← Back to home
Comparison · Analytics

randomwalk vs STACAS

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

randomwalk vs STACAS: at a glance

FeaturerandomwalkSTACAS
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themeswebassembly, shinylive, webr, simulationsingle-cell, batch-correction, data-integration, seurat
Last editorial update3h ago1h ago
WebsiteVisit →Visit →

What is randomwalk?

randomwalk spent every release getting an R simulation to run in the browser, not on a server.

A random walk and fractal-growth simulation package whose entire visible history is about its browser deployment. Six releases in four weeks moved a Shinylive dashboard from a blank black page to a working app — WebAssembly mounted from GitHub releases, CORS resolved by same-origin serving, missing plotting dependencies installed in-browser, then an async version using crew workers with its own debug log. A correctness fix followed, adding termination-position validation so simulations stop producing isolated pixels, and the most recent release publishes the package itself as a webR binary repository.

Read the full randomwalk trajectory →

What is STACAS?

Single-cell batch correction that learned to use cell labels, then spent three releases chasing Seurat.

STACAS integrates single-cell RNA-seq datasets by finding and weighting anchors between them, with rPCA-distance-based downweighting and an optional semi-supervised mode that uses cell type labels to discard inconsistent anchors. IntegrateData.STACAS() performs the integration natively rather than handing off, and StandardizeGeneSymbols() normalises gene naming across datasets before anchors are computed.

Read the full STACAS trajectory →

randomwalk vs STACAS: editorial side-by-side

R
randomwalk
ANALYTICS
0.0

randomwalk spent every release getting an R simulation to run in the browser, not on a server.

◆ Current state

A random walk and fractal-growth simulation package whose entire visible history is about its browser deployment. Six releases in four weeks moved a Shinylive dashboard from a blank black page to a working app — WebAssembly mounted from GitHub releases, CORS resolved by same-origin serving, missing plotting dependencies installed in-browser, then an async version using crew workers with its own debug log. A correctness fix followed, adding termination-position validation so simulations stop producing isolated pixels, and the most recent release publishes the package itself as a webR binary repository.

◆ Where it's heading

The package is being built as a browser artifact first and an R package second: the readme, the vignettes and the release notes all point at a hosted dashboard rather than at library(). The last release completes that by making the compiled WebAssembly build installable by anyone via webr::install(), which turns the deployment work into something reusable outside this project. Version numbers are unreliable here — v0.2.0 was published two weeks after v1.0.2 — so read the dates, not the tags.

◆ Prediction

With the webR repository published, the next work most likely moves back to the simulation itself, though the entries give no direct evidence of planned features.

S
STACAS
ANALYTICS
0.0

Single-cell batch correction that learned to use cell labels, then spent three releases chasing Seurat.

◆ Current state

STACAS integrates single-cell RNA-seq datasets by finding and weighting anchors between them, with rPCA-distance-based downweighting and an optional semi-supervised mode that uses cell type labels to discard inconsistent anchors. IntegrateData.STACAS() performs the integration natively rather than handing off, and StandardizeGeneSymbols() normalises gene naming across datasets before anchors are computed.

◆ Where it's heading

The method work concentrated in version 2.0 and has been stable since; everything after is Seurat compatibility and operational robustness. Versions 2.1.1 through 2.3.0 track Seurat v5 assays, v3-to-v5 conversion, multi-layer objects and SCT normalisation, with the genuinely useful additions — a reference seed dataset, max.seed.datasets for large-scale integration, min.sample.size — arriving as side effects of that work. The package is from the same lab as GeneNMF, and its release rhythm follows the single-cell ecosystem's upstream churn rather than an internal roadmap.

◆ Prediction

Expect the next release to follow further Seurat object-model changes, which have driven the last three. Nothing in the entries indicates new anchor-scoring or correction methodology in progress.

Alternatives to randomwalk and STACAS

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 randomwalk or STACAS.

See all randomwalk alternatives → · See all STACAS alternatives →

Recent activity from randomwalk and STACAS

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

  1. 8mo agorandomwalkPackage published as an installable webR binary repository
  2. 8mo agorandomwalkTermination validation removes isolated pixels from simulations
  3. 8mo agorandomwalkAsync dashboard with crew workers running under WebR
  4. 9mo agorandomwalkBrowser dashboard working end to end
  5. 9mo agorandomwalkMissing plot dependency and parameter display fixed
  6. 9mo agorandomwalkDashboard mounts WebAssembly from GitHub releases
  7. 1y agoSTACASMulti-layer objects and Seurat v3-to-v5 conversion handled
  8. 2y agoSTACASscale.data option for extreme batch effects; gene name conversion table
  9. 3y agoSTACASReference seeding, gene symbol standardisation, large-scale integration path
  10. 4y agoSTACASSemi-supervised integration and rPCA anchor downweighting
  11. 5y agoSTACASSeurat 4.0.0 compatibility and SCTransform support

Frequently asked questions

What is the difference between randomwalk and STACAS?

They serve adjacent needs but don't currently overlap on shipped themes. randomwalk and STACAS 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.

Is randomwalk better than STACAS?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. randomwalk and STACAS 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.

What are the best alternatives to randomwalk?

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

What are the best alternatives to STACAS?

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