METHODS, SYSTEMS, AND COMPUTER READABLE MEDIA FOR NUCLEIC ACID SEQUENCING

• US 20120173159A1
• Filed: 12/29/2011
• Published: 07/05/2012
• Est. Priority Date: 12/30/2010
• Status: Active Grant

• Current Assignee: Life Technologies Corporation (Thermo Fisher Scientific Incorporated)
• Original Assignee: Life Technologies Corporation (Thermo Fisher Scientific Incorporated)
• Inventors: DAVEY, Melville, CAWLEY, Simon, WILLIAMS, Alan
• Granted Patent: US 10,241,075 B2
• Time in Patent Office: Days
• US Class Current: 702/20
• CPC Class Codes: G01N 27/27 Association of two or more measuring systems or cells, each measuring a different parameter, where the measurement results may be either used independently, the systems or cells being physically associated, or combined to produce a value for a further parameter
• CPC Class Codes: G01N 27/4145 specially adapted for biomolecules, e.g. gate electrode with immobilised receptors
• 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

Abstract

A method for nucleic acid sequencing includes receiving a plurality of signals indicative of a parameter measured for a plurality of defined spaces, at least some of the defined spaces including one or more sample nucleic acids, the signals being responsive to a plurality of nucleotide flows introducing nucleotides to the defined spaces; determining, for at least some of the defined spaces, whether the defined space includes a sample nucleic acid; processing, for at least some of the defined spaces determined to include a sample nucleic acid, the received signals to improve a quality of the received signals; and predicting a plurality of nucleotide sequences corresponding to respective sample nucleic acids for the defined spaces based on the processed signals and the nucleotide flows.

Claims

1. A method for nucleic acid sequencing, comprising:

receiving a plurality of signals indicative of a parameter measured for a plurality of defined spaces, at least some of the defined spaces comprising one or more sample nucleic acids, the signals being responsive to a plurality of nucleotide flows introducing nucleotides to the defined spaces;

determining, for at least some of the defined spaces, whether the defined space comprises a sample nucleic acid;

processing, for at least some of the defined spaces determined to comprise a sample nucleic acid, the received signals to improve a quality of the received signals; and

predicting a plurality of nucleotide sequences corresponding to respective sample nucleic acids for the defined spaces based on the processed signals and the nucleotide flows.

2. The method of claim 1, wherein, in the receiving step, the parameter measured for the defined spaces comprises a voltage measurement indicative of hydrogen ion concentration for respective defined spaces.

3. The method of claim 1, wherein at least some of the defined spaces comprise a sample nucleic acid directly or indirectly coupled to a particle.

4. The method of claim 1, wherein at least some of the defined spaces comprise a sample nucleic acid directly or indirectly coupled to a surface of the defined space.

5. The method of claim 1, wherein the defined spaces comprise microwells associated with sensors formed from an integrated circuit chip.

6. The method of claim 1, wherein the determining step comprises evaluating a difference between a first rate of change in an hydrogen ion concentration for the defined space measured for a first solution having a first pH and a second rate of change in the hydrogen ion concentration for the defined space measured for a second solution having a second pH different from the first pH.

7. The method of claim 1, wherein the determining step comprises comparing a rate of change in an hydrogen ion concentration for the defined space measured for a solution having a given pH with a modeled rate of change for the defined space not containing a sample nucleic acid.

8. The method of claim 1, wherein the determining step comprises evaluating, for at least some of the defined spaces determined to comprise a sample nucleic acid, whether the signals for the defined space are informative or non-informative.

9. The method of claim 8, wherein the determining step comprises evaluating, for at least some of the defined spaces determined to comprise a sample nucleic acid and to be informative, whether the defined space comprises a library fragment, a test fragment, or an ambiguous fragment.

10. The method of claim 9, wherein the determining step comprises comparing a flow-space incorporation vector derived from a portion of the signals responsive to a set of initial nucleotide flows for the defined space with at least two pre-defined vectors.

11. The method of claim 10, wherein the at least two pre-defined vectors comprise:

a library fragment flow-space vector that would be expected to result if a pre-defined library fragment key sequence were subjected to the initial nucleotide flows; and

a test fragment flow-space vector that would be expected to result if a pre-defined test fragment key sequence were subjected to the initial nucleotide flows.

12. The method of claim 11, wherein the library fragment flow-space vector and the test fragment flow-space vector are orthogonal under the set of initial nucleotide flows with respect to at least two nucleotides selected from nucleotides A, C, G, and T.

13. The method of claim 11, wherein the library fragment flow-space vector and the test fragment flow-space vector are orthogonal under the set of initial nucleotide flows with respect to at least three nucleotides selected from nucleotides A, C, G, and T.

14. The method of claim 1, wherein the processing step comprises modifying the signals to remove noise, the noise being evaluated based at least partly on signals for defined spaces determined not to comprise a sample nucleic acid.

15. The method of claim 1, wherein the predicting step comprises:

normalizing the processed signals;

estimating, for at least some of the defined spaces determined to comprise a sample nucleic acid, a number of nucleotide incorporations that occurred in the defined space as a result of each of the nucleotide flows based on the normalized processed signals; and

compiling the estimated numbers of nucleotide incorporations for the nucleotide flows into one or more sequences of consecutive base calls for the sample nucleic acid to form one or more reads.

