Methods and systems for genomic analysis

Patent metadata

Field	Value
Publication number	US-2024257913-A1
Application number	US-202418431138-A
Country	US
Kind code	A1
Filing date	Feb 2, 2024
Priority date	Aug 30, 2013
Publication date	Aug 1, 2024
Grant date	—

Abstract

A computer-implemented method for processing and/or analyzing nucleic acid sequencing data comprises receiving a first data input and a second data input. The first data input comprises untargeted sequencing data generated from a first nucleic acid sample obtained from a subject. The second data input comprises target-specific sequencing data generated from a second nucleic acid sample obtained from the subject. Next, with the aid of a computer processor, the first data input and the second data input are combined to produce a combined data set. Next, an output derived from the combined data set is generated. The output is indicative of the presence or absence of one or more polymorphisms of the first nucleic acid sample and/or the second nucleic acid sample.

First claim

What is claimed is:

1 . A method for genetic analysis of a subject, comprising:
a. subjecting a first nucleic acid sample of said subject to untargeted sequencing to generate untargeted sequencing data; b. subjecting a second nucleic acid sample of said subject to target-specific sequencing to generate target-specific sequencing data, wherein said target-specific sequencing data comprises less than about 60 megabases, and wherein said target-specific sequencing data is at greater coverage than said untargeted sequencing data; and c. using a computer to generate a combined output from said untargeted sequencing data and said target-specific sequencing data, which combined output is indicative of a presence or absence of one or more polymorphisms in at least a portion of a genome of said subject.

2 . The method of claim 1 , wherein (c) comprises (1) mapping said untargeted sequencing data onto a first reference sequence to generate a first alignment, and (2) mapping said target-specific sequencing data onto a second reference sequence to generate a second alignment.

3 . The method of claim 2 , wherein said first reference sequence and said second reference sequence are the same sequence.

4 . The method of claim 1 , wherein said combined output comprises a uniform alignment that is mappable onto a reference sequence.

5 . The method of claim 1 , wherein said target-specific sequencing data is based on targeted sequencing of an exome, specific genes, genomic regions, or a combination thereof.

6 . The method of claim 1 , wherein said untargeted sequencing data is generated using one or more random primers or hybridization probes, and wherein said target-specific sequencing data is generated using one or more non-random primers or hybridization probes.

7 . The method of claim 6 , wherein said non-random primers comprise primers targeting one or more genes, exons, untranslated regions, or a combination thereof.

8 . The method of claim 1 , wherein said untargeted sequencing data is whole genome sequencing data, off-target data arising from a targeted assay, or a combination thereof.

9 . The method of claim 8 , wherein said whole genome sequencing data comprises single reads, paired-end reads, or mate-pair reads.

10 . The method of claim 1 , wherein said first nucleic acid sample and said second nucleic acid sample are derived from a biological sample of said subject.

11 . The method of claim 1 , wherein said target-specific sequencing data comprises a specific portion and a non-specific portion, and wherein at least a portion of said untargeted sequencing data is included in said non-specific portion of said target-specific sequencing data.

12 . The method of claim 11 , wherein said untargeted sequencing data is included in said non-specific portion of said target-specific sequencing data.

13 . The method of claim 1 , wherein each of said untargeted sequencing data and said target-specific sequencing data comprises variant data, and wherein (c) comprises combining variant data from said untargeted sequencing data and variant data from said target-specific sequencing data into said combined output.

14 . The method of claim 13 , wherein said untargeted sequencing data comprises copy number or structural variant data, and wherein said target-specific sequencing data comprises single nucleotide variations (SNV) or insertion deletion polymorphism (indel) data.

15 . The method of claim 1 , wherein said target-specific sequencing data comprises up to about 30 megabases.

16 . The method of claim 1 , wherein said first nucleic acid sample and said second nucleic acid sample are separately subjected to untargeted sequencing and target-specific sequencing, respectively.

17 . The method of claim 1 , wherein (c) comprises removing any redundant sequences.

18 . The method of claim 1 , wherein (c) comprises using a computer processor to identify said one or more polymorphisms at a sensitivity greater than or equal to 90%, wherein said one or more polymorphisms include structural variants that are less than 100,000 bases in length.

19 . The method of claim 1 , wherein said target-specific sequencing data comprises sequencing data corresponding to less than or equal to about 180,000 exons in an exome of said subject.

20 . A system for genetic analysis of a subject, comprising:
at least one computer memory comprising untargeted sequencing data and target-specific sequencing data, wherein said untargeted sequencing data is generated by untargeted sequencing of a first nucleic acid sample of said subject and said target-specific sequencing data is generated by target-specific sequencing of a second nucleic acid sample of said subject, wherein said target-specific sequencing data comprises less than about 60 megabases, and wherein said target-specific sequencing data is at greater coverage than said untargeted sequencing data; a computer processor coupled to said at least one computer memory and programmed to (i) generate a combined output from said untargeted sequencing data and said target-specific sequencing data, which combined output is indicative of a presence or absence of one or more polymorphisms in at least a portion of a genome of said subject; and an electronic data storage unit coupled to said computer processor, wherein said electronic data storage unit is configured to store said combined output.

21 . The system of claim 20 , wherein each of said untargeted sequencing data and said target-specific sequencing data comprises variant data, and wherein said computer processor is programmed to combine variant data from said untargeted sequencing data and variant data from said target-specific sequencing data into said combined output.

22 . The system of claim 21 , wherein said untargeted sequencing data comprises copy number or structural variant data, and wherein said target-specific sequencing data comprises single nucleotide variations (SNV) or insertion deletion polymorphism (indel) data.

23 . The system of claim 20 , further comprising an electronic display coupled to said computer processor, wherein said electronic display provides said combined output for display.

24 . The system of claim 20 , wherein said computer processor is programmed to (1) map said untargeted sequencing data onto a first reference sequence in computer memory to generate a first alignment, and (2) map said target-specific sequencing data onto a second reference sequence in computer memory to generate a second alignment.

25 . The system of claim 20 , wherein said computer processor is programmed to generate said combined output by (1) combining said untargeted sequencing data and said target-specific sequencing and (2) removing any redundant sequences.

26 . The system of claim 20 , wherein said untargeted sequencing data comprises up to about 30 megabases.

27 . The system of claim 20 , wherein said target-specific sequencing data comprises sequencing data corresponding to less than or equal to about 180,000 exons in an exome of said subject.

28 . The system of claim 20 , wherein said computer processor is programmed to generate said combined output that is indicative of the presence or absence of said one or more polymorphisms at a sensitivity greater than or equal to 90%, wherein said one or more polymorphisms include structural variants that are less

Assignees

• Personalis Inc

Inventors

• Harris Jason
• Pratt Mark R
• West John
• Chen Richard
• Li Ming

Classifications

• G06N20/20

  Ensemble learning · CPC title

• C12Q1/6886

  for cancer (immunoassay for cancer G01N33/575) · CPC title

• C12Q1/68

  involving nucleic acids · CPC title

• G16H50/00

  ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics · CPC title

• G16B20/20

  Allele or variant detection, e.g. single nucleotide polymorphism [SNP] detection · CPC title