Description
Relative Quantification of Gene Expression using Delta Ct Methods.
Description
The commonly used methods for relative quantification of gene expression levels obtained in real-time PCR (Polymerase Chain Reaction) experiments are the delta Ct methods, encompassing 2^-dCt and 2^-ddCt methods, originally proposed by Kenneth J. Livak and Thomas D. Schmittgen (2001) <doi:10.1006/meth.2001.1262>. The main idea is to normalise gene expression values using endogenous control gene, present gene expression levels in linear form by using the 2^-(value)^ transformation, and calculate differences in gene expression levels between groups of samples (or technical replicates of a single sample). The 'RQdeltaCT' package offers functions that cover both methods for comparison of either independent groups of samples or groups with paired samples, together with importing expression datasets, performing multi-step quality control of data, enabling numerous data visualisations, enrichment of the standard workflow with additional useful analyses (correlation analysis, Receiver Operating Characteristic analysis, logistic regression), and conveniently export obtained results in table and image formats. The package has been designed to be friendly to non-experts in R programming.
README.md
RQdeltaCT - an R package for relative quantification of gene expression using delta Ct methods
RQdeltaCT is an R package developed to perform relative quantification of gene expression using delta Ct family methods (encompassing 2^-Ct, 2^-dCt, and 2^-ddCt method), originally proposed by Kenneth J. Livak and Thomas D. Schmittgen in Article1 and Article2.
These methods have been designed to analyse gene expression data (Ct values) obtained from real-time PCR experiments. The main idea is to:
- normalise gene expression values using endogenous control gene,
- present gene expression levels in linear form by using the 2^-(value) transformation,
- calculate differences in gene expression levels between groups of samples (or technical replicates of a single sample).
The RQdeltaCT package offers functions that encompass all of these steps, together with:
- importing qPCR datasets,
- performing multi-step quality control of data,
- enabling numerous data visualisations,
- enrichment of standard workflow with additional useful methods including correlation analysis, Receiver Operating Characteristic analysis, and logistic regression),
- a convenient export of obtained results in table and image forms.
The package has been designed to be friendly to non-experts in R programming users. No additional, extensive coding steps are necessary in the standard workflow. Detailed demonstration of the package functionalities with examples can be found in the prepared vignette.
To install and load the RQdeltaCT package, simply run in R or RStudio:
remotes::install_github("Donadelnal/RQdeltaCT")library(RQdeltaCT)