rtpcr: qPCR Data Analysis

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) <doi:10.1186/s12859-017-1949-5> and Taylor et al. (2019) <doi:10.1016/j.tibtech.2018.12.002>, 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.

Version: 2.0.0
Depends: R (≥ 3.5.0)
Imports: multcomp, multcompView, ggplot2, lmerTest, purrr, reshape2, tidyr, dplyr, grid, emmeans
Suggests: knitr, rmarkdown
Published: 2024-07-07
DOI: 10.32614/CRAN.package.rtpcr
Author: Ghader Mirzaghaderi [aut, cre, cph]
Maintainer: Ghader Mirzaghaderi <gh.mirzaghaderi at uok.ac.ir>
License: GPL-3
URL: https://github.com/mirzaghaderi/rtpcr
NeedsCompilation: yes
CRAN checks: rtpcr results

Documentation:

Reference manual: rtpcr.pdf
Vignettes: Sending Messages With Gmailr

Downloads:

Package source: rtpcr_2.0.0.tar.gz
Windows binaries: r-devel: rtpcr_2.0.0.zip, r-release: rtpcr_2.0.0.zip, r-oldrel: rtpcr_2.0.0.zip
macOS binaries: r-release (arm64): rtpcr_2.0.0.tgz, r-oldrel (arm64): rtpcr_2.0.0.tgz, r-release (x86_64): rtpcr_2.0.0.tgz, r-oldrel (x86_64): rtpcr_2.0.0.tgz
Old sources: rtpcr archive

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