Methods and processes for non-invasive assessment of genetic variations

Patent metadata

Field	Value
Publication number	US-2016110497-A1
Application number	US-201414781987-A
Country	US
Kind code	A1
Filing date	Apr 2, 2014
Priority date	Apr 3, 2013
Publication date	Apr 21, 2016
Grant date	—

Abstract

Provided herein are methods, processes, apparatuses and machines for non-invasive assessment of genetic variations.

First claim

1 - 82 . (canceled)

83 . A method for determining the presence or absence of a chromosome trisomy, comprising:
(a) obtaining counts of sequence reads mapped to portions of a reference genome, which sequence reads are reads of circulating cell-free nucleic acid from a test sample from a pregnant female; (b) generating a regression for (i) the counts, and (ii) guanine and cytosine (GC) content, for each of the portions of the reference genome for the test sample; (c) assessing the goodness of fit of the counts and the GC content to a non-linear regression or a linear regression, thereby generating an assessment; (d) normalizing the counts by a process selected according to the assessment, thereby generating normalized counts with reduced GC bias; and (e) determining the presence or absence of a chromosome trisomy according to the normalized counts.

84 . The method of claim 83 , wherein the regression in (b) is a linear regression or a non-linear regression.

85 . The method of claim 84 , wherein the normalizing in (d) comprises, in instances where the assessment is indicative of a linear regression, subtracting the linear regression from the counts.

86 . The method of claim 84 , wherein the normalizing in (d) comprises, in instances where the assessment is indicative of a non-linear regression, subtracting the non-linear regression from the counts.

87 . The method of claim 84 , wherein the non-linear regression is performed by a LOESS process.

88 . The method of claim 87 , wherein the LOESS process is a GC-LOESS process.

89 . The method of claim 87 , wherein the LOESS process is a LOESS smoothing process.

90 . The method of claim 83 , wherein part (c) comprises determining a correlation coefficient from the regression, and the assessment is determined according to the correlation coefficient and a correlation coefficient cutoff value.

91 . The method of claim 90 , wherein the correlation coefficient cutoff value is about 0.5 to about 0.7.

92 . The method of claim 90 , wherein the correlation coefficient cutoff value is about 0.6.

93 . The method of claim 90 , wherein the correlation coefficient is equal to or greater than the correlation coefficient cutoff and the assessment in (c) is indicative of a linear regression.

94 . The method of claim 90 , wherein the correlation coefficient is equal to or less than the correlation coefficient cutoff and the assessment in (c) is indicative of a non-linear regression.

95 . The method of claim 83 , comprising, prior to (a):
(i) determining an uncertainty value for counts mapped for each of the portions for multiple test samples; and (ii) selecting a subset of portions having an uncertainty value within a pre-determined range of uncertainty values, thereby retaining selected portions; whereby (a) to (c) are performed using the selected portions.

96 . The method of claim 95 , wherein the uncertainty value is a median absolute deviation (MAD).

97 . The method of claim 95 , wherein the selected portions are in at least the 95% quantile of count variability.

98 . The method of claim 95 , wherein the selected portions are in at least the 99% quantile of count variability.

99 . The method of claim 83 , wherein each portion of the reference genome comprises a nucleotide sequence of a predetermined length of about 50 kilobases.

100 . The method of claim 83 , wherein the trisomy is trisomy 21, trisomy 18, or trisomy 13.

101 . The method of claim 83 , wherein the test sample comprises blood plasma or blood serum from the pregnant female.

102 . The method of claim 83 , comprising, prior to (a), sequencing nucleic acid of the test sample thereby providing sequencing reads, mapping the sequencing reads to the portions of the reference genome, and counting the reads mapped to the portions.

Assignees

• Sequenom Inc
• Sequenom Inc

Inventors

• Dzakula Zeljko
• Zhao Chen
• Deciu Cosmin

Classifications

• G16B30/00

  ICT specially adapted for sequence analysis involving nucleotides or amino acids · CPC title

• G06F17/18

  for evaluating statistical data {, e.g. average values, frequency distributions, probability functions, regression analysis (forecasting specially adapted for a specific administrative, business or logistic context G06Q10/04)} · CPC title

• G16B20/00 Primary

  ICT specially adapted for functional genomics or proteomics, e.g. genotype-phenotype associations · CPC title

• G06F19/18 Primary

  Physics · mapped topic

• G06F19/22

  Physics · mapped topic