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rtpcr (version 2.0.1)

qPCR Data Analysis

Description

Various methods are employed for statistical analysis and graphical presentation of real-time PCR (quantitative PCR or qPCR) data. 'rtpcr' handles amplification efficiency calculation, statistical analysis and graphical representation of real-time PCR data based on up to two reference genes. By accounting for amplification efficiency values, 'rtpcr' was developed using a general calculation method described by Ganger et al. (2017) and Taylor et al. (2019) , covering both the Livak and Pfaffl methods. Based on the experimental conditions, the functions of the 'rtpcr' package use t-test (for experiments with a two-level factor), analysis of variance (ANOVA), analysis of covariance (ANCOVA) or analysis of repeated measure data to calculate the fold change (FC, Delta Delta Ct method) or relative expression (RE, Delta Ct method). The functions further provide standard errors and confidence intervals for means, apply statistical mean comparisons and present significance. To facilitate function application, different data sets were used as examples and the outputs were explained. ‘rtpcr’ package also provides bar plots using various controlling arguments. The 'rtpcr' package is user-friendly and easy to work with and provides an applicable resource for analyzing real-time PCR data.

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Install

install.packages('rtpcr')

Monthly Downloads

355

Version

2.0.1

License

GPL-3

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Maintainer

Ghader Mirzaghaderi

Last Published

February 13th, 2025

Functions in rtpcr (2.0.1)

twoFACTORplot

Bar plot of the relative gene expression (\(\Delta C_T\) method) from the qpcrANOVARE output of a two-factorial experiment data
threeFACTORplot

Bar plot of the relative gene expression (\(\Delta C_T\) method) from the qpcrANOVARE output of a a three-factorial experiment data
multiplot

Multiple plot function
meanTech

Calculating mean of technical replicates
Lee_etal2020qPCR

Sample data (with technical replicates)
data_2factorBlock

Sample data (two factor with blocking factor)
data_ttest

Sample qPCR data from an experiment conducted under two different conditions
data_repeated_measure_1

Repeated measure sample data
Taylor_etal2019

Sample qPCR data (one target and two reference genes under two different conditions)
data_3factor

Sample data (three factor)
data_1factor

Sample data (one factor three levels)
data_repeated_measure_2

Repeated measure sample data
data_efficiency

Sample qPCR data: amplification efficiency
data_2factor

Sample data (two factor)
qpcrMeans

Fold change (\(\Delta \Delta C_T\) method) analysis using a model
qpcrANOVAFC

Fold change (\(\Delta \Delta C_T\) method) analysis using ANOVA and ANCOVA
qpcrANOVARE

Relative expression (\(\Delta C_T\) method) analysis using ANOVA
qpcrTTEST

Fold change (\(\Delta \Delta C_T\) method) analysis of target genes using t-test
oneFACTORplot

Bar plot of the relative gene expression (\(\Delta C_T\) method) from the qpcrANOVARE output of a single-factor experiment data
qpcrREPEATED

Fold change (\(\Delta \Delta C_T\) method) analysis of repeated measure qPCR data
efficiency

Slope, R2 and Efficiency (E) statistics and standard curves
data_withTechRep

Sample data (with technical replicates)
qpcrTTESTplot

Bar plot of the average fold change (\(\Delta \Delta C_T\) method) of target genes