rtPCR

rtPCR performs statistical analysis and graphical presentation of quantitative PCR (qPCR) data, including amplification efficiency calculation, fold change, and relative expression analysis using reference genes and the Pfaffl method.

Key Features:

• Amplification Efficiency Calculation: The package calculates amplification efficiency values and accommodates up to two reference genes using a general calculation methodology.
• Statistical Testing: Functions apply t-tests for two-level factor experiments, analysis of variance (ANOVA) for multi-level or multi-factor experiments, and analysis of covariance (ANCOVA) for experiments with covariates.
• Expression Quantification: The package calculates fold change (FC) or relative expression (RE) of target genes with standard errors and confidence intervals for means, supporting statistical mean comparisons.
• Graphical Presentation: The package provides ggplot-based visualizations with customizable arguments for publication-ready graphical output.
• Example Datasets: The package includes example datasets to facilitate usage and validation.

Scientific Applications:

• qPCR Data Analysis: rtPCR interprets qPCR data to measure mRNA levels of target genes under different experimental conditions.
• Multi-Factor Experimental Design: The package analyzes real-time PCR data from experiments involving up to three different factors.
• Gene Expression Quantification: rtPCR enables robust calculation of relative gene expression using the Pfaffl method with reference gene normalization.

Methodology:

The package uses a general calculation methodology that accommodates up to two reference genes and amplification efficiency values, including the Pfaffl method. Statistical functions apply t-tests, ANOVA, or ANCOVA depending on experimental design to calculate fold change or relative expression.