IP Library Granted Patent US 11,164,656
Granted Patent B2
US 11,164,656 · App. 16/107,904 · Granted Nov 2, 2021

Bambam: parallel comparative analysis of high-throughput sequencing data

Inventors: John Zachary Sanborn (Santa Cruz, CA); David Haussler (Santa Cruz, CA)
Assignee: THE REGENTS OF THE UNIVERSITY OF CALIFORNIA
G16B30/10C12Q1/6886G06F3/04845G06F40/169G06N7/005G06T11/206G16B20/20G16B30/00G16B40/00G16H50/20C12Q2600/106C12Q2600/118C12Q2600/156G06F2203/04806G16H10/40G16H10/60G16H70/20Y02A90/10Y02A90/30
View Patent ↗
Loading inventors, assignments & file history…
Monitor This Case
Get email alerts when status or documents change.
Order Certified Copies
Most orders are placed with the USPTO same day — all within 24 business hours.
Order via The Patent Place →
Pre-filled with this patent's details
Quick Facts
Patent No.
US 11,164,656
App. No.
16/107,904
Granted
Nov 2, 2021
Kind
B2
Abstract

The present invention relates to methods for evaluating and/or predicting the outcome of a clinical condition, such as cancer, metastasis, AIDS, autism, Alzheimer's, and/or Parkinson's disorder. The methods can also be used to monitor and track changes in a patient's DNA and/or RNA during and following a clinical treatment regime. The methods may also be used to evaluate protein and/or metabolite levels that correlate with such clinical conditions. The methods are also of use to ascertain the probability outcome for a patient's particular prognosis.

Claims (204)

1. A parallel genomic comparative analysis system comprising:

a computer-readable memory; and

a sequence analysis engine having at least one processor coupled with the computer-readable memory and configured to:

access a first file storing tumor sequence data including tumor reads associated with a tumor tissue;

access a second file storing matched normal sequence data including matched normal reads associated with a matched normal tissue;

read into the computer-readable memory at the same time from the first file and the second file and relative to a genomic position the tumor reads associated with the tumor tissue and the matched normal reads associated with the matched normal tissue;

select a tumor genotype and a matched normal genotype that maximize a likelihood as a function of the tumor reads and the matched normal reads at the genomic position;

determine at least one difference associated with at least one of the tumor sequence data and the matched normal sequence data at the genomic position based on at least one of the tumor genotype and the matched normal genotype;

store the at least one difference associated a device memory; and

wherein the likelihood is defined by:

P

(

D

g

,

D

t

,

G

g

,

G

t

|

α

,

r

)

=

P

(

D

g

|

G

g

)

P

(

G

g

|

r

)

P

(

D

t

|

G

g

,

G

t

,

α

)

P

(

G

t

|

G

g

)

(

1

)

where r is an observed reference allele, α is a fraction of normal contamination, where tumor genotypes and matched normal genotypes are defined by Gt=(t 1 , t 2 ) and Gg=(g 1 ,g 2 ), where t 1 , t 2 , g 1 , g 2 ∈{A, T, C, G}, and where the tumor sequence data and the matched normal sequence data are defined as a set of reads D t ={d t 1 , d t 2 . . . , d t n } and D g ={d g 1 , d g 2 . . . , d g n }, respectively, with the observed bases d t i , d g i ∈{A, T, C, G}.

2. The system of claim 1 , wherein a probability of matched normal alleles given the matched normal genotype is modeled as a multinomial over four nucleotides:

P

(

D

g

|

G

g

)

=

n

!

n

A

!

n

T

!

n

G

!

n

C

!

i

n

P

(

d

g

i

|

G

g

)

,

where n is a total number of matched normal reads at the genomic position and n A , n G , n C , n t are reads supporting each observed allele, and

a probability of tumor alleles given the tumor genotype is modeled as the multinomial over four nucleotides:

P

(

D

t

|

G

t

,

G

g

,

α

)

=

n

!

n

A

!

n

T

!

n

G

!

n

C

!

i

n

P

(

d

t

i

|

G

t

,

G

g

,

α

)

,

where n is the total number of matched normal reads at the genomic position and n A , n G , n C , n t are reads supporting each observed allele.

