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sccore vs sdsfun

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

Shared themes:r-package

sccore vs sdsfun: at a glance

Featuresccoresdsfun
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themessingle-cell, bioinformatics, r-package, cran-compliancespatial-statistics, geodetector, spatial-clustering, rcpp
Last editorial update3h ago1h ago
WebsiteVisit →Visit →

What is sccore?

Shared plumbing for the Kharchenko single-cell stack, updated once a year

sccore is the utility layer under the Kharchenko lab's single-cell packages — embedding plots, dot plots, parallel apply helpers and distance metrics that the downstream tools depend on rather than a tool researchers drive directly. The recent releases fix the Jensen-Shannon distance computation between matrix columns and add optional OpenMP support to the RcppArmadillo build. Cadence is roughly one CRAN release a year.

Read the full sccore trajectory →

What is sdsfun?

A spatial-statistics utility package exists to be depended on, and is built accordingly.

sdsfun collects spatial data science utilities — neighbour lists, spatial constrained clustering, discretization, dummy variable generation, geographical detector statistics and projection helpers — with the computationally heavy parts implemented in Rcpp. It was assembled quickly across late 2024, adding a function set roughly every three weeks, and has slowed since to a couple of releases a year. The most recent work is corrective: no longer initializing the RNG state at load, fixing matrix inputs misread as vectors, and clearing an Armadillo deprecation.

Read the full sdsfun trajectory →

sccore vs sdsfun: editorial side-by-side

S
sccore
ANALYTICS
0.0

Shared plumbing for the Kharchenko single-cell stack, updated once a year

◆ Current state

sccore is the utility layer under the Kharchenko lab's single-cell packages — embedding plots, dot plots, parallel apply helpers and distance metrics that the downstream tools depend on rather than a tool researchers drive directly. The recent releases fix the Jensen-Shannon distance computation between matrix columns and add optional OpenMP support to the RcppArmadillo build. Cadence is roughly one CRAN release a year.

◆ Where it's heading

Work splits cleanly into two streams: keeping the compiled build acceptable to CRAN as its Makevars policy shifts, and small correctness or interoperability fixes to the plotting and distance helpers. The interoperability thread is the one with direction — embeddingPlot() learning to read Seurat objects in 1.0.6 points at meeting users in the dominant single-cell framework rather than requiring the lab's own object types.

◆ Prediction

Expect the next release to be driven by a CRAN toolchain requirement or a downstream package's needs, with any user-facing change likely another interoperability or plotting fix rather than new capability.

S
sdsfun
ANALYTICS
0.0

A spatial-statistics utility package exists to be depended on, and is built accordingly.

◆ Current state

sdsfun collects spatial data science utilities — neighbour lists, spatial constrained clustering, discretization, dummy variable generation, geographical detector statistics and projection helpers — with the computationally heavy parts implemented in Rcpp. It was assembled quickly across late 2024, adding a function set roughly every three weeks, and has slowed since to a couple of releases a year. The most recent work is corrective: no longer initializing the RNG state at load, fixing matrix inputs misread as vectors, and clearing an Armadillo deprecation.

◆ Where it's heading

This is infrastructure for a family of packages rather than an end-user tool, and the changelog says so directly — functions were added to support gdverse and sesp, and moran_test was migrated in from geocomplexity. That migration pattern is the defining move: capability consolidates here so the downstream packages can share it instead of each carrying its own copy. Growth has slowed as that consolidation completed, leaving correctness and dependency upkeep.

◆ Prediction

Given the package moves when its dependents need something, the next release most likely brings in another shared function or responds to a downstream requirement rather than following its own plan. Armadillo and CRAN check changes remain the reliable source of maintenance work.

Alternatives to sccore and sdsfun

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 sccore or sdsfun.

See all sccore alternatives → · See all sdsfun alternatives →

Recent activity from sccore and sdsfun

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

  1. 4mo agosccoreJensen-Shannon distance fixed, OpenMP support added
  2. 10mo agosdsfunPackage load stops touching the RNG state
  3. 1y agosdsfunUnified partial correlation testing and head/tails discretization
  4. 1y agosccoreembeddingPlot() reads Seurat objects directly
  5. 1y agosdsfunMissing-value handling added to linear trend removal
  6. 1y agosdsfunCovariate-based detrending and long-to-matrix spatial reshaping
  7. 1y agosdsfunSpatially constrained hierarchical clustering and SPADE estimation
  8. 1y agosdsfunFast geodetector q-value estimator added
  9. 2y agosccoreVersion 1.0.5
  10. 3y agosccoreVersion 1.0.4
  11. 3y agosccoreVersion 1.0.3
  12. 3y agosccoreVersion 1.0.2

Frequently asked questions

What is the difference between sccore and sdsfun?

Both compete on the same themes — r-package — within Analytics. sccore and sdsfun 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 sccore better than sdsfun?

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

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

What are the best alternatives to sdsfun?

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