Patent Document ID: 10133843
Application ID: 13688133
Patent Flag: 1

Claim One:
1. A method of automatically removing a step discontinuity in data representing a Polymerase Chain Reaction (PCR) growth process, the method comprising: detecting, with a PCR system, intensity values of signals generated using a biological and/or chemical reaction sample undergoing the PCR growth process, at a plurality of growth cycles of the PCR growth process; receiving, by a computer system communicatively coupled to the PCR system, a dataset representing the PCR growth process, the dataset including a plurality of data points, each data point having a pair of coordinate values, wherein the pair of coordinate values correspond to a cycle number of the PCR growth process and an intensity value of a signal generated using the biological and/or chemical reaction sample and detected by the PCR system after a growth cycle corresponding to the cycle number; calculating, by the computer system, a first approximation of a curve that fits the dataset by applying a first non-linear regression process to a first non-linear function to determine parameters of the first non-linear function, said parameters including a first step discontinuity parameter that represents a magnitude of the step discontinuity, the first non-linear function including the first step discontinuity parameter multiplying a step function; calculating, by the computer system, a second approximation of a curve that fits the dataset by applying a second regression process to a second non-linear function to determine parameters of the second non-linear function, said parameters of the second non-linear function including a second step discontinuity parameter that represents the magnitude of the step discontinuity, the second non-linear function including the second step discontinuity parameter multiplying a step function, wherein the second non-linear function is different from the first non-linear function; determining, by the computer system, an information coefficient for each of the first and second approximations, each information coefficient indicating an accuracy of a fit of the corresponding approximation to the dataset; selecting, by the computer system, one of the approximations based on the information coefficient, the selected approximation providing a best fit to the dataset; determining, by the computer system, a confidence interval of the step discontinuity parameter for the selected approximation; if the confidence interval does not include the value zero, replacing, by the computer system, a portion of the dataset with the selected approximation with the corresponding step discontinuity parameter set to zero, wherein the method is implemented in a computer system having a processor; and determining, by the computer system, a quantity of a target molecule in the biological and/or chemical reaction sample by determining a cycle threshold (C t ) value using the dataset.