Methods and apparatuses for estimating parameters in a predictive model for use in sequencing-by-synthesis

• US 10,273,540 B2
• Filed: 08/15/2013
• Issued: 04/30/2019
• Est. Priority Date: 10/27/2010
• Status: Active Grant

• Current Assignee: Life Technologies Corporation (Thermo Fisher Scientific Incorporated)
• Original Assignee: Life Technologies Corporation (Thermo Fisher Scientific Incorporated)
• Inventors: Davey, Melville, Meyer, Michael, Sikora, Marcin, Cawley, Simon, Pastorian, Kirk
• Primary Examiner(s): Brusca, John S
• Application Number:
  US13/967,665
• Publication Number:
  US 20140051584A1
• Time in Patent Office: 2,084 Days
• Field of Search: None
• CPC Class Codes: C12Q 1/6874 involving nucleic acid arrays, e.g. sequencing by hybridisation
• CPC Class Codes: C12Q 2537/165 Mathematical modelling, e.g. logarithm, ratio
• CPC Class Codes: G16B 30/00 ICT specially adapted for sequence analysis involving nucleotides or amino acids
• CPC Class Codes: G16B 99/00 Subject matter not provided for in other groups of this subclass

Abstract

A method of estimating a parameter related to sequencing of a sample nucleic acid template includes: receiving signal data relating to nucleotide incorporation events resulting from a series of flows of nucleotides onto an array of wells including (i) a first well containing the sample nucleic acid template and (ii) a plurality of other sample-containing wells; determining sequence information for the sample nucleic acid template using signal data from the first well; and constructing a phase-state model for a set of nucleotide flows that contributed at least in part to the sequence information, wherein the model includes a signal correction parameter that is determined using signal data from the plurality of other sample-containing wells.

Claims

1. A method of estimating a parameter related to sequencing of a sample nucleic acid template, comprising:

(a) measuring signal data relating to nucleotide incorporation events resulting from a series of flows of nucleotides onto a sensor array comprising a plurality of regions of wells, at least one of the regions of wells comprising;

(i) a first set of wells including a first well containing the sample nucleic acid template and (ii) a second set of wells including a plurality of other sample-containing wells, wherein the first set of wells and the second set of wells are physically distinguishable from each other by shape or dimension;

(b) determining sequence information for the sample nucleic acid template using signal data from the first well containing the sample nucleic acid template;

(c) constructing a phase-state model for a set of nucleotide flows that contributed at least in part to the sequence information, wherein the model includes a signal correction parameter that is determined using signal data from the plurality of other sample-containing wells, and wherein the model is stored in a machine-readable memory;

(d) calculating, using the phase-state model, predicted signals for the plurality of other sample-containing wells resulting from the set of nucleotide flows;

(e) comparing the predicted signals to the signal data from the plurality of other sample-containing wells;

(f) fitting the signal correction parameter of the phase-state model based on the comparison of the predicted signals to the signal data from the plurality of other sample-containing wells; and

(g) storing the fitted signal correction parameter in the memory.

2. The method of claim 1, wherein the signal correction parameter is obtained using signal data obtained from at least a portion of the plurality of other sample-containing wells and without using signal data obtained from the first well.

3. The method of claim 1, wherein the signal correction parameter is obtained using signal data obtained from at least a portion of the plurality of other sample-containing wells and signal data obtained from the first well.

4. The method of claim 1, further comprising:

performing steps (b) through (g) for each of the obtained signal data from each or some of the plurality of other sample-containing wells to obtain multiple fitted signal correction parameters, wherein each of the multiple fitted signal correction parameters is determined for a given well without using signal data from that given well.

5. The method of claim 4, wherein the comparing step comprises calculating a fitting metric that measures the fit between the predicted signals and the signal data.

6. The method of claim 1, wherein the phase-state model includes two or more signal correction parameters, including a carry forward rate and an incomplete extension rate.

7. The method of claim 1, wherein the comparing step comprises calculating a fitting metric that measures a fit between the predicted signals and the signal data.

8. The method of claim 7, wherein the fitting step comprises determining a value of the signal correction parameter that optimizes the fitting metric.

9. The method of claim 7, wherein the fitting step comprises determining a value of the signal correction parameter using Nelder-Mead optimization.

10. The method of claim 8, wherein the fitting metric is calculated using only nucleotide flows that result in nucleotide non-incorporation or single nucleotide incorporations.

11. The method of claim 1, further comprising performing a base calling analysis of the signal data using the fitted signal correction parameter.

12. The method of claim 1, wherein the set of nucleotide flows is a first set of nucleotide flows and the sequence information is a first sequence information, and further comprising:

applying the phase-state model using the fitted signal correction parameter;

calculating, using the phase-state model and the fitted signal correction parameter obtained using signal data from the plurality of other sample-containing wells, predicted signals for the first well resulting from a second set of nucleotide flows that includes nucleotide flows that are not in the first set of nucleotide flows;

making base calls by comparing the signal data from the first well to the predicted signals for the first well; and

obtaining a second sequence information about the sample nucleic acid template, wherein the second sequence information includes sequence information not contained in the first sequence information.

13. The method of claim 12, further comprising repeating steps (d) through (g) using the second sequence information to obtain a further fitted signal correction parameter.