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Reducing sequence read count error in assessment of complex genetic variations

  • US 9,984,198 B2
  • Filed: 03/12/2013
  • Issued: 05/29/2018
  • Est. Priority Date: 10/06/2011
  • Status: Active Grant
First Claim
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1. A computer-implemented method for detecting presence or absence of a complex genetic variation, comprising:

  • (a) obtaining counts of sequence reads mapped to portions of a reference genome, which sequence reads are of circulating cell-free nucleic acid from a test sample from a pregnant female;

    (b) reducing error in the counts of the sequence reads, wherein the error is reduced according to a process comprising;

    (1) assigning a guanine and cytosine (GC) bias coefficient to the test sample based on a fitted relation between (i) the counts of the sequence reads mapped to each of the portions and (ii) GC content for each of the portions, wherein the GC bias coefficient is a slope for a linear fitted relation or a curvature estimation for a non-linear fitted relation; and

    (2) calculating a genomic section level for each of the portions for the test sample based on the counts of (a), the GC bias coefficient of (b)(1), and a fitted relation, for each of the portions, between (i) the GC bias coefficient for each of multiple samples and (ii) the counts of the sequence reads mapped to each of the portions for the multiple samples, thereby providing calculated genomic section levels, whereby error in the counts of the sequence reads is reduced; and

    (c) outputting a classification of the presence or absence of a complex genetic variation for the test sample according to the calculated genomic section levels, wherein the complex genetic variation comprises two or more copy number variations chosen from a whole chromosome aneuploidy, a microduplication, and a microdeletion, and wherein a measure of deviation between (i) calculated genomic section levels for portions that include a copy number variation and (ii) expected genomic section levels for portions that include no copy number variation is larger for counts with error reduction according to (b) than a measure of deviation between (i) and (ii) for counts with no error reduction according to (b).

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