BAMBAM: parallel comparative analysis of high-throughput sequencing data

• US 10,242,155 B2
• Filed: 12/11/2014
• Issued: 03/26/2019
• Est. Priority Date: 05/25/2010
• Status: Active Grant

• Current Assignee: Regents of the University of California (University of California)
• Original Assignee: Regents of the University of California (University of California)
• Inventors: Sanborn, John Z., Haussler, David
• Primary Examiner(s): Durant, Jonathan
• Application Number:
  US14/567,774
• Publication Number:
  US 20150094963A1
• Time in Patent Office: 1,566 Days
• CPC Class Codes: G06F 3/04845 for image manipulation, e.g. dragging, rotation, expansion or change of colour
• CPC Class Codes: G06F 40/169 Annotation, e.g. comment data or footnotes
• CPC Class Codes: G06N 7/01 Probabilistic graphical models, e.g. probabilistic networks
• CPC Class Codes: G16B 20/00 ICT specially adapted for functional genomics or proteomics, e.g. genotype-phenotype associations
• CPC Class Codes: G16B 20/10 Ploidy or copy number detection
• CPC Class Codes: G16B 20/20 Allele or variant detection, e.g. single nucleotide polymorphism [SNP] detection
• CPC Class Codes: G16B 20/40 Population genetics; Linkage disequilibrium
• 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 50/00 ICT programming tools or database systems specially adapted for bioinformatics
• CPC Class Codes: G16B 50/30 Data warehousing; Computing architectures
• CPC Class Codes: G16H 10/40 for data related to laboratory analysis, e.g. patient specimen analysis
• CPC Class Codes: G16H 10/60 for patient-specific data, e.g. for electronic patient records
• CPC Class Codes: G16H 50/20 for computer-aided diagnosis, e.g. based on medical expert systems
• CPC Class Codes: G16H 50/30 for calculating health indices; for individual health risk assessment
• CPC Class Codes: Y02A 90/10 Information and communication technologies [ICT] supporting adaptation to climate change, e.g. for weather forecasting or climate simulation

Abstract

A differential sequence object is constructed on the basis of alignment of sub-strings via incremental synchronization of sequence strings using known positions of the sub-strings relative to a reference genome sequence. An output file is then generated that comprises only relevant changes with respect to the reference genome.

Claims

1. A genomic analysis system comprising:

a data storage device storing a first aligned read file and a second aligned read file, where each file comprises genetic aligned sequence reads that include genomic location information; and

an analysis engine coupled with the data storage device and configured to;

obtain a first aligned sequence read from the first aligned read file and a second aligned sequence read from the second aligned read file;

align the first aligned sequence read and the second aligned sequence read through their respective genomic location information to form a local alignment between the first and second aligned sequence reads by using at least one known position of a sub-string of the first aligned sequence read or the second aligned sequence read in incremental synchronizing of the first aligned sequence read and the second aligned sequence read that moves from a previous local alignment to a next local alignment to bring the first aligned sequence read and the second aligned sequence read into alignment with each other and with each next local alignment depending upon the previous local alignment except for one or more mismatched portions of the first aligned sequence read or the second aligned sequence read;

generate a local differential sequence between the first and the second aligned sequence reads within the local alignment;

update a differential genetic sequence object according to the local differential sequence, wherein the updated differential genetic sequence object comprises the one or more mismatched portions of the first aligned sequence read or the second aligned sequence read; and

cause the differential genetic sequence object to be stored on a second storage device.

2. The system of claim 1, wherein the first and the second aligned read files conform to the same format.

3. The system of claim 1, wherein the first aligned read file conforms to a standard file format.

4. The system of claim 3, wherein the standard file format conforms to a BAM format.

5. The system of claim 1, wherein at least one of the first and the second aligned sequence reads comprises an aligned short-read.

6. The system of claim 1, wherein the first aligned read file conforms to a format that manages aligned reads.

7. The system of claim 1, wherein the first aligned read file conforms to a format that manages unmapped reads.

8. The system of claim 1, wherein the first aligned read file conforms to a format that manages metadata.

9. The system of claim 1, wherein the first aligned read file supports re-alignment.

10. The system of claim 1, wherein the differential genetic sequence object comprises a file.

11. The system of claim 1, wherein the second storage device comprises a medical record storage device.

12. The system of claim 1, wherein the differential genetic sequence object comprises a genetic status.

13. The system of claim 12, wherein the genetic status includes at least one of the following:

a deletion and an insertion.

14. The system of claim 1, wherein the differential genetic sequence object comprises a discovered variant.

15. The system of claim 14, wherein the discovered variant includes a structural variant.

16. The system of claim 14, wherein the discovered variant includes at least one of the following:

a somatic variant, and a germline variant.

17. The system of claim 1, wherein the first aligned read file represents a first complete genome of a tissue.

18. The system of claim 17, wherein the second aligned read file represents a second complete genome of the tissue generated at a different time.