First release.
Fifteen GPU- and canvas-accelerated visualization widgets, built on a shared
JavaScript core and exposed to R through htmlwidgets. Every widget renders in
the RStudio Viewer, R Markdown, Quarto and Shiny, and every one ships a matching
*Output() / render*() pair for classic Shiny apps.
volcano() -- differential expression, effect size against significance.bioheatmap() (alias heatmap_plotomics()) -- large sample-by-gene matrices.
Named to avoid masking stats::heatmap().clustermap() -- expression matrix with row and column dendrograms.dotplot() -- marker genes by group, dot area for the fraction expressing and
colour for the level.violin() -- one row per feature, one violin per group. violin_density()
computes the densities in R.embedding() -- UMAP, t-SNE and PCA scatter at several hundred thousand
points. A factor color column pins the legend order and keeps unused levels,
the way drop = FALSE does in ggplot2.spatial() -- measurements at their slide coordinates over the histology
image, with image and spots sharing one fit so they cannot drift apart on
resize.oncoplot() -- the cohort alteration landscape, with mutation-burden and
per-gene frequency barplots and clinical annotation strips.
oncoplot_memo_sort() produces the conventional column order.lollipop() -- variants along a protein over its domain architecture.km() -- Kaplan-Meier curves with censoring ticks, confidence bands and a
number-at-risk table. Accepts a survival::survfit object directly.bioprofile() -- grouped categorical profile, built for the 96-context
mutational signature layout.upset() -- set intersections for the many-set case.
upset_intersections() computes exclusive intersections, so columns sum to the
union rather than double-counting.treemap() -- hierarchical gene-set and pathway composition.network() -- large biological networks, with directed edges, per-edge colour
and node-click selection that pushes the clicked id to
input$<outputId>_selected in Shiny.hic() -- Hi-C contact matrices with level-of-detail tiling.