qqman
The Manhattan-plot package for GWAS results, finished and dormant since 2017.
A side-by-side editorial comparison of bittermelon and ggmagnify — release velocity, themes, recent moves, and the top alternatives to consider.
bittermelon is growing from binary bitmaps toward greyscale and color glyphs
The package manipulates bitmap fonts and bitmaps in R, and the recent direction is widening what a glyph can be. v2.3.1 adds greyscale font support by reading the experimental yaff levels property into pixmap glyphs with alpha derived from the level fraction, and makes writing a multi-colored glyph an error rather than silently clamping it. Earlier releases built out the same surface: bm_extract(), an interactive pixel picker, data frame coercion, and format support for other packages' bitmap types.
A single-purpose ggplot2 inset tool, refining the same three arguments.
ggmagnify draws magnified insets of a region of a ggplot, with projection lines connecting the inset to its source area. The visible releases are all small refinements to how that inset looks — corner radius, fill between projection lines — plus one fix for inset themes being overridden. There are only three entries, so the picture is necessarily partial.
The package manipulates bitmap fonts and bitmaps in R, and the recent direction is widening what a glyph can be. v2.3.1 adds greyscale font support by reading the experimental yaff levels property into pixmap glyphs with alpha derived from the level fraction, and makes writing a multi-colored glyph an error rather than silently clamping it. Earlier releases built out the same surface: bm_extract(), an interactive pixel picker, data frame coercion, and format support for other packages' bitmap types.
Two things are converging. The representation is moving beyond one-bit glyphs — pixmaps, color, and now greyscale levels with transparency — while the API gets stricter about the boundary between them, refusing to quietly downcast a color glyph on write. Separately, the package has been shedding weight: the embedded monobit copy was removed once it outgrew CRAN size limits, pushing format breadth onto a user-installed dependency.
Expect further greyscale and color work now that levels parsing exists — most likely writing that format rather than only reading it, since the write path is where the current release chose to draw a hard error instead.
ggmagnify draws magnified insets of a region of a ggplot, with projection lines connecting the inset to its source area. The visible releases are all small refinements to how that inset looks — corner radius, fill between projection lines — plus one fix for inset themes being overridden. There are only three entries, so the picture is necessarily partial.
Work concentrates on the visual finish of the inset rather than on new capability, which is what a package with one job should look like. Two feature releases a week apart in early 2024 suggest a short burst of attention rather than sustained development, and the feed goes quiet after mid-2024.
Too few entries to call a direction with confidence; continued small styling arguments would be consistent with what is visible.
Other Analytics products tracked by Sparkpulse, ranked by recent ship velocity. Each card links to a full editorial trajectory and lets you pivot into a head-to-head comparison with either bittermelon or ggmagnify.
The Manhattan-plot package for GWAS results, finished and dormant since 2017.
The R package for CODATA constants rebuilt its symbol table on NIST's naming so future updates stop being hand work.
The R client for AusTraits spends its releases chasing the dataset it reads.
A ggplot2 layer for seasonal adjustment output, filling in one plot type at a time.
A fossil-record simulator that quietly grew a trait-evolution engine.
Reference-based multiple imputation tables, shipping only what CRAN checks demand.
See all bittermelon alternatives → · See all ggmagnify alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
Both compete on the same themes — r-package — within Analytics. bittermelon and ggmagnify are shipping at a similar cadence (velocity 0.0 vs 0.0, both within Sparkpulse's "active" band). See the at-a-glance table above for a side-by-side breakdown of velocity, recent sparks, and editorial themes.
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. bittermelon and ggmagnify are shipping at a similar cadence (velocity 0.0 vs 0.0, both within Sparkpulse's "active" band). For your specific use case, the alternatives sections above list other Analytics products to evaluate alongside.
Top bittermelon alternatives in Analytics are ranked by recent ship velocity. Browse the "bittermelon alternatives" section above for the current picks, or visit /alternatives/bittermelon-r for the full list with editorial commentary on each.
Top ggmagnify alternatives in Analytics are ranked by recent ship velocity. Browse the "ggmagnify alternatives" section above for the current picks, or visit /alternatives/ggmagnify for the full list with editorial commentary on each.