16. The method of claim 15, wherein the number of nucleotide incorporations is selected for each of the nucleotide flows from the group consisting of zero, one, two, and any other positive integer.

17. The method of claim 15, wherein the predicting step comprises:

generating a quality metric for the base calls and for the reads; and

filtering out from the one or more reads at least one of;

any read that contains at least a threshold number of base calls failing to meet a minimal threshold of base call quality, and

any read that fails to meet a minimal threshold of read quality.

18. The method of claim 15, wherein the predicting step comprises generating a quality score for at least some of the base calls forming at least a portion of the one or more reads.

19. The method of claim 18, wherein the generating step comprises calculating at least a first quality predictor value and a second quality predictor value for each base call, the first and second quality predictor values including a phase error and at least one other parameter selected from the group consisting of base position, local noise, read noise, multiple incorporations, and environment noise;

comparing the calculated first quality predictor value and the calculated second quality predictor value to a pre-defined quality metric; and

assigning a quality score to the at least some of the base calls based at least partly upon the comparison.

20. The method of claim 18, wherein the predicting step comprises:

removing from the at least some of the base calls forming at least a portion of the one or more reads at least one of;

any base call identified as having a quality score below a quality score threshold, and

an adapter sequence; and

filtering out from the at least a portion of the one or more reads at least one of;

any read identified as a mixed template read, and

any read identified as having a median absolute residual value greater than a residual threshold value, thereby generating a filtered set of reads.

21. The method of claim 20, wherein the predicting step comprises aligning the filtered set of reads to predict a sample nucleic acid sequence assembled from the filtered set of reads for the sample nucleic acids.

22. The method of claim 15, wherein the predicting step comprises aligning the one or more reads to predict a sample nucleic acid sequence assembled from the one or more reads for the sample nucleic acids.

23. The method of claim 1, comprising transmitting, displaying, storing, printing or outputting to a user interface device, a computer readable storage medium, a local computer system or a remote computer system, information related to the predicted nucleotide sequences of the sample nucleic acids or other parameters, predictions, or data generated or used by the method.

24. A non-transitory machine-readable storage medium comprising instructions which, when executed by a processor, cause the processor to perform a method for nucleic acid sequencing comprising:

receiving a plurality of signals indicative of a parameter measured for a plurality of defined spaces, at least some of the defined spaces comprising one or more sample nucleic acids, the signals being responsive to a plurality of nucleotide flows introducing nucleotides to the defined spaces;

determining, for at least some of the defined spaces, whether the defined space comprises a sample nucleic acid;

processing, for at least some of the defined spaces determined to comprise a sample nucleic acid, the received signals to improve a quality of the received signals; and

predicting a plurality of nucleotide sequences corresponding to respective sample nucleic acids for the defined spaces based at least partly on the processed signals and the nucleotide flows.

25. The non-transitory machine-readable storage medium of claim 24, wherein the predicting step comprises:

normalizing the processed signals;

estimating, for at least some of the defined spaces determined to comprise a sample nucleic acid, a number of nucleotide incorporations that occurred in the defined space as a result of each of the nucleotide flows based at least partly on the normalized processed signals; and

compiling the estimated numbers of nucleotide incorporations for the nucleotide flows into one or more sequences of consecutive base calls for the sample nucleic acid to form one or more reads.

26. The non-transitory machine-readable storage medium of claim 25, wherein the predicting step comprises:

generating a quality metric for the base calls and for the reads; and

filtering out from the one or more reads at least one of;

any read that contains at least a threshold number of base calls failing to meet a minimal threshold of base call quality, and

any read that fails to meet a minimal threshold of read quality.

27. The non-transitory machine-readable storage medium of claim 25, wherein the predicting step comprises generating a quality score for at least some of the base calls forming at least a portion of the one or more reads.

28. The non-transitory machine-readable storage medium of claim 26, wherein the predicting step comprises:

removing from the at least some of the base calls forming at least a portion of the one or more reads at least one of;

any base call identified as having a quality score below a quality score threshold, and

an adapter sequence; and

filtering out from the at least a portion of the one or more reads at least one of;

any read identified as a mixed template read, and

any read identified as having a median absolute residual value greater than a residual threshold value, thereby generating a filtered set of reads.

29. The non-transitory machine-readable storage medium of claim 28, wherein the predicting step comprises aligning the filtered set of reads to predict a sample nucleic acid sequence assembled from the filtered set of reads for the sample nucleic acids.

30. A system, comprising:

a machine-readable memory; and

a processor configured to execute machine-readable instructions, which, when executed by the processor, cause the system to perform steps including;

receiving a plurality of signals indicative of a parameter measured for a plurality of defined spaces, at least some of the defined spaces comprising one or more sample nucleic acids, the signals being responsive to a plurality of nucleotide flows introducing nucleotides to the defined spaces;

determining, for at least some of the defined spaces, whether the defined space comprises a sample nucleic acid;

processing, for at least some of the defined spaces determined to comprise a sample nucleic acid, the received signals to improve a quality of the received signals; and

predicting a plurality of nucleotide sequences corresponding to respective sample nucleic acids for the defined spaces based at least partly on the processed signals and the nucleotide flows.