cIRT
A choice-based IRT model published once in 2019 and kept compiling ever since
A side-by-side editorial comparison of ddpcr and ggguides — release velocity, themes, recent moves, and the top alternatives to consider.
A decade-old droplet PCR analysis package woken up for one compatibility release
ddpcr reads droplet digital PCR data exported from Bio-Rad's QuantaSoft, classifies droplets and ships a Shiny interface over the analysis. It has been on CRAN since 2016 alongside an F1000Research paper. The last ten years of releases are almost entirely about keeping pace with QuantaSoft export formats and with churn in its own R dependencies.
Three releases in one day to make legend positioning finally do what the docs said.
ggguides is a helper layer over ggplot2's guide system, exposing legend placement and styling through small named functions instead of raw theme() calls. On 23 April 2026 it shipped 1.1.7, 1.1.8 and 1.1.9 within thirteen hours, each fixing a different path by which the justification argument silently did nothing. The common root cause is that ggplot2 3.5 split legend.justification into side-specific theme elements, and ggguides was still writing to the generic fallback.
ddpcr reads droplet digital PCR data exported from Bio-Rad's QuantaSoft, classifies droplets and ships a Shiny interface over the analysis. It has been on CRAN since 2016 alongside an F1000Research paper. The last ten years of releases are almost entirely about keeping pace with QuantaSoft export formats and with churn in its own R dependencies.
This is a maintained-not-developed package, and the release history shows it plainly: a burst of real work through 2016 and 2017, then long silences broken by releases whose stated purpose is staying on CRAN. The 2026 release fits the same shape but does more than the 2023 pair did, adding support for a QuantaSoft variant and finally retiring dplyr code written against a tidy evaluation style that has been outdated for years.
Nothing in the entries points to new analysis capability; the pattern suggests the package surfaces again only when a QuantaSoft export change or a dependency deprecation forces it.
ggguides is a helper layer over ggplot2's guide system, exposing legend placement and styling through small named functions instead of raw theme() calls. On 23 April 2026 it shipped 1.1.7, 1.1.8 and 1.1.9 within thirteen hours, each fixing a different path by which the justification argument silently did nothing. The common root cause is that ggplot2 3.5 split legend.justification into side-specific theme elements, and ggguides was still writing to the generic fallback.
The package is in the phase where a wrapper meets the reality of the API it wraps. All three same-day releases are the same bug found in successive entry points: legend_inside(), then the four side functions, then legend_style(by = ). Along the way the fix work produced a real feature, a justification argument on the side legend functions. The pattern of a single reporter driving three consecutive releases suggests the surface is being audited rather than randomly patched.
Expect a consolidation release that audits the remaining theme elements ggguides writes to against ggplot2 3.5 semantics, rather than another single-path fix.
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 ddpcr or ggguides.
A choice-based IRT model published once in 2019 and kept compiling ever since
The R engine behind MetaboAnalyst closes the gap from raw spectra to biological interpretation
Rebuilding SAS's formatting layer in R, one format specification at a time
Standardised coefficients for models where standardising everything is wrong — but the feed only links out
Stream-network spatial models learning to run on data that no longer fits in memory
Bioconductor's installer, frozen at 1.30.x and tuned almost entirely through environment variables
See all ddpcr alternatives → · See all ggguides alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. ddpcr and ggguides 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. ddpcr and ggguides 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 ddpcr alternatives in Analytics are ranked by recent ship velocity. Browse the "ddpcr alternatives" section above for the current picks, or visit /alternatives/ddpcr for the full list with editorial commentary on each.
Top ggguides alternatives in Analytics are ranked by recent ship velocity. Browse the "ggguides alternatives" section above for the current picks, or visit /alternatives/ggguides for the full list with editorial commentary on each.