n2kanalysis
n2kanalysis has spent eight years wiring INLA models to an S3 bucket.
A side-by-side editorial comparison of ggcorrplot and lineup2 — release velocity, themes, recent moves, and the top alternatives to consider.
ggcorrplot came back after four years and found its significance markers had been lying
ggcorrplot draws correlation matrices in ggplot2 with optional significance marking and hierarchical reordering. It sat untouched from late 2022 until mid-2026, then shipped 0.2.0 and 0.3.0 sixteen days apart. Between them they added the display options users had been requesting since 2016 and repaired a set of bugs where hc.order = TRUE silently changed which cells were marked significant.
lineup2 ships once every few years, and 2026's release is a logo and a core-count tweak.
lineup2 provides distance-based tools for detecting sample mix-ups between related datasets — comparing rows and columns of two matrices to find swapped or mislabeled samples. Its visible history is four releases spread across six years, and the capability surface has barely moved since plot_sample() and the propdiff distance arrived in 0.4. Version 0.8 in July 2026 adds a package logo and redefines cores=0 to mean all-but-one core.
ggcorrplot draws correlation matrices in ggplot2 with optional significance marking and hierarchical reordering. It sat untouched from late 2022 until mid-2026, then shipped 0.2.0 and 0.3.0 sixteen days apart. Between them they added the display options users had been requesting since 2016 and repaired a set of bugs where hc.order = TRUE silently changed which cells were marked significant.
Both releases chase the same target: parity with the older corrplot package inside a ggplot2 object. Significance stars appended to coefficient labels, circle scaling, decimal control, then boxed cells and glyphs sized by absolute correlation — these are corrplot's visual vocabulary reimplemented where they can be composed with other ggplot2 layers. The bug fixes point the other way, at foundations: p-values matched to cells by name rather than row position, clustering computed on the unrounded matrix, tl.col actually applied.
With the corrplot look largely reproduced and the correctness backlog cleared, the remaining gap is the mixed upper/lower display corrplot supports; that is the natural next argument if the current release pace holds.
lineup2 provides distance-based tools for detecting sample mix-ups between related datasets — comparing rows and columns of two matrices to find swapped or mislabeled samples. Its visible history is four releases spread across six years, and the capability surface has barely moved since plot_sample() and the propdiff distance arrived in 0.4. Version 0.8 in July 2026 adds a package logo and redefines cores=0 to mean all-but-one core.
This is a finished, single-purpose package in maintenance. The substantive changes across the whole window are plotting conveniences and one parallelism default; nothing in the entries points at new distance measures, new input formats, or expanded scope. The release cadence — five years between 0.6 and 0.8 — reads as a tool the author considers done.
Further releases are likely to stay small: a plotting option, a parallelism detail, or a check-farm fix. The entries give no signal of planned feature work.
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 ggcorrplot or lineup2.
n2kanalysis has spent eight years wiring INLA models to an S3 bucket.
A Fortran-descended optimizer got thread-safe, then found two flags that never worked.
ggstatsplot reached 1.0 by adding tests, having outsourced its statistics years ago.
collapse got a JSS paper and a 7x fmean speedup in the same release.
gtsummary is quietly rebuilding itself around analysis results data, one table verb at a time.
broadcast is filling in NumPy-style array broadcasting for R, operator by operator.
See all ggcorrplot alternatives → · See all lineup2 alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. ggcorrplot is currently shipping more aggressively (velocity 2.5 vs 0.0), with 0 editorial sparks in the last 30 days against 0. 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. ggcorrplot is currently shipping more aggressively (velocity 2.5 vs 0.0), with 0 editorial sparks in the last 30 days against 0. For your specific use case, the alternatives sections above list other Analytics products to evaluate alongside.
Top ggcorrplot alternatives in Analytics are ranked by recent ship velocity. Browse the "ggcorrplot alternatives" section above for the current picks, or visit /alternatives/ggcorrplot for the full list with editorial commentary on each.
Top lineup2 alternatives in Analytics are ranked by recent ship velocity. Browse the "lineup2 alternatives" section above for the current picks, or visit /alternatives/lineup2-r for the full list with editorial commentary on each.