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Comparison · Analytics

ggsci vs OneSampleMR

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

Shared themes:r

ggsci vs OneSampleMR: at a glance

FeatureggsciOneSampleMR
SectorAnalyticsAnalytics
Velocity score2.50.0
Sparks · 30d00
Top themescolor palettes, ggplot2, r, data visualizationmendelian randomization, r, instrumental variables, epidemiology
Last editorial update1h ago1h ago
WebsiteVisit →Visit →

What is ggsci?

ggsci quietly became a palette mirror, then taught itself to generate colors on demand

ggsci ships ready-made ggplot2 color scales, originally journal and sci-fi palettes and now overwhelmingly terminal themes — the iTerm collection has grown past 400 entries and picks up 30 to 70 more with each sync. The one structural change in the recent run is gephi_palettes(), which generates distinct categorical colors for an arbitrary number of levels rather than serving a fixed list. Release cadence is steady, roughly every six to eight weeks.

Read the full ggsci trajectory →

What is OneSampleMR?

OneSampleMR found that argument order in a formula was silently changing its estimates

OneSampleMR implements one-sample Mendelian randomization estimators — two-stage predictor substitution, two-stage residual inclusion, and Sanderson-Windmeijer conditional F statistics for instrument strength. The package spent its first years on packaging and dependency upkeep. The 2026 releases turn to substance: broader support for models fitted elsewhere, then a correctness fix for a defect that depended on nothing more than where covariates appeared in a formula.

Read the full OneSampleMR trajectory →

ggsci vs OneSampleMR: editorial side-by-side

G
ggsci
ANALYTICS
2.5

ggsci quietly became a palette mirror, then taught itself to generate colors on demand

◆ Current state

ggsci ships ready-made ggplot2 color scales, originally journal and sci-fi palettes and now overwhelmingly terminal themes — the iTerm collection has grown past 400 entries and picks up 30 to 70 more with each sync. The one structural change in the recent run is gephi_palettes(), which generates distinct categorical colors for an arbitrary number of levels rather than serving a fixed list. Release cadence is steady, roughly every six to eight weeks.

◆ Where it's heading

Two threads run in parallel. The larger one is curation: ggsci has effectively become a distribution channel for upstream color work, adding design-system palettes (Primer, Atlassian, Bootstrap, Tailwind) and re-syncing iTerm as that project changes, including correcting existing color values when upstream moves. The smaller and more interesting one is generation — the Gephi engine sidesteps the ceiling every fixed palette has, which is what happens when a plot needs more categories than any curated set provides.

◆ Prediction

Given how much of the release notes each cycle is a mechanical upstream sync, the plausible next step is automating those syncs rather than adding another vendor palette by hand; the Gephi generator is the more likely place any genuinely new capability appears.

O
OneSampleMR
ANALYTICS
0.0

OneSampleMR found that argument order in a formula was silently changing its estimates

◆ Current state

OneSampleMR implements one-sample Mendelian randomization estimators — two-stage predictor substitution, two-stage residual inclusion, and Sanderson-Windmeijer conditional F statistics for instrument strength. The package spent its first years on packaging and dependency upkeep. The 2026 releases turn to substance: broader support for models fitted elsewhere, then a correctness fix for a defect that depended on nothing more than where covariates appeared in a formula.

◆ Where it's heading

Two threads. The first is reach — fsw() now reads models fitted by AER::ivreg(), estimatr::iv_robust() and fixest::feols() in addition to ivreg::ivreg(), which makes conditional F statistics available without refitting in the package's own idiom. The second is hardening: clear errors when more than one exposure is given or when a variable collides with the reserved name y, and print methods that no longer fail on user-specified t0 with log or logit links. Both come largely from user reports rather than a plan.

◆ Prediction

The estimator-support work has been adding one IV-fitting package at a time on outside contributions, so further backends are the likeliest next content — the package's own estimators have been stable since first release.

Alternatives to ggsci and OneSampleMR

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 ggsci or OneSampleMR.

See all ggsci alternatives → · See all OneSampleMR alternatives →

Recent activity from ggsci and OneSampleMR

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

  1. 15d agoggsciggsci 5.2.0
  2. 1mo agoOneSampleMROneSampleMR fixes estimates broken by covariate order in the formula
  3. 1mo agoggsciggsci 5.1.0
  4. 4mo agoggsciggsci 5.0.0 generates categorical colors instead of serving a fixed list
  5. 4mo agoggsciggsci 4.3.0
  6. 5mo agoOneSampleMROneSampleMR computes conditional F for three more IV packages
  7. 8mo agoggsciggsci 4.2.0
  8. 9mo agoggsciggsci 4.1.0
  9. 1y agoOneSampleMROneSampleMR 0.1.6
  10. 2y agoOneSampleMROneSampleMR 0.1.5
  11. 2y agoOneSampleMROneSampleMR 0.1.4
  12. 3y agoOneSampleMROneSampleMR 0.1.3

Frequently asked questions

What is the difference between ggsci and OneSampleMR?

Both compete on the same themes — r — within Analytics. ggsci 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 ggsci better than OneSampleMR?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. ggsci 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 ggsci?

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

What are the best alternatives to OneSampleMR?

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