qqman
The Manhattan-plot package for GWAS results, finished and dormant since 2017.
Comparison · Analytics
austraits vs ggcorrplot
A side-by-side editorial comparison of austraits and ggcorrplot — release velocity, themes, recent moves, and the top alternatives to consider.
austraits vs ggcorrplot: at a glance
What is austraits?
The R client for AusTraits spends its releases chasing the dataset it reads.
austraits is the R access layer for the AusTraits plant trait database, and its release history is almost entirely a record of keeping pace with two upstream systems it does not control: the austraits.build data releases and the Zenodo archive that hosts them. The most recent release adds a version-dispatch layer so the same package can read both v4.x and v5.0.0 data. Three of the four visible tags were backfilled to GitHub within 23 minutes of each other, so version order and publication order do not agree.
What is ggcorrplot?
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.
austraits vs ggcorrplot: editorial side-by-side
austraits
0.0ANALYTICS
The R client for AusTraits spends its releases chasing the dataset it reads.
◆ Current state
austraits is the R access layer for the AusTraits plant trait database, and its release history is almost entirely a record of keeping pace with two upstream systems it does not control: the austraits.build data releases and the Zenodo archive that hosts them. The most recent release adds a version-dispatch layer so the same package can read both v4.x and v5.0.0 data. Three of the four visible tags were backfilled to GitHub within 23 minutes of each other, so version order and publication order do not agree.
◆ Where it's heading
The package is converging on a stable public vocabulary and a versioned internal. Sites became locations across every join, plot and extract function; the extract_ and print family filled out at 1.0.0; and by 2.2.2 the core functions each carry a switch on the detected data version rather than assuming one schema. The visible cost of that is dependency churn — plotting packages moved to Suggests, which the notes admit can leave core functions unable to run.
◆ Prediction
Given that every release so far has been triggered by an upstream austraits.build or Zenodo change, the next one most likely follows the next data release rather than any independent roadmap. The entries do not indicate new analysis capability being planned in the client itself.
ggcorrplot
2.5ANALYTICS
ggcorrplot came back after four years and found its significance markers had been lying
◆ Current state
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.
◆ Where it's heading
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.
◆ Prediction
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.
Alternatives to austraits and ggcorrplot
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 austraits or ggcorrplot.
constants
The R package for CODATA constants rebuilt its symbol table on NIST's naming so future updates stop being hand work.
ggdemetra
A ggplot2 layer for seasonal adjustment output, filling in one plot type at a time.
fossilsim
A fossil-record simulator that quietly grew a trait-evolution engine.
tern.rbmi
Reference-based multiple imputation tables, shipping only what CRAN checks demand.
tern.mmrm
An MMRM tabulation package that has published nothing since its 2024 CRAN releases.
See all austraits alternatives → · See all ggcorrplot alternatives →
Recent activity from austraits and ggcorrplot
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 22d agoggcorrplotggcorrplot 0.3.0 adds boxed cells and correlation-sized squares
- 1mo agoggcorrplotggcorrplot 0.2.0 fixes significance markers broken by hc.order
- 2y agoaustraitsSupport for AusTraits 5.0.0 data and the rebuilt Zenodo API
- 3y agoaustraitsextract_taxa, lookup_trait and print methods arrive
- 3y agoaustraitsVignette build and extract_ function polish
- 3y agoaustraitssite becomes location across the API; AusTraits 3.0.2+ support
- 3y agoggcorrplotggcorrplot 0.1.4
- 6y agoggcorrplotggcorrplot 0.1.3
- 7y agoggcorrplotggcorrplot 0.1.2
- 10y agoggcorrplotggcorrplot's first release: correlograms in ggplot2
Frequently asked questions
What is the difference between austraits and ggcorrplot?
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.
Is austraits better than ggcorrplot?
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.
What are the best alternatives to austraits?
Top austraits alternatives in Analytics are ranked by recent ship velocity. Browse the "austraits alternatives" section above for the current picks, or visit /alternatives/austraits-r for the full list with editorial commentary on each.
What are the best alternatives to ggcorrplot?
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.