Table of contents | Introduction | The summary of standard workflow | Data import | Reading long-format data using the read_Ct_long() function | Reading wide-format data using the read_Ct_wide() function | Other methods | Part A: The workflow for analysis of independent groups of samples | Quality control of raw Ct data | Filtering of raw Ct data | Collapsing technical replicates and imputation of missing data - make_Ct_ready() function | Reference gene selection | Data normalization using reference gene | Quality control and filtering of normalized Ct data | Analysis of data distribution | Hierarchical clustering | PCA analysis | Data filtering after quality control | Relative quantification: 2^-dCt^ method | Relative quantification: 2^-ddCt^ method | Final visualisations | The FCh_plot() function | The results_volcano() function | The results_boxplot() function | The results_barplot() function | The results_heatmap() function | Further analyses | PCA and k means clustering | Correlation analysis | Simple linear regression analysis | Receiver Operating Characteristic (ROC) analysis | Simple logistic regression | Part B: A pairwise analysis | Quality control of raw Ct data (a pairwise approach) | Filtering of raw Ct data (a pairwise approach) | Collapsing technical replicates and imputation of missing data - make_Ct_ready() function (a pairwise approach) | Reference gene selection (a pairwise approach) | Data normalization using reference gene (a pairwise approach) | Relative quantification: 2^-dCt^ method (a pairwise approach) | Relative quantification: 2^-ddCt^ method (a pairwise approach) | Quality control and filtering of normalized Ct data (a pairwise approach) | Analysis of data distribution (a pairwise approach) | Hierarchical clustering (a pairwise approach) | PCA analysis (a pairwise approach) | Data filtering after quality control (a pairwise approach) | Final visualisations (a pairwise approach) | The FCh_plot() function (a pairwise approach) | The results_volcano() function (a pairwise approach) | The results_boxplot() function (a pairwise approach) | The results_barplot() function (a pairwise approach) | The results_heatmap() function (a pairwise approach) | The parallel_plot() function (a pairwise approach) | Further analyses (a pairwise approach) | PCA and k means clustering (a pairwise approach) | Correlation analysis (a pairwise approach) | Simple linear regression analysis (a pairwise approach) | Receiver Operating Characteristic (ROC) analysis (a pairwise approach) | Simple logistic regression (a pairwise approach) | Part C: Analysis of more than two groups | Quality control of raw Ct data - a multigroup variant of analysis | Filtering of raw Ct data, collapsing technical replicates, and imputation of missing data - a multigroup variant of analysis | Reference gene selection - a multigroup variant of analysis | Data normalization using reference gene - a multigroup variant of analysis | Quality control and filtering of normalized Ct data - a multigroup variant of analysis | Data filtering after quality control - a multigroup variant of analysis | Relative quantification: 2^-dCt^ and 2^-ddCt^ methods - a multigroup variant of analysis | Final visualisations - a multigroup variant of analysis | Solution for the results_boxplot() function | Solution for the results_barplot() function | Further analyses - a multigroup variant of analysis | Session info