3. The system of claim 1 , wherein the tumor reads and the matched normal reads comprise short reads.

4. The system of claim 1 , wherein the genomic position is relative to a reference genome.

5. The system of claim 1 , wherein the likelihood comprises a joint probability.

6. The system of claim 1 , wherein the at least one difference is selected from the group consisting of: a somatic variant, a germline variant, a single nucleotide polymorphism, an allele-specific copy number, a loss of heterozygosity, a structural rearrangement, a chromosomal fusion, a mutation, a difference relative to a reference genome, and a breakpoint.

7. The system of claim 1 , wherein the tumor reads associated with the tumor tissue form a tumor pileup and the matched normal reads associated with the matched normal tissue form a matched normal pileup.

8. The system of claim 1 , wherein the sequence analysis engine is further configured to identify false positives.

9. The system of claim 8 , wherein the false positives are determined based on at least one of the following distributions: a strand distribution, and an allele position distribution.

10. The system of claim 1 , wherein the at least one difference comprises a difference between the tumor sequence data at the genomic position and the matched normal sequence data at the genomic position.

11. A parallel genomic comparative analysis system comprising:

a computer-readable memory; and

a sequence analysis engine having at least one processor coupled with the computer-readable memory and configured to:

access a first file storing tumor sequence data including reads associated with a tumor tissue;

access a second file storing matched normal sequence data including reads associated with a matched normal tissue;

read, into the computer-readable memory at the same time from the first file and the second file and relative to a first genomic position, the reads associated with the tumor tissue and the reads associated with the matched normal tissue;

select a tumor genotype and a matched normal genotype that maximize a likelihood as a function of the tumor sequence data and the matched normal sequence data at the first genomic position, wherein the likelihood is calculated based on a multinomial operating as a function of at least one of the tumor genotype or the matched normal genotype;

determine at least a first difference associated the tumor sequence data and the matched normal sequence data at the first genomic position based on at least one of the tumor genotype and the matched normal genotype;

determine at least a second difference associated the tumor sequence data and the matched normal sequence data at a second genomic position based on reads at the second genomic position and corresponding selected second tumor genotype and second matched normal genotype at the second genomic position; and

store the at least first and second differences in a device memory.

12. The system of claim 11 , wherein the reads comprises short reads.

13. The system of claim 11 , wherein the first and the second genomic positions are relative to reference genome.

14. The system of claim 11 , wherein the likelihood comprises a joint probability.

15. The system of claim 11 , wherein the likelihood is calculated based the multinomial operating as a function of the tumor genotype.

16. The system of claim 11 , wherein the likelihood is calculated based the multinomial operating as a function of the matched normal genotype.

17. The system of claim 11 , wherein the first and the second differences are selected from the group consisting of: a somatic variant, a germline variant, a single nucleotide polymorphism, an allele-specific copy number, a loss of heterozygosity, a structural rearrangement, a chromosomal fusion, a mutation, and a breakpoint.

18. The system of claim 11 , wherein the reads associated with the tumor tissue form a tumor pileup and the reads associated with the matched normal tissue form a matched normal pileup.

19. The system of claim 11 , wherein the sequence analysis engine is further configured to identify false positives.

20. The system of claim 19 , wherein the false positives are determined based on at least one of the following distributions: a strand distribution, and an allele position distribution.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Aug 21, 2018
From: SANBORN, JOHN ZACHARY; HAUSSLER, DAVID
To: THE REGENTS OF THE UNIVERSITY OF CALIFORNIA
Reel/Frame 046654/0415 →
Continuity (5)
Continuation 15634919 · Jun 27, 2017
Continuation 15167530 · May 27, 2016
Continuation 13134047 · May 25, 2011
Provisional Application 61396356 · May 25, 2010
Related Publication 20180357371A1 · Dec 13, 2018
Cited By (1)
US 12,347,526