Systems And Methods For Model-Based qPCR

Patent metadata

Field	Value
Publication number	US-2016110495-A1
Application number	US-201514921948-A
Country	US
Kind code	A1
Filing date	Oct 23, 2015
Priority date	Apr 11, 2010
Publication date	Apr 21, 2016
Grant date	—

Abstract

A method for determining a cycle threshold for a PCR amplification curve is provided. The method includes receiving a data set for a plurality of biological samples for a PCR amplification reaction. The data set includes a plurality of amplification curves, each amplification curve associated with a biological sample of the plurality of biological samples. The method further includes performing a nonlinear optimization comprising a fit of each amplification curve to a complementary modeled amplification curve to determine a best-fit set of parameters for a modeled efficiency curve and associated amplification curve. The modeled amplification curve is based on a modeled efficiency curve. The method includes determining a cycle threshold value for each biological sample based on a complementary relationship of the modeled efficiency curve to the modeled amplification curve. In an embodiment, the nonlinear optimization is a constrained nonlinear optimization.

First claim

1 . A method for determining a cycle threshold for a PCR amplification curve, the method comprising:
receiving a data set for a plurality of biological samples for a PCR amplification reaction, wherein the data set includes a plurality of amplification curves, each amplification curve associated with a biological sample of the plurality of biological samples; and displaying, on a computer display, a modeled amplification curve and a cycle threshold value for each biological sample, wherein each cycle threshold value is determined by a processor based on a complementary relationship of a modeled efficiency curve to the modeled amplification curve for each sample, wherein each modeled amplification curve is determined and generated by a processor using the associated modeled efficiency curve on a cycle-by-cycle basis, wherein each modeled efficiency curve is determined and generated by a processor using a nonlinear optimization.

2 . The method of claim 1 , wherein the nonlinear optimization is a constrained non-linear optimization.

3 . The method of claim 1 , further comprising:
generating the modeled efficiency curve based on the best-fit set of parameters; and generating the associated amplification curve based on the modeled efficiency curve.

4 . The method of claim 1 , wherein the modeled efficiency curve is explicitly modeled, and the modeled amplification curve is implicitly modeled based on the explicitly modeled efficiency curve.

5 . The method of claim 3 , wherein determining the cycle threshold value is based on a predetermined efficiency parameter value.

6 . The method of claim 1 , further comprising identifying non-amplified samples.

7 . The method of claim 6 , wherein the identifying non-amplified samples comprises performing a test selected from the group consisting of: threshold amplification, model curve fit, noise threshold, maximum cycle, minimum cycle, end-point amplification, model efficiency threshold, minimum noise, relative noise, relative scaling, or drop-off.

8 . The method of claim 1 , further comprising:
generating baselined model amplification curves based on the best-fit set of parameters, wherein the cycle threshold determination is based on the complementary relationship between the baselined model amplification curves and corresponding efficiency curve.

9 . The method of claim 1 , wherein the best-fit set of parameters for the modeled efficiency curve comprises three parameters.

10 . The method of claim 9 , wherein the three best-fit set of parameters are a curve shift parameter, a curve bend parameter, and a curve shift adjustment parameter.

11 - 19 . (canceled)

20 . A system for determining a cycle threshold for a PCR amplification curve, the system comprising:
a processor; and a memory storing instructions executable by the processor, the instructions comprising instructions for:
receiving a data set for a plurality of biological samples for a PCR amplification reaction, wherein the data set includes a plurality of amplification curves, each amplification curve associated with a biological sample of the plurality of biological samples; and
displaying, on a computer display, a modeled amplification curve and a cycle threshold value for each biological sample, wherein each cycle threshold value is determined by a processor based on a complementary relationship of a modeled efficiency curve to the modeled amplification curve for each sample, wherein each modeled amplification curve is determined and generated by a processor using the associated modeled efficiency curve on a cycle-by-cycle basis, wherein each modeled efficiency curve is determined and generated by a processor using a nonlinear optimization.

21 . The system of claim 20 , wherein the nonlinear optimization is a constrained non-linear optimization.

22 . The system of claim 20 , wherein the memory further stores instructions for:
generating the modeled efficiency curve based on the best-fit set of parameters; and generating the associated amplification curve based on the modeled efficiency curve.

23 . The system of claim 20 , wherein the modeled efficiency curve is explicitly modeled, and the modeled amplification curve is implicitly modeled based on the explicitly modeled efficiency curve.

24 . The system of claim 22 , wherein determining the cycle threshold value is based on a predetermined efficiency parameter value.

25 . The system of claim 20 , wherein the memory further stores instructions for identifying non-amplified samples.

26 . The system of claim 25 , wherein the identifying non-amplified samples comprises performing a test selected from the group consisting of: threshold amplification, model curve fit, noise threshold, maximum cycle, minimum cycle, end-point amplification, model efficiency threshold, minimum noise, relative noise, relative scaling, or drop-off.

27 . The system of claim 20 , wherein the memory further stores instructions for:
generating baselined model amplification curves based on the best-fit set of parameters, wherein the cycle threshold determination is based on the complementary relationship between the baselined model amplification curves and corresponding efficiency curve.

28 . The system of claim 20 , wherein the best-fit set of parameters for the modeled efficiency curve comprises three parameters.

29 . The system of claim 28 , wherein the three best-fit set of parameters are a curve shift parameter, a curve bend parameter, and a curve shift adjustment parameter.

Assignees

• Life Technologies Corp

Inventors

• George Wallace R

Classifications

• C12Q1/6851

  Quantitative amplification · CPC title

• G16B40/00

  ICT specially adapted for biostatistics; ICT specially adapted for bioinformatics-related machine learning or data mining, e.g. knowledge discovery or pattern finding · CPC title

• G06F19/12 Primary

  Physics · mapped topic

• G16B40/10

  Signal processing, e.g. from mass spectrometry [MS] or from PCR · CPC title

• G16B25/20 Primary

  Polymerase chain reaction [PCR]; Primer or probe design; Probe optimisation · CPC title