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ggcorrplot vs qqman

A side-by-side editorial comparison of ggcorrplot and qqman — release velocity, themes, recent moves, and the top alternatives to consider.

Shared themes:visualization

ggcorrplot vs qqman: at a glance

Featureggcorrplotqqman
SectorAnalyticsAnalytics
Velocity score2.50.0
Sparks · 30d00
Top themescorrelation, r, ggplot2, visualizationgwas, genomics, manhattan-plot, visualization
Last editorial update10h ago1h ago
WebsiteVisit →Visit →

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.

Read the full ggcorrplot trajectory →

What is qqman?

The Manhattan-plot package for GWAS results, finished and dormant since 2017.

qqman does two things: manhattan() and qq() plots for genome-wide association study results. Its six visible releases run from 2014 to a single 2017 packaging fix, and the last release with any user-facing change shipped in 2015. The archive is non-monotonic — a 0.0.0 tag published after 0.1.1 archives the pre-package standalone script — so version order and publication order disagree.

Read the full qqman trajectory →

ggcorrplot vs qqman: editorial side-by-side

G
ggcorrplot
ANALYTICS
2.5

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.

Q
qqman
ANALYTICS
0.0

The Manhattan-plot package for GWAS results, finished and dormant since 2017.

◆ Current state

qqman does two things: manhattan() and qq() plots for genome-wide association study results. Its six visible releases run from 2014 to a single 2017 packaging fix, and the last release with any user-facing change shipped in 2015. The archive is non-monotonic — a 0.0.0 tag published after 0.1.1 archives the pre-package standalone script — so version order and publication order disagree.

◆ Where it's heading

The real development window was 2014 to 2015. The 0.1.2 release did the substantive work, replacing the assumption that SNPs are evenly distributed across chromosomes and handing users control of axis limits, labels and log transformation; 0.1.3 then added annotation by p-value threshold and top-SNP-per-chromosome. After that the package stops. Notably, the archival 0.0.0 entry records that the original script had confidence intervals on QQ plots and richer highlighting than the released package ever regained.

◆ Prediction

With one packaging fix in the last decade, these entries support no prediction of further releases. The package reads as complete for its narrow purpose rather than abandoned mid-arc.

Alternatives to ggcorrplot and qqman

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 qqman.

See all ggcorrplot alternatives → · See all qqman alternatives →

Recent activity from ggcorrplot and qqman

Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.

  1. 22d agoggcorrplotggcorrplot 0.3.0 adds boxed cells and correlation-sized squares
  2. 1mo agoggcorrplotggcorrplot 0.2.0 fixes significance markers broken by hc.order
  3. 3y agoggcorrplotggcorrplot 0.1.4
  4. 6y agoggcorrplotggcorrplot 0.1.3
  5. 7y agoggcorrplotggcorrplot 0.1.2
  6. 9y agoqqmanREADME image path fix for pandoc
  7. 10y agoggcorrplotggcorrplot's first release: correlograms in ggplot2
  8. 11y agoqqmanAnnotate SNPs by p-value threshold or per-chromosome top hit
  9. 11y agoqqmanChromosome ticks stop assuming even SNP spacing; axis control opens up
  10. 12y agoqqmanArchival tag for the pre-package standalone script
  11. 12y agoqqmanVignette touch-up
  12. 12y agoqqmanZenodo archival tag, no code change

Frequently asked questions

What is the difference between ggcorrplot and qqman?

Both compete on the same themes — visualization — within Analytics. 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 ggcorrplot better than qqman?

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 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.

What are the best alternatives to qqman?

Top qqman alternatives in Analytics are ranked by recent ship velocity. Browse the "qqman alternatives" section above for the current picks, or visit /alternatives/qqman-r for the full list with editorial commentary on each.