visualizations

Functions to plot data from Samples object or DMP/DMR dataframes

Functions

analyze_replicates(samples, sample_id_column)	Analyze the beta values standard deviation of the technical replicates to check for batch effect or quality issues.
betas_2D(samples[, label_column, ...])	Plot samples in 2D space according to their beta distances.
betas_dendrogram(samples[, title, ...])	Plot dendrogram of samples according to their beta values distances.
betas_density(samples[, n_ind, title, ...])	Plot beta values density for each sample
get_nb_probes_per_chr_and_type(samples)	Count the number of probes covered by the sample-s per chromosome and design type
manhattan_plot_cnv(data_to_plot[, ...])	Display a Manhattan plot of the given CNV data, designed to work with the dataframes returned by copy_number_variation()
manhattan_plot_dmr(data_to_plot, contrast[, ...])	Display a Manhattan plot of the given DMR data, designed to work with the dataframe returned by get_dmrs()
plot_betas_heatmap(samples[, apply_mask, ...])	Plot a heatmap of the probes with the most variable beta values, showing hierarchical clustering of the probes with dendrograms on the sides.
plot_dmp_heatmap(dmps, samples[, contrast, ...])	Plot a heatmap of the probes that are the most differentially methylated, showing hierarchical clustering of the probes with dendrograms on the sides.
plot_methylation_distribution(samples[, ...])	Plot the distribution of hyper/hypo methylated probes in the samples.
plot_nb_probes_and_types_per_chr(sample[, ...])	Plot the number of probes covered by the sample per chromosome and design type
plot_pc_correlation(samples[, params, ...])	Plot the correlation between the principal components and the parameters in the sample sheet.
visualize_chr_region(samples, chr_id, ...[, ...])	Show the beta values of a gene for all probes and samples in its transcription zone.
visualize_gene(samples, gene_name[, ...])	Show the beta values of a gene for all probes and samples in its transcription zone.