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.