Relative Quantification of Gene Expression using Delta Ct Methods
control_boxplot_gene
control_boxplot_sample
control_cluster_gene
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control_Ct_barplot_gene
control_Ct_barplot_sample
control_heatmap
control_pca_gene
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corr_gene
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delta_Ct
FCh_plot
filter_Ct
filter_transformed_data
find_ref_gene
log_reg
make_Ct_ready
norm_finder
parallel_plot
pca_kmeans
read_Ct_long
read_Ct_wide
results_barplot
results_boxplot
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ROCh
RQ_dCt
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single_pair_gene
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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.