IP Library Granted Patent US 7,228,237
Granted Patent B2
US 7,228,237 · App. 10/152,280 · Granted Jun 5, 2007

Automatic threshold setting and baseline determination for real-time PCR

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 7,228,237
App. No.
10/152,280
Granted
Jun 5, 2007
Kind
B2
Abstract

The invention discloses a system and methods for quantitating the presence of nucleic acid sequences by evaluation of amplification data generated using real-time PCR. In one aspect, the methods may be adapted to identify a threshold and threshold cycle for one or more reactions based upon evaluation of exponential and baseline regions for each amplification reaction. The methodology used in the analysis may be readily automated such that subjective user interpretation of the data is substantially reduced or eliminated.

Claims (52)

1. A method for target sequence quantitation, the method comprising:

amplifying a plurality of target sequences by PCR in the presence of a detectable reporter construct;

acquiring signal information for each target sequence associated with the detectable reporter construct;

evaluating the signal information and identifying an exponential region associated with substantial increases in the signal information for each target sequence amplification wherein each identified exponential region comprises an associated upper and lower bound;

identifying a baseline component for the signal information associated with each target sequence amplification and normalizing the signal information for each target sequence amplification using the baseline component;

determining an exponential region threshold based upon a comparison of the exponential regions far each target sequence amplification wherein the associated upper and lower bounds the identified exponential regions are evaluated in the comparison of the exponential regions, wherein the determining further comprises:

identifying a minimal upper bound from the exponential region upper bounds;

identifying a maximal lower bound from the exponential region lower bounds;

determining the intersection region between the minimal upper bound and the maximal lower bound and determining the value of the smallest upper bound of the ordered set as the exponential region threshold for the data set; and

if no intersection region is identified, discarding a target sequence amplification from the signal information and re-identifying the exponential region upper bound and the exponential region lower bound until an intersection is identified;

identifying a threshold cycle for each target sequence amplification determined as the root of a polynomial identified using the exponential region threshold; and

quantifying each target sequence using the threshold cycle.

2. The method of claim 1 , wherein identification of the exponential region upper bound for the signal information associated with each target sequence amplification comprises performing a derivative operation using the signal information for each target sequence amplification.

3. The method of claim 2 , wherein the derivative operation further comprises obtaining the second derivative for the signal information for each target sequence amplification.

4. The method of claim 1 , wherein identification of the exponential region lower bound for the signal information associated with each target sequence amplification comprises assessing incremental differences in the signal information for each target sequence amplification and comparing the incremental differences to a selected difference value.

5. The meted of claim 1 , wherein normalizing the signal information for each target sequence amplification using the baseline component further comprises:

identifying a baseline region based on the exponential region lower bound and performing a regression analysis of the baseline region to generate a characteristic equation; and

differencing the baseline component using the characteristic equation to obtain the normalized signal information.

6. The method of claim 1 , wherein identifying the polynomial further comprises:

performing a data smoothing operation over a selected number of cycles including the threshold cycle of the exponential region threshold to identify a threshold equation;

factoring the threshold equation to identify a real root; and

associating the real root with the threshold cycle.

7. The method of claim 6 , wherein the data smoothing operation comprises a Savitzky-Golay smoothing operation.

8. The method of claim 1 , wherein identifying the polynomial further comprises:

performing a curve fitting operation over a selected number of cycles including the threshold cycle of the exponential region threshold to identify a threshold equation;

factoring the threshold equation to identify a real root; and

associating the real root with the threshold cycle.

9. The method of claim 8 , wherein identifying the polynomial further comprises solving the roots of a polynomial generated by Savitzky-Golay smoothing operation.

