Changes in version 0.2.1.9000 - Add the possibility to plot different assays in plot_pca() when obj is a SummarizedExperiment - Add function to plot one boxplot or one ECDF per sample Changes in version 0.2.1 (2024-07-15) Changes in version 0.2 - Add the possibility to plot gene expression in plot_pca() - plot_pca() and plot_pca_scatters() now detect if the variable to color by is continuous or discrete and chooses an appropriate, colorblind friendly color scale - Add option to plot rasterised points in plot_pca_scatters() - It is now possible to plot squared loadings in the plot_loadings() function - Fix a bug where the distance parameter was ignored in plot_sample_clustering() - Fix a bug where the annotate_top_n parameter didn't work in plot_loadings() when the input was a matrix Changes in version 0.1.4 (2022-06-15) - Fix of bug in plot_pca() that was introduced in the previous version, causing the the feature selection to be circumvented. - Add three dots argument to plot_sample_clustering() to modify the heatmap - Add documentation to plot_sample_clustering() indicating that it can be used with an arbitrary SummarizedExperiment object. - Improved truncation of too large values in plot_chromosome() Changes in version 0.1.3 (2022-05-27) - MA plots between replicates better handle missing values - chromosome heatmaps are not scaled by default anymore - plot_pca better handles missing values by first mean-imputing NAs and then selecting top-variable features - added a function to make a matrix of PCA scatter plots to plot each PC against each other - allow to specify a design during make_dds Changes in version 0.1.2 (2022-04-27) - Fixed issue when the results object fed into plot_ma() contains s-values. - Add GC content gene annotation. Changes in version 0.1.1 (2022-03-18) - Fixed some package dependencies by moving ggsci to Imports and updating the data vignette. Changes in version 0.1.0 (2022-03-17) - Initial version