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.