quantGenius

quantGenius applies standard-curve qPCR analysis with integrated QC-based decision support to quantify nucleic acids while accounting for reference-gene normalization, amplification efficiency, pipetting errors, and PCR inhibition.

Key Features:

• Standard Curve Approach: Employs the standard curve methodology for qPCR-based quantification and supports normalization against one or several reference genes.
• Quality Control (QC) System: Implements an integrated QC-based decision support system that evaluates pipetting errors, assay amplification efficiencies, and PCR inhibition in individual samples.
• Error Control and Decision Support: Assesses limits of detection and limits of quantification and applies qPCR-standard-based decision rules to address potential errors.
• Data Exportability: Exports intermediate calculations and final results in a data matrix format for downstream statistical analysis and visualization.
• Comparative Analysis: Includes comparative assessment against other advanced qPCR software to highlight the impact of QC procedures on quantification outcomes.

Scientific Applications:

• High-throughput qPCR quantification: Supports consistent nucleic acid quantification in high-throughput experimental settings.
• Quality-controlled quantification: Enables robust quantification by detecting and accounting for pipetting errors, amplification efficiency variability, and PCR inhibition.
• Reference-gene normalization: Facilitates normalization of target measurements against one or several reference genes.
• LOD/LOQ assessment: Provides assessment of limits of detection and limits of quantification to inform analytical decision-making.
• Downstream data analysis integration: Produces data matrices suitable for subsequent statistical analysis and visualization.

Methodology:

Uses standard curve methodology and a QC-based decision support algorithm that evaluates pipetting errors, amplification efficiencies, and PCR inhibition, assesses limits of detection/quantification, and exports intermediate and final calculations as a data matrix.