Method for automatically and quickly judging fluorescent quantitative PCR (Polymerase Chain Reaction) result

Abstract

The invention relates to a method for automatically and quickly judging a fluorescent quantitative PCR (Polymerase Chain Reaction) result. The method comprises the steps of extracting a data curve of a fluorescent quantitative PCR; performing baseline setting on the data curve; setting a standard threshold of the fluorescence intensity during an exponential rise period of the data curve, wherein a cycle number corresponding to the standard threshold is Ct1; setting an auxiliary threshold of the fluorescence intensity during the exponential rise period of the data curve, wherein a cycle number corresponding to the auxiliary threshold is Ct2 and the standard threshold is not equal to the auxiliary threshold; establishing a scoring formula z (z=(Ct1-Ct2) / (log(the standard threshold, 2)-log(the auxiliary threshold, 2)); and if z is more than 0 and less than (1 / E)+1, judging that the data curve is a normal curve, or otherwise, judging that the data curve is an abnormal curve, wherein E is a fluorescent quantitative PCR efficiency value. By designing a brand-new identification method, fluorescent quantitative PCR test data can be quickly and accurately judged, so that the judgment speed of detection data is increased and the judgment accuracy of the detection data is improved.

Description

technical field [0001] The invention belongs to the field of biological analysis, in particular to a method for automatically and quickly distinguishing the results of fluorescent quantitative PCR. Background technique [0002] Fluorescent quantitative PCR (PCR: Polymerase Chain Reaction) is a quantitative experimental technology that uses fluorescent dyes or fluorescent-labeled specific probes to mark and track PCR products and monitor the reaction process online in real time. The data analysis process of fluorescent quantitative PCR is generally as follows: [0003] (1) Baseline setting: usually, choose automatic analysis, at this time, the machine will optimize the analysis for each curve, so the effect is usually better. If some abnormally shaped curves appear on the basis of the automatic baseline analysis, the baseline analysis needs to be adjusted manually. [0004] (2) Threshold value setting: The threshold value can also be set automatically or manually. The inter...

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Problems solved by technology

[0005] However, in the actual data analysis process, due to factors such as edge effects and unclean sample processing, some amplification curves have abnormal shapes, and the obtained Ct values ​​are not credible, and subsequent analysis cannot be performed.

When it is necessary to use the same PCR reaction system (including reaction mixture formula, thermal cycle conditions, instrument equipment and data analysis conditions, such as baseline settings and Ct threshold, etc.) to detect a large number of similar experimental subjects, manually confirm whether the curves are Normally, it will consume a lot of time and greatly reduce the efficiency of the experiment

Especially when fluorescent quantitative PCR is applied to clinical molecular diagnosis, the clinical report is generally given directly through the Ct value. If the abnormal curve is not eliminated by directly observing the amplification curve, the possible abnormal curve will cause inaccurate clinical test results. letter, and even lead to serious consequences of misdiagnosis or missed diagnosis

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