Quantification Revisited: What qPCR Efficiency Models Reveal About Data Analysis Integrity

Amplification efficiency is one of the key parameters in quantitative real-time PCR, as it directly influences the accuracy of both absolute and relative quantification. Amplification efficiency, the fold increase per cycle, is affected by oligonucleotide design, reaction chemistry, sample and template properties, and instrument performance. Consequently, it differs between samples, assays and experimental runs. Although methods for estimating the amplification efficiency have been available for more than two decades, most published qPCR studies continue to assume equal and ideal efficiency across assays. This simplifying assumption introduces efficiency- and expression-dependent error into relative expression and fold-change analyses, contributing to the poor reproducibility observed in many PCR-based studies. This review examines the role of the amplification efficiency in qPCR quantification; the consequences of ignoring, assuming or misapplying efficiency; and the practical implications for data interpretation. The review also considers the development of efficiency estimation models and their implications for contemporary analytical approaches, including emerging data-driven methods for amplification curve analyses.

Authors

Institutions

Publication Details

Journal
International Journal of Molecular Sciences
Published
2026-03-02
DOI
https://doi.org/10.3390/ijms27052337
Primary Topic
Molecular Biology Techniques and Applications
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Quantification Revisited: What qPCR Efficiency Models Reveal About Data Analysis Integrity

Stephen A. Bustin, Mikael Kubista, Jan M. Ruijter, Maurice J B van den Hoff
International Journal of Molecular Sciences
Molecular Biology Techniques and Applications
article

Quantification Revisited: What qPCR Efficiency Models Reveal About Data Analysis Integrity

Stephen A. Bustin, Mikael Kubista, Jan M. Ruijter, Maurice J B van den Hoff
article en

Abstract

Amplification efficiency is one of the key parameters in quantitative real-time PCR, as it directly influences the accuracy of both absolute and relative quantification. Amplification efficiency, the fold increase per cycle, is affected by oligonucleotide design, reaction chemistry, sample and template properties, and instrument performance. Consequently, it differs between samples, assays and experimental runs. Although methods for estimating the amplification efficiency have been available for more than two decades, most published qPCR studies continue to assume equal and ideal efficiency across assays. This simplifying assumption introduces efficiency- and expression-dependent error into relative expression and fold-change analyses, contributing to the poor reproducibility observed in many PCR-based studies. This review examines the role of the amplification efficiency in qPCR quantification; the consequences of ignoring, assuming or misapplying efficiency; and the practical implications for data interpretation. The review also considers the development of efficiency estimation models and their implications for contemporary analytical approaches, including emerging data-driven methods for amplification curve analyses.

International Journal of Molecular SciencesVol. 27(5)
Czech Academy of Sciences, Institute of Biotechnology (CZ), Amsterdam University Medical Centers (NL), Anglia Ruskin University (GB), Technical University of Munich (DE), University of Amsterdam (NL)
Openalex Percentile: Top 38%
Molecular Biology Techniques and Applications
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Quantification Revisited: What qPCR Efficiency Models Reveal About Data Analysis Integrity — Stephen A. Bustin, Mikael Kubista, et al. · International Journal of Molecular Sciences (2026) | TGRS Research Map | TGRS