Analyzing qPCR data: Better practices to facilitate rigor and reproducibility

. Additionally, simulations support ANCOVA's applicability across diverse experimental conditions. We also demonstrate how general-purpose data repositories (e.g., figshare) and code repositories (e.g., GitHub) facilitate adherence to FAIR principles and promote transparency in qPCR research. Finally, we offer graphical examples that transparently depict both target and reference gene behavior within the same figure, enhancing interpretability. This work establishes practical resources and conceptual foundations to improve rigor, reproducibility, and openness in qPCR data analysis.Image 1.