# Understanding the qPCR Standard Curve: From Assay Validation to Absolute Quantification and Variance PCR

## TL;DR

This paper explains how qPCR standard curves are used to validate assays and quantify target molecules, introducing a new method called variance PCR for absolute quantification.

## Contribution

The paper introduces 'variance PCR', a novel method using threshold variation to estimate target molecule counts, potentially extending quantification range.

## Key findings

- Variance in threshold crossing points can estimate target molecule numbers, complementing digital PCR.
- Idealized standard curves with many replicates clarify PCR efficiency and detection limits.
- Routine qPCR workflows can validate dynamic range and precision using standard curves.

## Abstract

The quantitative polymerase chain reaction (PCR) standard curve is the central analytical tool for validating qPCR assays and can also be used to estimate target concentrations in test samples. This review explains how qPCR standard curves are constructed, validated, and analyzed for different purposes. We first examine an idealized standard curve generated using an exceptionally high number of replicates, far exceeding typical routine use. This approach clearly illustrates fundamental qPCR characteristics and provides an educational framework for defining and estimating PCR efficiency, limit of detection, and limit of quantification. Furthermore, we demonstrate that, in theory, variation in threshold crossing points across replicates can be used to estimate the number of target molecules in a sample. This method, which we term variance PCR, could complement digital PCR and potentially extend the dynamic range of absolute quantification. We also analyze a representative standard curve as typically processed in routine qPCR workflows. This includes validating its dynamic range, assessing the impact of outliers, estimating PCR efficiency and precision, and finally applying the curve to determine the concentration of test samples.