This article presents a standard curve-based method for processing relative real-time PCR data. The method avoids PCR efficiency assessment, minimizes operator involvement, and provides a statistical assessment of intra-assay variation. The procedure includes noise filtering, threshold selection, crossing point calculation, and derivation of non-normalized values from crossing points. The method is validated for relative real-time PCR and is shown to be a reliable and simple alternative to PCR-efficiency based calculations. The data processing procedure involves several steps: noise filtering from raw fluorescence readings, automatic selection of the optimal threshold, calculation of crossing points, and derivation of non-normalized values from crossing points. The method is tested on the expression of six genes in 42 breast cancer biopsies and validated for its effectiveness in processing real-time PCR data. The procedure is implemented using a VBA script and is compatible with various PCR machines and software. The method is shown to be effective in reducing variability and providing accurate results. The use of amplitude normalization is discussed, and its impact on PCR data processing is analyzed. The method is also shown to be effective in reducing variability in PCR replicas and improving the accuracy of results. The procedure is validated using computer simulations and is shown to be effective in processing data with low variability. The method is also shown to be effective in reducing the impact of PCR plateau scattering on results. The procedure is compared to other methods, including PCR efficiency-based calculations, and is shown to be a reliable and simple alternative. The method is suitable for use in routine laboratory practice and is recommended for its simplicity and reliability. The procedure is also shown to be effective in reducing the impact of PCR plateau scattering on results. The method is validated using a variety of data and is shown to be effective in processing real-time PCR data. The procedure is also shown to be effective in reducing the impact of PCR plateau scattering on results. The method is recommended for use in routine laboratory practice due to its simplicity and reliability.This article presents a standard curve-based method for processing relative real-time PCR data. The method avoids PCR efficiency assessment, minimizes operator involvement, and provides a statistical assessment of intra-assay variation. The procedure includes noise filtering, threshold selection, crossing point calculation, and derivation of non-normalized values from crossing points. The method is validated for relative real-time PCR and is shown to be a reliable and simple alternative to PCR-efficiency based calculations. The data processing procedure involves several steps: noise filtering from raw fluorescence readings, automatic selection of the optimal threshold, calculation of crossing points, and derivation of non-normalized values from crossing points. The method is tested on the expression of six genes in 42 breast cancer biopsies and validated for its effectiveness in processing real-time PCR data. The procedure is implemented using a VBA script and is compatible with various PCR machines and software. The method is shown to be effective in reducing variability and providing accurate results. The use of amplitude normalization is discussed, and its impact on PCR data processing is analyzed. The method is also shown to be effective in reducing variability in PCR replicas and improving the accuracy of results. The procedure is validated using computer simulations and is shown to be effective in processing data with low variability. The method is also shown to be effective in reducing the impact of PCR plateau scattering on results. The procedure is compared to other methods, including PCR efficiency-based calculations, and is shown to be a reliable and simple alternative. The method is suitable for use in routine laboratory practice and is recommended for its simplicity and reliability. The procedure is also shown to be effective in reducing the impact of PCR plateau scattering on results. The method is validated using a variety of data and is shown to be effective in processing real-time PCR data. The procedure is also shown to be effective in reducing the impact of PCR plateau scattering on results. The method is recommended for use in routine laboratory practice due to its simplicity and reliability.