cairo
Cairo finally catches R's graphics engine, all the way to GE API 16.
Comparison · Analytics
ggcorrplot vs qtl
A side-by-side editorial comparison of ggcorrplot and qtl — release velocity, themes, recent moves, and the top alternatives to consider.
ggcorrplot vs qtl: at a glance
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.
What is qtl?
R/qtl is in pure custodial mode: every recent release answers a compiler, not a user
R/qtl is the long-established R package for QTL mapping in experimental crosses, covering interval mapping, composite interval mapping, multiple-QTL model fitting and the associated cross data formats. Nothing in the recent release history adds capability. Version 1.74 removes an include that started warning on CRAN, 1.72 improves an error message in cim(), and 1.70 migrates the C code from Calloc/Realloc/Free to their R_-prefixed equivalents for R-devel.
ggcorrplot vs qtl: editorial side-by-side
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.
qtl
0.0ANALYTICS
R/qtl is in pure custodial mode: every recent release answers a compiler, not a user
◆ Current state
R/qtl is the long-established R package for QTL mapping in experimental crosses, covering interval mapping, composite interval mapping, multiple-QTL model fitting and the associated cross data formats. Nothing in the recent release history adds capability. Version 1.74 removes an include that started warning on CRAN, 1.72 improves an error message in cim(), and 1.70 migrates the C code from Calloc/Realloc/Free to their R_-prefixed equivalents for R-devel.
◆ Where it's heading
The package is being maintained, not developed. The work divides cleanly into keeping the compiled code building against successive R and toolchain versions, and fixing narrow bugs reported through the issue tracker. The C-level migrations in particular are compliance with R's tightening of its C interface rather than anything chosen. Users should read the stability as maturity: the analysis surface has been fixed for years and the maintainer is keeping it installable.
◆ Prediction
R has continued to restrict its non-API C entry points, and this package has already made two such migrations, so further compile-time compliance work is the most likely content of the next release.
Alternatives to ggcorrplot and qtl
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 qtl.
rjdqa
rjdqa keeps refining one screen: the seasonal adjustment quality dashboard
epikit
epikit narrows to field-epidemiology helpers, handing proportions to a sibling package
SimInf
SimInf 10.0 turns an epidemic simulator into a tool that fits models to real time series
mutagen
A young package porting Stata's egen row-wise helpers to the tidyverse, one function per release
broman
A statistician's personal toolbox, growing one plotting utility at a time
See all ggcorrplot alternatives → · See all qtl alternatives →
Recent activity from ggcorrplot and qtl
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 21d agoggcorrplotggcorrplot 0.3.0 adds boxed cells and correlation-sized squares
- 1mo agoggcorrplotggcorrplot 0.2.0 fixes significance markers broken by hc.order
- 8mo agoqtlRemove R_ext/PrtUtil.h include flagged by CRAN
- 8mo agoqtlClearer cim() error when multiple phenotypes are passed
- 1y agoqtlC memory calls migrated to R_Calloc/R_Realloc/R_Free
- 2y agoqtlFix Rprintf call and remaining compiler warnings
- 2y agoqtlFix summary.scanone() thresholds and csvs phenotype reading
- 3y agoqtlFix addint()/addcovarint() with X chromosome QTL and missing phenotypes
- 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 ggcorrplot and qtl?
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 ggcorrplot better than qtl?
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 qtl?
Top qtl alternatives in Analytics are ranked by recent ship velocity. Browse the "qtl alternatives" section above for the current picks, or visit /alternatives/qtl-r for the full list with editorial commentary on each.