Methods and systems for detecting sequence variants

• US 9,904,763 B2
• Filed: 06/29/2016
• Issued: 02/27/2018
• Est. Priority Date: 08/21/2013
• Status: Active Grant

• Current Assignee: Seven Bridges Genomics, Inc.
• Original Assignee: Seven Bridges Genomics, Inc.
• Inventors: Kural, Deniz
• Primary Examiner(s): Martinell, James
• Application Number:
  US15/196,345
• Publication Number:
  US 20160306921A1
• Time in Patent Office: 608 Days
• Field of Search: None
• CPC Class Codes: G16B 30/00 ICT specially adapted for sequence analysis involving nucleotides or amino acids
• CPC Class Codes: G16B 30/10 Sequence alignment; Homology search
• CPC Class Codes: G16B 30/20 Sequence assembly
• CPC Class Codes: G16B 50/00 ICT programming tools or database systems specially adapted for bioinformatics

Abstract

The invention provides methods for identifying rare variants near a structural variation in a genetic sequence, for example, in a nucleic acid sample taken from a subject. The invention additionally includes methods for aligning reads (e.g., nucleic acid reads) to a reference sequence construct accounting for the structural variation, methods for building a reference sequence construct accounting for the structural variation or the structural variation and the rare variant, and systems that use the alignment methods to identify rare variants. The method is scalable, and can be used to align millions of reads to a construct thousands of bases long, or longer.

Claims

1. A method of identifying variations in sequence data, the method comprising:

using at least one computer hardware processor to perform;

receiving a plurality of nucleotide sequence reads from a genomic sample, wherein at least one sequence read comprises a mutation and at least a portion of a structural variation;

representing, in at least one non-transitory computer-readable storage medium connected to the computer hardware processor, a reference sequence and a plurality of known variations from the reference sequence as a reference graph, wherein the reference graph is an assembled construct represented as a directed graph stored in the at least one non-transitory computer-readable storage medium, the reference graph comprising a first node representing a conserved portion of the reference sequence, the first node connected by directed edges to a second node and a third node, the second node representing a first alternative sequence and the third node representing a second alternative sequence, the second alternative sequence comprising a sequence matching the structural variation;

mapping, using the computer hardware processor, the at least one sequence read to the reference graph, the mapping comprising determining a location on the reference graph for which a score for the at least one sequence read is maximized, wherein the determined location of the mapped at least one sequence read spans the first node and the third node; and

identifying the mutation within the mapped at least one sequence read with respect to the conserved portion of the reference sequence represented by the first node.

2. The method of claim 1, wherein the direction of the directed edges is towards the second and third nodes.

3. The method of claim 1, wherein the direction of the directed edges is towards the first node.

4. The method of claim 1, wherein the reference graph is acyclic.

5. The method of claim 1, further comprising mapping a second sequence read to the reference graph.

6. The method of claim 5, wherein the second sequence read does not comprise the mutation and at least a portion of the structural variation.

7. The method of claim 5, wherein the determined location of the mapped second sequence read spans only the first node.

8. The method of claim 1, wherein mapping the at least one sequence read to the reference graph comprises calculating a scoring matrix for each node.

9. The method of claim 8, wherein the scoring matrix considers scores from predecessor nodes.

10. The method of claim 1, wherein a length of the at least one sequence read is less than 500 base pairs.

11. The method of claim 1, wherein the mutation and the structural variation are separated by 100 bp or fewer.

12. The method of claim 1, wherein the structural variation is 100 bp to 3 megabases in length.

13. The method of claim 1, wherein the structural variation is a marker for disease.

14. The method of claim 1, wherein identifying the mutation within the mapped at least one sequence read comprises comparing the mapped at least one sequence read with the first node and the third node by comparing the mapped at least one sequence read with the conserved portion of the reference sequence and the second alternative sequence.

15. The method of claim 1, wherein the mutation comprises a single nucleotide polymorphism.

16. The method of claim 1, further comprising adding the mutation to the reference graph.

17. The method of claim 16, wherein adding the mutation to the reference graph comprises:

segmenting the first node, at a position of the mutation in the conserved portion of the reference sequence, into two segmented nodes, the two nodes representing the 5′

sequence and 3′

sequence of the conserved portion of the reference sequence adjacent to the mutation, respectively;

associating the mutation with a mutation node;

associating the conserved portion of the reference sequence at the mutation with a reference node;

connecting, within the reference graph, the two segmented nodes, the mutation node, and the reference node with a plurality of directed edges, such that a first path through the reference graph includes the mutation, and a second path through the reference graph includes the reference sequence.

18. The method of claim 1, further comprising mapping the plurality of sequence reads to the reference graph, identifying a set of mapped sequence reads overlapping the mutation, and determining whether the mutation is present in the identified set of mapped sequence reads at a frequency of less than 5%.

19. The method of claim 18, further comprising determining whether the mutation is present in the identified set of mapped sequence reads at a frequency of less than 1%.

20. A system for identifying variations in sequence data, the system comprising:

at least one computer hardware processor; and

at least one non-transitory computer-readable storage medium storing processor executable instructions that, when executed by the at least one computer hardware processor, cause the at least one computer hardware processor to;

receive a plurality of nucleotide sequence reads from a genomic sample, wherein at least one sequence read comprises a mutation and at least a portion of a structural variation;

represent a reference sequence and a plurality of known variations as a reference graph, the reference graph comprising a first node representing a conserved portion of the reference sequence, the first node connected by directed edges to a second node and a third node, the second node representing a first alternative sequence and the third node representing a second alternative sequence, the second alternative sequence comprising a sequence matching the structural variation, wherein the reference graph is an assembled construct represented as a directed graph stored in the computer-readable storage medium;

map the at least one sequence read to the reference graph, the mapping comprising determining a location on the reference graph for which a score for the sequence read is maximized, wherein the determined location of the mapped at least one sequence read spans the first node and the third node; and

identify the mutation within the mapped at least one sequence read with respect to the conserved portion of the reference sequence represented by the first node.