RNAseqQC 0.2.1

• bug fix to not convert factors to numerical before PCA plotting

RNAseqQC 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

RNAseqQC 0.1.4

• 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()

RNAseqQC 0.1.3

• 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

RNAseqQC 0.1.2

• Fixed issue when the results object fed into plot_ma() contains s-values.
• Add GC content gene annotation.

RNAseqQC 0.1.1

• Fixed some package dependencies by moving ggsci to Imports and updating the data vignette.

RNAseqQC 0.1.0

• Initial version