10. A system for target polynucleotide quantitation, the system comprising:

a reaction module for amplifying target polynucleotides using a detectable reporter label;

a data collection module that detects reporter label intensities during target polynucleotide amplification,

a data processing module configured to:

receive the detected reporter label intensities for each target polynucleotide amplification;

evaluate the detected reporter label intensities to identify an exponential region associated with a substantial increase in the detected reporter label intensity for each target polynucleotide amplification wherein each identified exponential region comprises an associated upper and lower bound;

identify a baseline component for each target polynucleotide amplification;

normalize the exponential region for each target polynucleotide using the baseline component;

identify an exponential region threshold by collectively comparing the exponential regions for each target polynucleotide wherein the associated upper and lower bounds for identified exponential regions are evaluated in the comparison of the exponential regions, wherein the identification of the exponential region threshold further comprises:

identifying a minimal upper bound from the exponential region upper bounds,

identifying a maximal lower bound from the exponential region tower bounds,

determining the intersection region between the minimal upper bound and the maximal lower bound and determining the value of the smallest upper bound of the ordered set as the exponential region threshold for the data set; and

if no intersection region is identified, discarding a target polynucleotide amplification of the signal information and re-identifying the exponential region upper bound and the exponential region lower bound until an intersection is identified;

identify a threshold cycle for each target polynucleotide amplification based upon the exponential region threshold; and

quantitate each target polynucleotide using the threshold cycle.

11. The system of claim 10 , wherein the data processing module identifies the upper bound associated with the exponential region for each target polynucleotide amplification using a derivatization operation applied to the detected reporter label intensities.

12. The system of claim 11 , wherein the derivatization operation comprises obtaining the second derivative of the detected reporter label intensities.

13. The system of claim 10 , wherein the data processing module identifies the lower bound associated with the exponential region for each target polynucleotide amplification through assessment of incremental data differences between selected detected reporter label intensities compared to a selected difference value.

14. The system of claim 13 , wherein the data processing module is further configured to:

identify a baseline region bounded by the lower bound;

generate the baseline component for the baseline region by performing a regression analysis of the detected intensities in the baseline region; and

apply the baseline component to the detected reporter label intensifies to normalize them.

15. The system of claim 10 , wherein the data processing module identifies the threshold cycle as the root of a polynomial for each of the exponential regions for the target polynucleotides.

16. The system of claim 15 , wherein the polynomial root is determined by solving the roots of a polynomial generated by a Savitzky-Golay smoothing operation.

Assignments (9)
CORRECTIVE ASSIGNMENT TO CORRECT THE RECEIVING PARTY NAME PREVIOUSLY RECORDED AT REEL: 030182 FRAME: 0677. ASSIGNOR(S) HEREBY CONFIRMS THE RELEASE OF SECURITY INTEREST. Recorded Mar 4, 2016
From: BANK OF AMERICA, N.A.
To: APPLIED BIOSYSTEMS, LLC
Reel/Frame 038002/0175 →
LIEN RELEASE Recorded Apr 9, 2013
From: BANK OF AMERICA, N.A.
To: APPLIED BIOSYSTEMS, INC.
Reel/Frame 030182/0677 →
CHANGE OF NAME Recorded Feb 26, 2010
From: APPLERA CORPORATION
To: APPLIED BIOSYSTEMS INC.
Reel/Frame 023994/0538 →
MERGER Recorded Feb 26, 2010
From: APPLIED BIOSYSTEMS INC.
To: APPLIED BIOSYSTEMS, LLC
Reel/Frame 023994/0587 →
MERGER Recorded Dec 15, 2009
From: ATOM ACQUISITION, LLC & APPLIED BIOSYSTEMS INC.
To: APPLIED BIOSYSTEMS, LLC
Reel/Frame 023649/0586 →
CHANGE OF NAME Recorded Dec 15, 2009
From: APPLERA CORPORATION
To: APPLIED BIOSYSTEMS INC.
Reel/Frame 023649/0567 →
MERGER Recorded Dec 15, 2009
From: ATOM ACQUISITION CORPORATION
To: APPLIED BIOSYSTEMS, INC.
Reel/Frame 023649/0573 →
SECURITY AGREEMENT Recorded Dec 5, 2008
From: APPLIED BIOSYSTEMS, LLC
To: BANK OF AMERICA, N.A, AS COLLATERAL AGENT
Reel/Frame 021976/0001 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Sep 30, 2002
From: WOO, DAVID; LEWIS, CLINTON; ABBASI, NASSER M.
To: APPLERA CORPORATION
Reel/Frame 013327/0109 →