Methods and processes for non-invasive assessment of genetic variations

Abstract

Technology provided herein relates in part to methods, processes and apparatuses for non-invasive assessment of genetic variations.

1 . A method for detecting the presence or absence of a chromosome aneuploidy, comprising:
 (a) obtaining counts of partial nucleotide sequence reads mapped to genomic sections of a reference genome, which partial nucleotide sequence reads are reads of circulating cell-free nucleic acid from a test sample from a pregnant female bearing a fetus, wherein at least some of the partial nucleotide sequence reads comprise:
 i) multiple nucleobase gaps between identified nucleobases, or 
 ii) one or more nucleobase classes, wherein each nucleobase class comprises a subset of nucleobases present in the sample nucleic acid, or 
 a combination of (i) and (ii), 
   (b) normalizing the counts of the partial nucleotide sequence reads, thereby providing normalized counts, and   (c) detecting the presence or absence of a chromosome aneuploidy based on the normalized counts.   
     
     
         2 - 10 . (canceled) 
     
     
         11 . The method of claim  10 , wherein the normalizing in (b) comprises normalizing according to guanine and cytosine (GC) content of the genomic sections, and providing calculated genomic section levels. 
     
     
         12 . The method of  claim 11 , wherein the normalizing in (b) comprises:
 (i) determining a guanine and cytosine (GC) bias coefficient for the test sample based on a fitted relation between (1) the counts of the partial nucleotide sequence reads mapped to each of the genomic sections, and (2) GC content for each of the genomic sections, wherein the GC bias coefficient is a slope for a linear fitted relation or a curvature estimation for a non-linear fitted relation; and   (ii) calculating a genomic section level for each of the genomic sections based on the counts of the partial nucleotide sequence reads, the GC bias coefficient of (i), and a fitted relation, for each of the portions, between (1) the GC bias coefficient for each of multiple samples, and (2) the counts of the partial nucleotide sequence reads mapped to each of the genomic sections for the multiple samples, thereby providing calculated genomic section levels, whereby bias in the counts of the partial nucleotide sequence reads mapped to each of the portions of the reference genome is reduced in the calculated genomic section levels, and wherein the normalized counts in (b) comprise the calculated genomic section levels.   
     
     
         13 . The method of  claim 12 , wherein the normalized counts in (b) are the calculated genomic section levels. 
     
     
         14 - 16 . (canceled) 
     
     
         17 . The method of  claim 1 , wherein the normalizing in (b) comprises performing a local regression on the counts of the partial nucleotide sequence reads or the calculated genomic section levels, or the counts of the partial nucleotide sequence reads and the calculated genomic section levels. 
     
     
         18 . The method of  claim 17 , wherein the local regression comprises a weighted least squares fit. 
     
     
         19 . The method of  claim 18 , wherein the local regression comprises a LOESS regression. 
     
     
         20 . The method of  claim 1 , wherein the partial nucleotide sequence reads are unary partial reads, for which unary partial reads one nucleotide species is known at known positions and the other positions can be any one of three other nucleotide species. 
     
     
         21 . The method of  claim 20 , wherein the partial nucleotide sequence reads are about 30 base pairs or more. 
     
     
         22 . The method of  claim 1 , wherein the partial nucleotide sequence reads are binary partial reads, for which binary partial reads a first nucleotide class consisting of two possible bases is known at known positions and a second nucleotide class consisting of two possible bases is known at known positions, wherein the bases of the first nucleotide class are different than the bases of the second nucleotide class. 
     
     
         23 . The method of  claim 22 , wherein the partial nucleotide sequence reads are about 30 base pairs or more. 
     
     
         24 . The method of  claim 1 , wherein the partial nucleotide sequence reads are ternary partial reads, for which ternary partial reads a first nucleotide species is known at known positions, a second nucleotide species is known at other known positions and the other positions are any one of two nucleotide species other than the first nucleotide species and the second nucleotide species. 
     
     
         25 . The method of  claim 24 , wherein the partial nucleotide sequence reads are about 20 base pairs or more. 
     
     
         26 . The method of  claim 1 , comprising sequencing the circulating cell-free nucleic acid and determining the partial nucleotide sequence reads. 
     
     
         27 . The method of  claim 26 , which partial nucleotide sequence reads are determined using a method comprising a massively parallel sequencing (MPS) process or a nanopore process, or a massively parallel sequencing (MPS) process and a nanopore process. 
     
     
         28 . The method of  claim 26 , comprising mapping the partial nucleotide sequence reads to genomic sections of the reference genome. 
     
     
         29 - 31 . (canceled) 
     
     
         32 . The method of  claim 1 , wherein the test sample is blood plasma, blood serum or urine. 
     
     
         33 - 97 . (canceled) 
     
     
         98 . The method of  claim 1 , wherein the chromosome aneuploidy is a fetal chromosome trisomy. 
     
     
         99 . The method of  claim 98 , wherein the chromosome trisomy is a chromosome 13 trisomy, chromosome 18 trisomy and/or chromosome 21 trisomy. 
     
     
         100 . The method of  claim 99 , wherein the chromosome trisomy is a chromosome 21 trisomy.