A data sifting method applied to a growth type curve including a plurality of data points, and includes: calculating a plurality of first derivative values corresponding to the data points; searching at least one local maximum value from the first derivative values; determining whether a part of the first derivative values adjacent to the at least one local maximum value are all positive; determining one of the first derivative values after a predetermined effective cycle number or the at least one local maximum value as a target maximum value according to a determination result; deriving a basic cycle number according to a target cycle number corresponding to the target maximum value; and setting a baseline of the growth type curve according to the basic cycle number to calculate a first Cq value according to the adjusted growth type curve. The present disclosure further provides a data sifting apparatus.

The invention provides methods, systems, and computer readable medium for detecting ploidy of chromosome segments or entire chromosomes, for detecting single nucleotide variants and for detecting both ploidy of chromosome segments and single nucleotide variants. In some aspects, the invention provides methods, systems, and computer readable medium for detecting cancer or a chromosomal abnormality in a gestating fetus.

An improved diagnostic assay and methods relating to the same that are directed to mutation focused disease diagnosis and surveillance biomarker panels wherein potential genomic regions are selected based on their ability to encompass the genomic diversity of a patient population, maximize the number of unique markers monitored within each patient are maximized while balancing these factors with empirical sequencing performance, geographic clustering of events with a region across diverse patients, and size and cost associated with measuring the respective genomic region. The methods also include quality control steps to reduce noise and

An improved diagnostic assay and methods relating to the same that are directed to mutation focused disease diagnosis and surveillance biomarker panels wherein potential genomic regions are selected based on their ability to encompass the genomic diversity of a patient population, maximize the number of unique markers monitored within each patient are maximized while balancing these factors with empirical sequencing performance, geographic clustering of events with a region across diverse patients, and size and cost associated with measuring the respective genomic region. The methods also include quality control steps to reduce noise and

Disclosed herein are systems and methods for multiplex primer design and selection. In one example, a system includes non-transitory memory configured to store executable instructions; and a hardware processor programmed by the executable instructions to receive a plurality of target gene sequences and determine a set of primers for each target gene sequence based on a penalty score associated with the set of primers, wherein the penalty score is based on a non-linear combination of a primer-level penalty score and a set-level penalty score.

The disclosure relates to a method for operating a quantitative polymerase chain reaction (qPCR) method, having the following steps: cyclically carrying out qPCR cycles; measuring the fluorescence in each qPCR cycle in order to obtain a qPCR curve of intensity values; determining the reaction efficiency (η) for each cycle; correcting the intensity value of each cycle on the basis of the reaction efficiency (η) determined for the cycle in question in order to obtain a corrected qPCR curve; and operating the qPCR method on the basis of the corrected qPCR curve.

The disclosure relates to a method for operating a quantitative polymerase chain reaction (qPCR) method, having the following steps: cyclically carrying out qPCR cycles; measuring the fluorescence in each qPCR cycle in order to obtain a qPCR curve of intensity values; determining the reaction efficiency (η) for each cycle; correcting the intensity value of each cycle on the basis of the reaction efficiency (η) determined for the cycle in question in order to obtain a corrected qPCR curve; and operating the qPCR method on the basis of the corrected qPCR curve.

The disclosure relates to a computer-implemented method for carrying out a quantitative polymerase chain reaction (qPCR) process, comprising the following steps: —cyclically carrying out qPCR cycles; —measuring an intensity value of a fluorescence relating to each qPCR cycle to obtain a qPCR curve from intensity values; —analyzing the shape of the qPCR curve using a data-based classification model trained to provide a classification result depending on the shape of the qPCR curve; and—carrying out the qPCR process depending on the classification result of the analysis of the shape of the qPCR curve.

The disclosure relates to a method for carrying out a quantitative polymerase chain reaction (qPCR) process, comprising the following steps:—cyclically carrying out qPCR cycles; —measuring the fluorescence for each qPCR cycle to obtain a qPCR curve of intensity values (I); —creating a probability density function (PDF) from the intensity values (I); —establishing a presence or absence of the DNA strand section to be detected depending on the presence of one or more features of the probability density function (PDF); —carrying out the qPCR process depending on the presence or absence of the DNA strand section to be detected.

The disclosure relates to a method for carrying out a quantitative polymerase chain reaction (qPCR) process, comprising the following steps:—cyclically carrying out qPCR cycles; —measuring the fluorescence for each qPCR cycle to obtain a qPCR curve of intensity values (I); —creating a probability density function (PDF) from the intensity values (I); —establishing a presence or absence of the DNA strand section to be detected depending on the presence of one or more features of the probability density function (PDF); —carrying out the qPCR process depending on the presence or absence of the DNA strand section to be detected.