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All functions

calculate_condition_mean_sd_per_gene()
Calculate statistics for each gene of an expression matrix given a grouping
crossPanelUI() crossPanelServer()
Generate the cross plot panel of the shiny app
cross_plot()
Create a cross plot comparing differential expression (DE) results
DEanalysis_edger() DEanalysis_deseq2()
Perform differential expression (DE) analysis on an expression matrix
DEpanelUI() DEpanelServer()
Generate the DE panel of the shiny app
DEplotPanelUI() DEplotPanelServer()
Generate the DE plot plot panel of the shiny app
DEsummaryPanelUI() DEsummaryPanelServer()
Generate the DE summary panel of the shiny app
determine_uds()
Determine the pattern between two intervals
enrichmentPanelUI() enrichmentPanelServer()
Generate the enrichment panel of the shiny app
expression_heatmap()
Create heatmap of an expression matrix
find_regulators_with_recurring_edges()
Find recurring regulators
generateShinyApp()
Generate all files required for an autonomous shiny app
get_link_list_rename()
Convert the adjacency matrix to network links
GRNCisPanelUI() GRNCisPanelServer()
Generate the GRN cis integration panel of the shiny app
GRNCustomPanelUI() GRNCustomPanelServer()
Generate the GRN custom integration panel of the shiny app
GRNpanelUI() GRNpanelServer()
Generate the GRN panel of the shiny app
GRNTransPanelUI() GRNTransPanelServer()
Generate the GRN trans integration panel of the shiny app
infer_GRN()
Perform GRN inference
jaccard_heatmap()
Create a heatmap of the Jaccard similarity index (JSI) between samples of an experiment
jaccard_index()
Calculate the Jaccard similarity index (JSI) between two vectors
landingPanelUI() landingPanelServer()
Generate the landing page panel of the shiny app
make_heatmap_matrix()
Create a matrix of the average expression of each gene in each condition
make_pattern_matrix()
Create a matrix of the patterns between conditions
ma_plot() ma_enhance()
Create an MA plot visualising differential expression (DE) results
modalityPanelUI() modalityPanelServer()
Generate an app panel for a modality
noisyr_counts_with_plot()
Apply a modified noisyR counts pipeline printing a plot
patternPanelUI() patternPanelServer()
Generate the expression patterns panel of the shiny app
plot_GRN()
Plot a GRN
plot_line_pattern()
Create a line plot of average expression across conditions
plot_pca()
Create a principal component analysis (PCA) plot the samples of an experiment
plot_upset()
Visualise the overlap of edges between different networks
preprocessExpressionMatrix()
Pre-process the expression matrix before generating the shiny app
preprocess_miRTarBase()
Creates a comparison table for miRTarBase to be used for custom integration
QCpanelUI() QCpanelServer()
Generate the QC panel of the shiny app
rescale_matrix()
Rescale a matrix
sampleSelectPanelUI() sampleSelectPanelServer()
Generate the sample select panel of the shiny app
volcano_plot() volcano_enhance()
Create a volcano plot visualising differential expression (DE) results