and an intercept from a linear regression of
- (i) a GC bias coefficient for each of multiple samples in a dataset, wherein the GC bias coefficient for each of the multiple samples in the dataset is the slope of a linear regression of (1) counts of sequence reads mapped to each of the portions of the reference genome for each of the multiple samples, and (2) GC content for each of the portions for each of the multiple samples, and
- (ii) counts of sequence reads mapped to the portion of the reference genome for each of the multiple samples, wherein the dataset comprises samples comprising circulating cell-free nucleic acid from multiple pregnant women with known fetal karyotype;
- and
- (c) generating, using a microprocessor, genomic section level (L) for each of the portions according to Li=(mi−GiS)I−1,
- wherein G is the GC bias coefficient determined in (a), I is the intercept provided in (b), S is the slope provided in (b), m is the counts of the sequence reads generated in (III), and i is the test sample;
- (V) determining a sex chromosome karyotype for the fetus according to the genomic section levels generated in (c);
- and
- (VI) generating a report for the sex chromosome karyotype for the fetus based on the determination in (V).
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Dependencies are inferred from the claim text.